WorldWideScience

Sample records for multi-modal image fusion

  1. Multi-Modality Registration And Fusion Of Medical Image Data

    International Nuclear Information System (INIS)

    Kassak, P.; Vencko, D.; Cerovsky, I.

    2008-01-01

    Digitalisation of health care providing facilities allows US to maximize the usage of digital data from one patient obtained by various modalities. Complex view on to the problem can be achieved from the site of morphology as well as functionality. Multi-modal registration and fusion of medical image data is one of the examples that provides improved insight and allows more precise approach and treatment. (author)

  2. Extended feature-fusion guidelines to improve image-based multi-modal biometrics

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-09-01

    Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

  3. Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Multi-modality medical image fusion has more and more important applications in medical image analysisand understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fusemedical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusionresults when applying different selection rules and obtain optimum combination of fusion parameters.

  4. Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

    Directory of Open Access Journals (Sweden)

    Dane Brown

    2017-07-01

    Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

  5. On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

    Science.gov (United States)

    LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

    2017-12-01

    The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

  6. Noncontact Sleep Study by Multi-Modal Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Ku-young Chung

    2017-07-01

    Full Text Available Polysomnography (PSG is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

  7. Mixing of multi-modal images for conformational radiotherapy: application to patient re positioning; Fusion d`images multi-modales pour la radiotherapie conformationnelle: application au repositionnement du patient

    Energy Technology Data Exchange (ETDEWEB)

    Vassal, P

    1998-06-29

    This study shows a procedure of patient re positioning by comparative evaluation between the position of the patient and the theoretical expected position of the patient; the stagger between the two information gives the error of installation in translation and rotation. A correction is calculated and applied to the treatment environment (position and orientation of the patient, position and orientation of the irradiation source). The control system allows to determine the precise position of the tumor volume. The echography allows to determine the position of an organ.The surface captor is used to localize the tumors of the face or of the brain, with the respect to the face, the acquisition and the treatment of information take only few minutes. The X rays imager is applied for the localization of bones structures. (N.C.)

  8. Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

    Science.gov (United States)

    Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

    2018-02-01

    Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

  9. Drug-related webpages classification based on multi-modal local decision fusion

    Science.gov (United States)

    Hu, Ruiguang; Su, Xiaojing; Liu, Yanxin

    2018-03-01

    In this paper, multi-modal local decision fusion is used for drug-related webpages classification. First, meaningful text are extracted through HTML parsing, and effective images are chosen by the FOCARSS algorithm. Second, six SVM classifiers are trained for six kinds of drug-taking instruments, which are represented by PHOG. One SVM classifier is trained for the cannabis, which is represented by the mid-feature of BOW model. For each instance in a webpage, seven SVMs give seven labels for its image, and other seven labels are given by searching the names of drug-taking instruments and cannabis in its related text. Concatenating seven labels of image and seven labels of text, the representation of those instances in webpages are generated. Last, Multi-Instance Learning is used to classify those drugrelated webpages. Experimental results demonstrate that the classification accuracy of multi-instance learning with multi-modal local decision fusion is much higher than those of single-modal classification.

  10. Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling

    Directory of Open Access Journals (Sweden)

    Wenkai Zhang

    2017-12-01

    Full Text Available In recent years, Fully Convolutional Networks (FCN have led to a great improvement of semantic labeling for various applications including multi-modal remote sensing data. Although different fusion strategies have been reported for multi-modal data, there is no in-depth study of the reasons of performance limits. For example, it is unclear, why an early fusion of multi-modal data in FCN does not lead to a satisfying result. In this paper, we investigate the contribution of individual layers inside FCN and propose an effective fusion strategy for the semantic labeling of color or infrared imagery together with elevation (e.g., Digital Surface Models. The sensitivity and contribution of layers concerning classes and multi-modal data are quantified by recall and descent rate of recall in a multi-resolution model. The contribution of different modalities to the pixel-wise prediction is analyzed explaining the reason of the poor performance caused by the plain concatenation of different modalities. Finally, based on the analysis an optimized scheme for the fusion of layers with image and elevation information into a single FCN model is derived. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset (infrared and RGB imagery as well as elevation and the Potsdam dataset (RGB imagery and elevation. Comprehensive evaluations demonstrate the potential of the proposed approach.

  11. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  12. A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

    Science.gov (United States)

    Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

    2018-02-19

    The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

  13. Multi-modality molecular imaging: pre-clinical laboratory configuration

    Science.gov (United States)

    Wu, Yanjun; Wellen, Jeremy W.; Sarkar, Susanta K.

    2006-02-01

    In recent years, the prevalence of in vivo molecular imaging applications has rapidly increased. Here we report on the construction of a multi-modality imaging facility in a pharmaceutical setting that is expected to further advance existing capabilities for in vivo imaging of drug distribution and the interaction with their target. The imaging instrumentation in our facility includes a microPET scanner, a four wavelength time-domain optical imaging scanner, a 9.4T/30cm MRI scanner and a SPECT/X-ray CT scanner. An electronics shop and a computer room dedicated to image analysis are additional features of the facility. The layout of the facility was designed with a central animal preparation room surrounded by separate laboratory rooms for each of the major imaging modalities to accommodate the work-flow of simultaneous in vivo imaging experiments. This report will focus on the design of and anticipated applications for our microPET and optical imaging laboratory spaces. Additionally, we will discuss efforts to maximize the daily throughput of animal scans through development of efficient experimental work-flows and the use of multiple animals in a single scanning session.

  14. Visual tracking for multi-modality computer-assisted image guidance

    Science.gov (United States)

    Basafa, Ehsan; Foroughi, Pezhman; Hossbach, Martin; Bhanushali, Jasmine; Stolka, Philipp

    2017-03-01

    With optical cameras, many interventional navigation tasks previously relying on EM, optical, or mechanical guidance can be performed robustly, quickly, and conveniently. We developed a family of novel guidance systems based on wide-spectrum cameras and vision algorithms for real-time tracking of interventional instruments and multi-modality markers. These navigation systems support the localization of anatomical targets, support placement of imaging probe and instruments, and provide fusion imaging. The unique architecture - low-cost, miniature, in-hand stereo vision cameras fitted directly to imaging probes - allows for an intuitive workflow that fits a wide variety of specialties such as anesthesiology, interventional radiology, interventional oncology, emergency medicine, urology, and others, many of which see increasing pressure to utilize medical imaging and especially ultrasound, but have yet to develop the requisite skills for reliable success. We developed a modular system, consisting of hardware (the Optical Head containing the mini cameras) and software (components for visual instrument tracking with or without specialized visual features, fully automated marker segmentation from a variety of 3D imaging modalities, visual observation of meshes of widely separated markers, instant automatic registration, and target tracking and guidance on real-time multi-modality fusion views). From these components, we implemented a family of distinct clinical and pre-clinical systems (for combinations of ultrasound, CT, CBCT, and MRI), most of which have international regulatory clearance for clinical use. We present technical and clinical results on phantoms, ex- and in-vivo animals, and patients.

  15. Modeling decision-making in single- and multi-modal medical images

    Science.gov (United States)

    Canosa, R. L.; Baum, K. G.

    2009-02-01

    This research introduces a mode-specific model of visual saliency that can be used to highlight likely lesion locations and potential errors (false positives and false negatives) in single-mode PET and MRI images and multi-modal fused PET/MRI images. Fused-modality digital images are a relatively recent technological improvement in medical imaging; therefore, a novel component of this research is to characterize the perceptual response to these fused images. Three different fusion techniques were compared to single-mode displays in terms of observer error rates using synthetic human brain images generated from an anthropomorphic phantom. An eye-tracking experiment was performed with naÃve (non-radiologist) observers who viewed the single- and multi-modal images. The eye-tracking data allowed the errors to be classified into four categories: false positives, search errors (false negatives never fixated), recognition errors (false negatives fixated less than 350 milliseconds), and decision errors (false negatives fixated greater than 350 milliseconds). A saliency model consisting of a set of differentially weighted low-level feature maps is derived from the known error and ground truth locations extracted from a subset of the test images for each modality. The saliency model shows that lesion and error locations attract visual attention according to low-level image features such as color, luminance, and texture.

  16. Compositional-prior-guided image reconstruction algorithm for multi-modality imaging

    Science.gov (United States)

    Fang, Qianqian; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

    2010-01-01

    The development of effective multi-modality imaging methods typically requires an efficient information fusion model, particularly when combining structural images with a complementary imaging modality that provides functional information. We propose a composition-based image segmentation method for X-ray digital breast tomosynthesis (DBT) and a structural-prior-guided image reconstruction for a combined DBT and diffuse optical tomography (DOT) breast imaging system. Using the 3D DBT images from 31 clinically measured healthy breasts, we create an empirical relationship between the X-ray intensities for adipose and fibroglandular tissue. We use this relationship to then segment another 58 healthy breast DBT images from 29 subjects into compositional maps of different tissue types. For each breast, we build a weighted-graph in the compositional space and construct a regularization matrix to incorporate the structural priors into a finite-element-based DOT image reconstruction. Use of the compositional priors enables us to fuse tissue anatomy into optical images with less restriction than when using a binary segmentation. This allows us to recover the image contrast captured by DOT but not by DBT. We show that it is possible to fine-tune the strength of the structural priors by changing a single regularization parameter. By estimating the optical properties for adipose and fibroglandular tissue using the proposed algorithm, we found the results are comparable or superior to those estimated with expert-segmentations, but does not involve the time-consuming manual selection of regions-of-interest. PMID:21258460

  17. Structured and Sparse Canonical Correlation Analysis as a Brain-Wide Multi-Modal Data Fusion Approach.

    Science.gov (United States)

    Mohammadi-Nejad, Ali-Reza; Hossein-Zadeh, Gholam-Ali; Soltanian-Zadeh, Hamid

    2017-07-01

    Multi-modal data fusion has recently emerged as a comprehensive neuroimaging analysis approach, which usually uses canonical correlation analysis (CCA). However, the current CCA-based fusion approaches face problems like high-dimensionality, multi-collinearity, unimodal feature selection, asymmetry, and loss of spatial information in reshaping the imaging data into vectors. This paper proposes a structured and sparse CCA (ssCCA) technique as a novel CCA method to overcome the above problems. To investigate the performance of the proposed algorithm, we have compared three data fusion techniques: standard CCA, regularized CCA, and ssCCA, and evaluated their ability to detect multi-modal data associations. We have used simulations to compare the performance of these approaches and probe the effects of non-negativity constraint, the dimensionality of features, sample size, and noise power. The results demonstrate that ssCCA outperforms the existing standard and regularized CCA-based fusion approaches. We have also applied the methods to real functional magnetic resonance imaging (fMRI) and structural MRI data of Alzheimer's disease (AD) patients (n = 34) and healthy control (HC) subjects (n = 42) from the ADNI database. The results illustrate that the proposed unsupervised technique differentiates the transition pattern between the subject-course of AD patients and HC subjects with a p-value of less than 1×10 -6 . Furthermore, we have depicted the brain mapping of functional areas that are most correlated with the anatomical changes in AD patients relative to HC subjects.

  18. Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

    Science.gov (United States)

    Fuerst, Bernhard; Tateno, Keisuke; Johnson, Alex; Fotouhi, Javad; Osgood, Greg; Tombari, Federico; Navab, Nassir

    2017-01-01

    Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red–green–blue–depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion. PMID:29184659

  19. Computer-based image analysis in radiological diagnostics and image-guided therapy: 3D-Reconstruction, contrast medium dynamics, surface analysis, radiation therapy and multi-modal image fusion

    International Nuclear Information System (INIS)

    Beier, J.

    2001-01-01

    This book deals with substantial subjects of postprocessing and analysis of radiological image data, a particular emphasis was put on pulmonary themes. For a multitude of purposes the developed methods and procedures can directly be transferred to other non-pulmonary applications. The work presented here is structured in 14 chapters, each describing a selected complex of research. The chapter order reflects the sequence of the processing steps starting from artefact reduction, segmentation, visualization, analysis, therapy planning and image fusion up to multimedia archiving. In particular, this includes virtual endoscopy with three different scene viewers (Chap. 6), visualizations of the lung disease bronchiectasis (Chap. 7), surface structure analysis of pulmonary tumors (Chap. 8), quantification of contrast medium dynamics from temporal 2D and 3D image sequences (Chap. 9) as well as multimodality image fusion of arbitrary tomographical data using several visualization techniques (Chap. 12). Thus, the software systems presented cover the majority of image processing applications necessary in radiology and were entirely developed, implemented and validated in the clinical routine of a university medical school. (orig.) [de

  20. Multi-modal brain imaging software for guiding invasive treatment of epilepsy

    NARCIS (Netherlands)

    Ossenblok, P.P.W.; Marien, S.; Meesters, S.P.L.; Florack, L.M.J.; Hofman, P.; Schijns, O.E.M.G.; Colon, A.

    2017-01-01

    Purpose: The surgical treatment of patients with complex epilepsies is changing more and more from open, invasive surgery towards minimally invasive, image guided treatment. Multi-modal brain imaging procedures are developed to delineate preoperatively the region of the brain which is responsible

  1. Facile Fabrication of Animal-Specific Positioning Molds For Multi-modality Molecular Imaging

    International Nuclear Information System (INIS)

    Park, Jeong Chan; Oh, Ji Eun; Woo, Seung Tae

    2008-01-01

    Recently multi-modal imaging system has become widely adopted in molecular imaging. We tried to fabricate animal-specific positioning molds for PET/MR fusion imaging using easily available molding clay and rapid foam. The animal-specific positioning molds provide immobilization and reproducible positioning of small animal. Herein, we have compared fiber-based molding clay with rapid foam in fabricating the molds of experimental animal. The round bottomed-acrylic frame, which fitted into microPET gantry, was prepared at first. The experimental mice was anesthetized and placed on the mold for positioning. Rapid foam and fiber-based clay were used to fabricate the mold. In case of both rapid foam and the clay, the experimental animal needs to be pushed down smoothly into the mold for positioning. However, after the mouse was removed, the fabricated clay needed to be dried completely at 60 .deg. C in oven overnight for hardening. Four sealed pipe tips containing [ 18 F]FDG solution were used as fiduciary markers. After injection of [ 18 F]FDG via tail vein, microPET scanning was performed. Successively, MRI scanning was followed in the same animal. Animal-specific positioning molds were fabricated using rapid foam and fiber-based molding clay for multimodality imaging. Functional and anatomical images were obtained with microPET and MRI, respectively. The fused PET/MR images were obtained using freely available AMIDE program. Animal-specific molds were successfully prepared using easily available rapid foam, molding clay and disposable pipet tips. Thanks to animal-specific molds, fusion images of PET and MR were co-registered with negligible misalignment

  2. Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

    International Nuclear Information System (INIS)

    Joshi, Bishnu P.; Wang, Thomas D.

    2010-01-01

    Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research

  3. Multi-modal image registration: matching MRI with histology

    NARCIS (Netherlands)

    Alić, L.; Haeck, J.C.; Klein, S.; Bol, K.; Tiel, S.T. van; Wielopolski, P.A.; Bijster, M.; Niessen, W.J.; Bernsen, M.; Veenland, J.F.; Jong, M. de

    2010-01-01

    Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co

  4. Multi-modal image registration: matching MRI with histology

    Science.gov (United States)

    Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

    2010-03-01

    Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

  5. Accuracy and reproducibility of tumor positioning during prolonged and multi-modality animal imaging studies

    International Nuclear Information System (INIS)

    Zhang Mutian; Huang Minming; Le, Carl; Zanzonico, Pat B; Ling, C Clifton; Koutcher, Jason A; Humm, John L; Claus, Filip; Kolbert, Katherine S; Martin, Kyle

    2008-01-01

    Dedicated small-animal imaging devices, e.g. positron emission tomography (PET), computed tomography (CT) and magnetic resonance imaging (MRI) scanners, are being increasingly used for translational molecular imaging studies. The objective of this work was to determine the positional accuracy and precision with which tumors in situ can be reliably and reproducibly imaged on dedicated small-animal imaging equipment. We designed, fabricated and tested a custom rodent cradle with a stereotactic template to facilitate registration among image sets. To quantify tumor motion during our small-animal imaging protocols, 'gold standard' multi-modality point markers were inserted into tumor masses on the hind limbs of rats. Three types of imaging examination were then performed with the animals continuously anesthetized and immobilized: (i) consecutive microPET and MR images of tumor xenografts in which the animals remained in the same scanner for 2 h duration, (ii) multi-modality imaging studies in which the animals were transported between distant imaging devices and (iii) serial microPET scans in which the animals were repositioned in the same scanner for subsequent images. Our results showed that the animal tumor moved by less than 0.2-0.3 mm over a continuous 2 h microPET or MR imaging session. The process of transporting the animal between instruments introduced additional errors of ∼0.2 mm. In serial animal imaging studies, the positioning reproducibility within ∼0.8 mm could be obtained.

  6. Evaluation of registration strategies for multi-modality images of rat brain slices

    International Nuclear Information System (INIS)

    Palm, Christoph; Vieten, Andrea; Salber, Dagmar; Pietrzyk, Uwe

    2009-01-01

    In neuroscience, small-animal studies frequently involve dealing with series of images from multiple modalities such as histology and autoradiography. The consistent and bias-free restacking of multi-modality image series is obligatory as a starting point for subsequent non-rigid registration procedures and for quantitative comparisons with positron emission tomography (PET) and other in vivo data. Up to now, consistency between 2D slices without cross validation using an inherent 3D modality is frequently presumed to be close to the true morphology due to the smooth appearance of the contours of anatomical structures. However, in multi-modality stacks consistency is difficult to assess. In this work, consistency is defined in terms of smoothness of neighboring slices within a single modality and between different modalities. Registration bias denotes the distortion of the registered stack in comparison to the true 3D morphology and shape. Based on these metrics, different restacking strategies of multi-modality rat brain slices are experimentally evaluated. Experiments based on MRI-simulated and real dual-tracer autoradiograms reveal a clear bias of the restacked volume despite quantitatively high consistency and qualitatively smooth brain structures. However, different registration strategies yield different inter-consistency metrics. If no genuine 3D modality is available, the use of the so-called SOP (slice-order preferred) or MOSOP (modality-and-slice-order preferred) strategy is recommended.

  7. Multi-Modal Curriculum Learning for Semi-Supervised Image Classification.

    Science.gov (United States)

    Gong, Chen; Tao, Dacheng; Maybank, Stephen J; Liu, Wei; Kang, Guoliang; Yang, Jie

    2016-07-01

    Semi-supervised image classification aims to classify a large quantity of unlabeled images by typically harnessing scarce labeled images. Existing semi-supervised methods often suffer from inadequate classification accuracy when encountering difficult yet critical images, such as outliers, because they treat all unlabeled images equally and conduct classifications in an imperfectly ordered sequence. In this paper, we employ the curriculum learning methodology by investigating the difficulty of classifying every unlabeled image. The reliability and the discriminability of these unlabeled images are particularly investigated for evaluating their difficulty. As a result, an optimized image sequence is generated during the iterative propagations, and the unlabeled images are logically classified from simple to difficult. Furthermore, since images are usually characterized by multiple visual feature descriptors, we associate each kind of features with a teacher, and design a multi-modal curriculum learning (MMCL) strategy to integrate the information from different feature modalities. In each propagation, each teacher analyzes the difficulties of the currently unlabeled images from its own modality viewpoint. A consensus is subsequently reached among all the teachers, determining the currently simplest images (i.e., a curriculum), which are to be reliably classified by the multi-modal learner. This well-organized propagation process leveraging multiple teachers and one learner enables our MMCL to outperform five state-of-the-art methods on eight popular image data sets.

  8. TU-C-BRD-01: Image Guided SBRT I: Multi-Modality 4D Imaging

    International Nuclear Information System (INIS)

    Cai, J; Mageras, G; Pan, T

    2014-01-01

    Motion management is one of the critical technical challenges for radiation therapy. 4D imaging has been rapidly adopted as essential tool to assess organ motion associated with respiratory breathing. A variety of 4D imaging techniques have been developed and are currently under development based on different imaging modalities such as CT, MRI, PET, and CBCT. Each modality provides specific and complementary information about organ and tumor respiratory motion. Effective use of each different technique or combined use of different techniques can introduce a comprehensive management of tumor motion. Specifically, these techniques have afforded tremendous opportunities to better define and delineate tumor volumes, more accurately perform patient positioning, and effectively apply highly conformal therapy techniques such as IMRT and SBRT. Successful implementation requires good understanding of not only each technique, including unique features, limitations, artifacts, imaging acquisition and process, but also how to systematically apply the information obtained from different imaging modalities using proper tools such as deformable image registration. Furthermore, it is important to understand the differences in the effects of breathing variation between different imaging modalities. A comprehensive motion management strategy using multi-modality 4D imaging has shown promise in improving patient care, but at the same time faces significant challenges. This session will focuses on the current status and advances in imaging respiration-induced organ motion with different imaging modalities: 4D-CT, 4D-MRI, 4D-PET, and 4D-CBCT/DTS. Learning Objectives: Understand the need and role of multimodality 4D imaging in radiation therapy. Understand the underlying physics behind each 4D imaging technique. Recognize the advantages and limitations of each 4D imaging technique

  9. Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

    Science.gov (United States)

    Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

    2015-01-01

    The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

  10. SU-E-I-83: Error Analysis of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using a Preclinical Multi-Modality QA Phantom

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Y [University of Kansas Hospital, Kansas City, KS (United States); Fullerton, G; Goins, B [University of Texas Health Science Center at San Antonio, San Antonio, TX (United States)

    2015-06-15

    Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group; 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement

  11. Multi-modality image reconstruction for dual-head small-animal PET

    International Nuclear Information System (INIS)

    Huang, Chang-Han; Chou, Cheng-Ying

    2015-01-01

    The hybrid positron emission tomography/computed tomography (PET/CT) or positron emission tomography/magnetic resonance imaging (PET/MRI) has become routine practice in clinics. The applications of multi-modality imaging can also benefit research advances. Consequently, dedicated small-imaging system like dual-head small-animal PET (DHAPET) that possesses the advantages of high detection sensitivity and high resolution can exploit the structural information from CT or MRI. It should be noted that the special detector arrangement in DHAPET leads to severe data truncation, thereby degrading the image quality. We proposed to take advantage of anatomical priors and total variation (TV) minimization methods to reconstruct PET activity distribution form incomplete measurement data. The objective is to solve the penalized least-squares function consisted of data fidelity term, TV norm and medium root priors. In this work, we employed the splitting-based fast iterative shrinkage/thresholding algorithm to split smooth and non-smooth functions in the convex optimization problems. Our simulations studies validated that the images reconstructed by use of the proposed method can outperform those obtained by use of conventional expectation maximization algorithms or that without considering the anatomical prior information. Additionally, the convergence rate is also accelerated.

  12. Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

    Science.gov (United States)

    Rababaah, Haroun; Shirkhodaie, Amir

    2009-04-01

    The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

  13. The role of multi modality imaging in selecting patients and guiding lead placement for the delivery of cardiac resynchronization therapy.

    Science.gov (United States)

    Behar, Jonathan M; Claridge, Simon; Jackson, Tom; Sieniewicz, Ben; Porter, Bradley; Webb, Jessica; Rajani, Ronak; Kapetanakis, Stamatis; Carr-White, Gerald; Rinaldi, Christopher A

    2017-02-01

    Cardiac resynchronization therapy (CRT) is an effective pacemaker delivered treatment for selected patients with heart failure with the target of restoring electro-mechanical synchrony. Imaging techniques using echocardiography have as yet failed to find a metric of dyssynchrony to predict CRT response. Current guidelines are thus unchanged in recommending prolonged QRS duration, severe systolic function and refractory heart failure symptoms as criteria for CRT implantation. Evolving strain imaging techniques in 3D echocardiography, cardiac MRI and CT may however, overcome limitations of older methods and yield more powerful CRT response predictors. Areas covered: In this review, we firstly discuss the use of multi modality cardiac imaging in the selection of patients for CRT implantation and predicting the response to CRT. Secondly we examine the clinical evidence on avoiding areas of myocardial scar, targeting areas of dyssynchrony and in doing so, achieving the optimal positioning of the left ventricular lead to deliver CRT. Finally, we present the latest clinical studies which are integrating both clinical and imaging data with X-rays during the implantation in order to improve the accuracy of LV lead placement. Expert commentary: Image integration and fusion of datasets with live X-Ray angiography to guide procedures in real time is now a reality for some implanting centers. Such hybrid facilities will enable users to interact with images, allowing measurement, annotation and manipulation with instantaneous visualization on the catheter laboratory monitor. Such advances will serve as an invaluable adjunct for implanting physicians to accurately deliver pacemaker leads into the optimal position to deliver CRT.

  14. A multi-modality concept for radiotherapy planning with imaging techniques

    International Nuclear Information System (INIS)

    Schultze, J.

    1993-01-01

    The reported multi-modality concept of radiotherapy planning in the LAN can be realised in any hospital with standard equipment, although in some cases by way of auxiliary configurations. A software is currently developed as a tool for reducing the entire planning work. The heart of any radiotherapy planning is the therapy simulator, which has to be abreast with the requirements of modern radiotherapy. Integration of tomograpy, digitalisation, and electronic data processing has added important modalities to therapy planning which allow more precise target volume definition, and better biophysical planning. This is what is needed in order to achieve well differentiated radiotherapy for treatment of the manifold tumors, and the quality standards expected by the supervisory quality assurance regime and the population. At present, the CT data still are transferred indirect, on storage media, to the EDP processing system of the radiotherapy planning system. Based on the tomographic slices given by the imaging data, the contours and technical problem solutions are derived automatically, either for multi-field radiotherapy or moving field irradiation, depending on the anatomy or the targets to be protected from ionizing radiation. (orig./VHE) [de

  15. Detecting Pedestrian Flocks by Fusion of Multi-Modal Sensors in Mobile Phones

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun; Wirz, Martin; Roggen, Daniel

    2012-01-01

    derived from multiple sensor modalities of modern smartphones. Automatic detection of flocks has several important applications, including evacuation management and socially aware computing. The novelty of this paper is, firstly, to use data fusion techniques to combine several sensor modalities (WiFi...

  16. Role of the multi-modality image archival and communication system in nuclear medicine

    International Nuclear Information System (INIS)

    Bela Kari; Adam Mester; Erno Mako; Zoltan Gyorfi; Bela Mihalik; Zsolt; Hegyi

    2004-01-01

    Various non-invasive imaging systems produce increasing amount of diagnostic images day by day in digital format. The direct consequence of this tendency places electronic archives and image transfers in spotlight. Moreover, the digital image archives may support any other activities like simultaneous displaying of multi-modality images, telediagnostics, on-line consultation, construction of standard databases for dedicated organs by regional and/or country wide (e.g. myocardial scintigraphy, mammography, etc....) in order to obtain much more exact diagnosis as well as to support education and training. Our institute started similar research and developing activities few years ago, resulting the construction of our PACS systems -MEDISA LINUX Debian and eRAD ImageMedical TM LINUX Red Hat- together with the telecommunication part. Mass storage unit of PACS is based on hard drives connecting in RAID with l.2Tbyte capacity. The on-line telecommunication system consists of an ISDN Multi-Media System (MMS) and Internet based independent units. MMS was dedicated mainly for on-line teleconferencing and consultation by the simultaneously transferred morphological and functional images obtaining from the central archives by DICOM or any other allowable image formats. MMS has been created as a part and requirements of an EU research project - RETRANSPLANT -. The central archives -PACS- can be accessed by DICOM 3.0 protocol on Internet surface through well maintained and secure access rights. Displaying and post-processing of any retrieved images on individual workstations are supported by eRAD ImageMedical TM PracticeBuilder1-2-3 (Window based) image manager with its unique supports and services. The 'real engine' of PracticeBuilder is Ver.5.0 or newer Internet Explorer. The unique feature of PracticelBuilder1-2-3 is the extremely fast patient and image access from the archives even from very 'far distance' (through continents), due to the exceptional image communication

  17. Detection of relationships among multi-modal brain imaging meta-features via information flow.

    Science.gov (United States)

    Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

    2018-01-15

    Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is

  18. vECTlab-A fully integrated multi-modality Monte Carlo simulation framework for the radiological imaging sciences

    International Nuclear Information System (INIS)

    Peter, Joerg; Semmler, Wolfhard

    2007-01-01

    Alongside and in part motivated by recent advances in molecular diagnostics, the development of dual-modality instruments for patient and dedicated small animal imaging has gained attention by diverse research groups. The desire for such systems is high not only to link molecular or functional information with the anatomical structures, but also for detecting multiple molecular events simultaneously at shorter total acquisition times. While PET and SPECT have been integrated successfully with X-ray CT, the advance of optical imaging approaches (OT) and the integration thereof into existing modalities carry a high application potential, particularly for imaging small animals. A multi-modality Monte Carlo (MC) simulation approach at present has been developed that is able to trace high-energy (keV) as well as optical (eV) photons concurrently within identical phantom representation models. We show that the involved two approaches for ray-tracing keV and eV photons can be integrated into a unique simulation framework which enables both photon classes to be propagated through various geometry models representing both phantoms and scanners. The main advantage of such integrated framework for our specific application is the investigation of novel tomographic multi-modality instrumentation intended for in vivo small animal imaging through time-resolved MC simulation upon identical phantom geometries. Design examples are provided for recently proposed SPECT-OT and PET-OT imaging systems

  19. Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

    Science.gov (United States)

    Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

    2018-05-01

    In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

  20. WE-H-206-02: Recent Advances in Multi-Modality Molecular Imaging of Small Animals

    Energy Technology Data Exchange (ETDEWEB)

    Tsui, B. [Johns Hopkins University (United States)

    2016-06-15

    Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly

  1. WE-H-206-02: Recent Advances in Multi-Modality Molecular Imaging of Small Animals

    International Nuclear Information System (INIS)

    Tsui, B.

    2016-01-01

    Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly

  2. Multi-modality imaging review of congenital abnormalities of kidney and upper urinary tract.

    Science.gov (United States)

    Ramanathan, Subramaniyan; Kumar, Devendra; Khanna, Maneesh; Al Heidous, Mahmoud; Sheikh, Adnan; Virmani, Vivek; Palaniappan, Yegu

    2016-02-28

    Congenital abnormalities of the kidney and urinary tract (CAKUT) include a wide range of abnormalities ranging from asymptomatic ectopic kidneys to life threatening renal agenesis (bilateral). Many of them are detected in the antenatal or immediate postnatal with a significant proportion identified in the adult population with varying degree of severity. CAKUT can be classified on embryological basis in to abnormalities in the renal parenchymal development, aberrant embryonic migration and abnormalities of the collecting system. Renal parenchymal abnormalities include multi cystic dysplastic kidneys, renal hypoplasia, number (agenesis or supernumerary), shape and cystic renal diseases. Aberrant embryonic migration encompasses abnormal location and fusion anomalies. Collecting system abnormalities include duplex kidneys and Pelvi ureteric junction obstruction. Ultrasonography (US) is typically the first imaging performed as it is easily available, non-invasive and radiation free used both antenatally and postnatally. Computed tomography (CT) and magnetic resonance imaging (MRI) are useful to confirm the ultrasound detected abnormality, detection of complex malformations, demonstration of collecting system and vascular anatomy and more importantly for early detection of complications like renal calculi, infection and malignancies. As CAKUT are one of the leading causes of end stage renal disease, it is important for the radiologists to be familiar with the varying imaging appearances of CAKUT on US, CT and MRI, thereby helping in prompt diagnosis and optimal management.

  3. Quantitative multi-modal NDT data analysis

    International Nuclear Information System (INIS)

    Heideklang, René; Shokouhi, Parisa

    2014-01-01

    A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundant information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity

  4. Performance study of a fan beam collimator designed for a multi-modality small animal imaging device

    International Nuclear Information System (INIS)

    Sabbir Ahmed, ASM; Kramer, Gary H.; Semmler, Wolfrad; Peter, Jorg

    2011-01-01

    This paper describes the methodology to design and conduct the performances of a fan beam collimator. This fan beam collimator was designed to use with a multi-modality small animal imaging device and the performance of the collimator was studied for a 3D geometry. Analytical expressions were formulated to calculate the parameters for the collimator. A Monte Carlo model was developed to analyze the scattering and image noises for a 3D object. The results showed that the performance of the fan beam collimator was strongly dependent on the source distribution and position. The fan beam collimator showed increased counting efficiency in comparison to a parallel hole collimator. Inside attenuating medium, the increased attenuating effect outweighed the fan beam increased counting efficiency.

  5. Assessment of rigid multi-modality image registration consistency using the multiple sub-volume registration (MSR) method

    International Nuclear Information System (INIS)

    Ceylan, C; Heide, U A van der; Bol, G H; Lagendijk, J J W; Kotte, A N T J

    2005-01-01

    Registration of different imaging modalities such as CT, MRI, functional MRI (fMRI), positron (PET) and single photon (SPECT) emission tomography is used in many clinical applications. Determining the quality of any automatic registration procedure has been a challenging part because no gold standard is available to evaluate the registration. In this note we present a method, called the 'multiple sub-volume registration' (MSR) method, for assessing the consistency of a rigid registration. This is done by registering sub-images of one data set on the other data set, performing a crude non-rigid registration. By analysing the deviations (local deformations) of the sub-volume registrations from the full registration we get a measure of the consistency of the rigid registration. Registration of 15 data sets which include CT, MR and PET images for brain, head and neck, cervix, prostate and lung was performed utilizing a rigid body registration with normalized mutual information as the similarity measure. The resulting registrations were classified as good or bad by visual inspection. The resulting registrations were also classified using our MSR method. The results of our MSR method agree with the classification obtained from visual inspection for all cases (p < 0.02 based on ANOVA of the good and bad groups). The proposed method is independent of the registration algorithm and similarity measure. It can be used for multi-modality image data sets and different anatomic sites of the patient. (note)

  6. Multi-modal neuroimaging in premanifest and early Huntington's disease: 18 month longitudinal data from the IMAGE-HD study.

    Science.gov (United States)

    Domínguez D, Juan F; Egan, Gary F; Gray, Marcus A; Poudel, Govinda R; Churchyard, Andrew; Chua, Phyllis; Stout, Julie C; Georgiou-Karistianis, Nellie

    2013-01-01

    IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI) study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively). In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume) and microstructural (diffusivity) longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter) and in caudate and putamen (volume and diffusivity change). Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years), close to diagnosis (fractional anisotropy, FA), only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.

  7. Multi-Modal Imaging in a Mouse Model of Orthotopic Lung Cancer

    OpenAIRE

    Patel, Priya; Kato, Tatsuya; Ujiie, Hideki; Wada, Hironobu; Lee, Daiyoon; Hu, Hsin-pei; Hirohashi, Kentaro; Ahn, Jin Young; Zheng, Jinzi; Yasufuku, Kazuhiro

    2016-01-01

    Background Investigation of CF800, a novel PEGylated nano-liposomal imaging agent containing indocyanine green (ICG) and iohexol, for real-time near infrared (NIR) fluorescence and computed tomography (CT) image-guided surgery in an orthotopic lung cancer model in nude mice. Methods CF800 was intravenously administered into 13 mice bearing the H460 orthotopic human lung cancer. At 48 h post-injection (peak imaging agent accumulation time point), ex vivo NIR and CT imaging was performed. A cli...

  8. Interactive, multi-modality image registrations for combined MRI/MRSI-planned HDR prostate brachytherapy

    Directory of Open Access Journals (Sweden)

    Galen Reed

    2011-03-01

    Full Text Available Purpose: This study presents the steps and criteria involved in the series of image registrations used clinically during the planning and dose delivery of focal high dose-rate (HDR brachytherapy of the prostate. Material and methods: Three imaging modalities – Magnetic Resonance Imaging (MRI, Magnetic Resonance Spectroscopic Imaging (MRSI, and Computed Tomography (CT – were used at different steps during the process. MRSI is used for identification of dominant intraprosatic lesions (DIL. A series of rigid and nonrigid transformations were applied to the data to correct for endorectal-coil-induced deformations and for alignment with the planning CT. Mutual information was calculated as a morphing metric. An inverse planning optimization algorithm was applied to boost dose to the DIL while providing protection to the urethra, penile bulb, rectum, and bladder. Six prostate cancer patients were treated using this protocol. Results: The morphing algorithm successfully modeled the probe-induced prostatic distortion. Mutual information calculated between the morphed images and images acquired without the endorectal probe showed a significant (p = 0.0071 increase to that calculated between the unmorphed images and images acquired without the endorectal probe. Both mutual information and visual inspection serve as effective diagnostics of image morphing. The entire procedure adds less than thirty minutes to the treatment planning. Conclusion: This work demonstrates the utility of image transformations and registrations to HDR brachytherapy of prostate cancer.

  9. Novelty detection of foreign objects in food using multi-modal X-ray imaging

    DEFF Research Database (Denmark)

    Einarsdottir, Hildur; Emerson, Monica Jane; Clemmensen, Line Katrine Harder

    2016-01-01

    In this paper we demonstrate a method for novelty detection of foreign objects in food products using grating-based multimodal X-ray imaging. With this imaging technique three modalities are available with pixel correspondence, enhancing organic materials such as wood chips, insects and soft...... plastics not detectable by conventional X-ray absorption radiography. We conduct experiments, where several food products are imaged with common foreign objects typically found in the food processing industry. To evaluate the benefit from using this multi-contrast X-ray technique over conventional X......-ray absorption imaging, a novelty detection scheme based on well known image- and statistical analysis techniques is proposed. The results show that the presented method gives superior recognition results and highlights the advantage of grating-based imaging....

  10. Multi-modality imaging of tumor phenotype and response to therapy

    Science.gov (United States)

    Nyflot, Matthew J.

    2011-12-01

    Imaging and radiation oncology have historically been closely linked. However, the vast majority of techniques used in the clinic involve anatomical imaging. Biological imaging offers the potential for innovation in the areas of cancer diagnosis and staging, radiotherapy target definition, and treatment response assessment. Some relevant imaging techniques are FDG PET (for imaging cellular metabolism), FLT PET (proliferation), CuATSM PET (hypoxia), and contrast-enhanced CT (vasculature and perfusion). Here, a technique for quantitative spatial correlation of tumor phenotype is presented for FDG PET, FLT PET, and CuATSM PET images. Additionally, multimodality imaging of treatment response with FLT PET, CuATSM, and dynamic contrast-enhanced CT is presented, in a trial of patients receiving an antiangiogenic agent (Avastin) combined with cisplatin and radiotherapy. Results are also presented for translational applications in animal models, including quantitative assessment of proliferative response to cetuximab with FLT PET and quantification of vascular volume with a blood-pool contrast agent (Fenestra). These techniques have clear applications to radiobiological research and optimized treatment strategies, and may eventually be used for personalized therapy for patients.

  11. Expert consensus for multi-modality imaging evaluation of cardiovascular complications of radiotherapy in adults

    DEFF Research Database (Denmark)

    Lancellotti, Patrizio; Nkomo, Vuyisile T; Badano, Luigi P

    2013-01-01

    . A comprehensive review of potential cardiac complications related to radiotherapy is warranted. An evidence-based review of several imaging approaches used to detect, evaluate, and monitor RIHD is discussed. Recommendations for the early identification and monitoring of cardiovascular complications...

  12. Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

    Science.gov (United States)

    Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

    2015-03-01

    Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

  13. VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

    Science.gov (United States)

    Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

    2016-01-01

    In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the

  14. Multi-Modal Imaging in a Mouse Model of Orthotopic Lung Cancer.

    Science.gov (United States)

    Patel, Priya; Kato, Tatsuya; Ujiie, Hideki; Wada, Hironobu; Lee, Daiyoon; Hu, Hsin-Pei; Hirohashi, Kentaro; Ahn, Jin Young; Zheng, Jinzi; Yasufuku, Kazuhiro

    2016-01-01

    Investigation of CF800, a novel PEGylated nano-liposomal imaging agent containing indocyanine green (ICG) and iohexol, for real-time near infrared (NIR) fluorescence and computed tomography (CT) image-guided surgery in an orthotopic lung cancer model in nude mice. CF800 was intravenously administered into 13 mice bearing the H460 orthotopic human lung cancer. At 48 h post-injection (peak imaging agent accumulation time point), ex vivo NIR and CT imaging was performed. A clinical NIR imaging system (SPY®, Novadaq) was used to measure fluorescence intensity of tumor and lung. Tumor-to-background-ratios (TBR) were calculated in inflated and deflated states. The mean Hounsfield unit (HU) of lung tumor was quantified using the CT data set and a semi-automated threshold-based method. Histological evaluation using H&E, the macrophage marker F4/80 and the endothelial cell marker CD31, was performed, and compared to the liposomal fluorescence signal obtained from adjacent tissue sections. The fluorescence TBR measured when the lung is in the inflated state (2.0 ± 0.58) was significantly greater than in the deflated state (1.42 ± 0.380 (n = 7, p<0.003). Mean fluorescent signal in tumor was highly variable across samples, (49.0 ± 18.8 AU). CT image analysis revealed greater contrast enhancement in lung tumors (a mean increase of 110 ± 57 HU) when CF800 is administered compared to the no contrast enhanced tumors (p = 0.0002). Preliminary data suggests that the high fluorescence TBR and CT tumor contrast enhancement provided by CF800 may have clinical utility in localization of lung cancer during CT and NIR image-guided surgery.

  15. Automatic registration of multi-modal microscopy images for integrative analysis of prostate tissue sections

    International Nuclear Information System (INIS)

    Lippolis, Giuseppe; Edsjö, Anders; Helczynski, Leszek; Bjartell, Anders; Overgaard, Niels Chr

    2013-01-01

    Prostate cancer is one of the leading causes of cancer related deaths. For diagnosis, predicting the outcome of the disease, and for assessing potential new biomarkers, pathologists and researchers routinely analyze histological samples. Morphological and molecular information may be integrated by aligning microscopic histological images in a multiplex fashion. This process is usually time-consuming and results in intra- and inter-user variability. The aim of this study is to investigate the feasibility of using modern image analysis methods for automated alignment of microscopic images from differently stained adjacent paraffin sections from prostatic tissue specimens. Tissue samples, obtained from biopsy or radical prostatectomy, were sectioned and stained with either hematoxylin & eosin (H&E), immunohistochemistry for p63 and AMACR or Time Resolved Fluorescence (TRF) for androgen receptor (AR). Image pairs were aligned allowing for translation, rotation and scaling. The registration was performed automatically by first detecting landmarks in both images, using the scale invariant image transform (SIFT), followed by the well-known RANSAC protocol for finding point correspondences and finally aligned by Procrustes fit. The Registration results were evaluated using both visual and quantitative criteria as defined in the text. Three experiments were carried out. First, images of consecutive tissue sections stained with H&E and p63/AMACR were successfully aligned in 85 of 88 cases (96.6%). The failures occurred in 3 out of 13 cores with highly aggressive cancer (Gleason score ≥ 8). Second, TRF and H&E image pairs were aligned correctly in 103 out of 106 cases (97%). The third experiment considered the alignment of image pairs with the same staining (H&E) coming from a stack of 4 sections. The success rate for alignment dropped from 93.8% in adjacent sections to 22% for sections furthest away. The proposed method is both reliable and fast and therefore well suited

  16. Multi-Modality Imaging in the Evaluation and Treatment of Mitral Regurgitation.

    Science.gov (United States)

    Bouchard, Marc-André; Côté-Laroche, Claudia; Beaudoin, Jonathan

    2017-10-13

    Mitral regurgitation (MR) is frequent and associated with increased mortality and morbidity when severe. It may be caused by intrinsic valvular disease (primary MR) or ventricular deformation (secondary MR). Imaging has a critical role to document the severity, mechanism, and impact of MR on heart function as selected patients with MR may benefit from surgery whereas other will not. In patients planned for a surgical intervention, imaging is also important to select candidates for mitral valve (MV) repair over replacement and to predict surgical success. Although standard transthoracic echocardiography is the first-line modality to evaluate MR, newer imaging modalities like three-dimensional (3D) transesophageal echocardiography, stress echocardiography, cardiac magnetic resonance (CMR), and computed tomography (CT) are emerging and complementary tools for MR assessment. While some of these modalities can provide insight into MR severity, others will help to determine its mechanism. Understanding the advantages and limitations of each imaging modality is important to appreciate their respective role for MR assessment and help to resolve eventual discrepancies between different diagnostic methods. With the increasing use of transcatheter mitral procedures (repair or replacement) for high-surgical-risk patients, multimodality imaging has now become even more important to determine eligibility, preinterventional planning, and periprocedural guidance.

  17. Automatic classification of early Parkinson's disease with multi-modal MR imaging.

    Directory of Open Access Journals (Sweden)

    Dan Long

    Full Text Available BACKGROUND: In recent years, neuroimaging has been increasingly used as an objective method for the diagnosis of Parkinson's disease (PD. Most previous studies were based on invasive imaging modalities or on a single modality which was not an ideal diagnostic tool. In this study, we developed a non-invasive technology intended for use in the diagnosis of early PD by integrating the advantages of various modals. MATERIALS AND METHODS: Nineteen early PD patients and twenty-seven normal volunteers participated in this study. For each subject, we collected resting-state functional magnetic resonance imaging (rsfMRI and structural images. For the rsfMRI images, we extracted the characteristics at three different levels: ALFF (amplitude of low-frequency fluctuations, ReHo (regional homogeneity and RFCS (regional functional connectivity strength. For the structural images, we extracted the volume characteristics from the gray matter (GM, the white matter (WM and the cerebrospinal fluid (CSF. A two-sample t-test was used for the feature selection, and then the remaining features were fused for classification. Finally a classifier for early PD patients and normal control subjects was identified from support vector machine training. The performance of the classifier was evaluated using the leave-one-out cross-validation method. RESULTS: Using the proposed methods to classify the data set, good results (accuracy  = 86.96%, sensitivity  = 78.95%, specificity  = 92.59% were obtained. CONCLUSIONS: This method demonstrates a promising diagnosis performance by the integration of information from a variety of imaging modalities, and it shows potential for improving the clinical diagnosis and treatment of PD.

  18. Multi-modal and targeted imaging improves automated mid-brain segmentation

    Science.gov (United States)

    Plassard, Andrew J.; D'Haese, Pierre F.; Pallavaram, Srivatsan; Newton, Allen T.; Claassen, Daniel O.; Dawant, Benoit M.; Landman, Bennett A.

    2017-02-01

    The basal ganglia and limbic system, particularly the thalamus, putamen, internal and external globus pallidus, substantia nigra, and sub-thalamic nucleus, comprise a clinically relevant signal network for Parkinson's disease. In order to manually trace these structures, a combination of high-resolution and specialized sequences at 7T are used, but it is not feasible to scan clinical patients in those scanners. Targeted imaging sequences at 3T such as F-GATIR, and other optimized inversion recovery sequences, have been presented which enhance contrast in a select group of these structures. In this work, we show that a series of atlases generated at 7T can be used to accurately segment these structures at 3T using a combination of standard and optimized imaging sequences, though no one approach provided the best result across all structures. In the thalamus and putamen, a median Dice coefficient over 0.88 and a mean surface distance less than 1.0mm was achieved using a combination of T1 and an optimized inversion recovery imaging sequences. In the internal and external globus pallidus a Dice over 0.75 and a mean surface distance less than 1.2mm was achieved using a combination of T1 and FGATIR imaging sequences. In the substantia nigra and sub-thalamic nucleus a Dice coefficient of over 0.6 and a mean surface distance of less than 1.0mm was achieved using the optimized inversion recovery imaging sequence. On average, using T1 and optimized inversion recovery together produced significantly improved segmentation results than any individual modality (p<0.05 wilcox sign-rank test).

  19. Multi-modality imaging findings of huge intrachoroidal cavitation and myopic peripapillary sinkhole.

    Science.gov (United States)

    Chen, Yutong; Ma, Xiaoli; Hua, Rui

    2018-02-02

    Peripapillary intrachoroidal cavitation was described as the presence of an asymptomatic, well-circumscribed, yellow-orange, peripapillary lesion at the inferior border of the myopic conus in eyes with high myopia. A 66-year-old myopic Chinese man was enrolled and his multi-color imaging examination showed a well-circumscribed, caesious, peripapillary lesion coalesced with the optic nerve head vertically rotated and obliquely tilted, together with an inferotemporal sinkhole in the myopic conus. The optical coherence tomography images showed an intrachoroidal hyporeflective space, schisis, an intracavitary septum located below the retinal pigment epithelium and inserted beneath the optic nerve head, as well as a sinkhole between the peripapillary intrachoroidal cavitation and the vitreous space. Both myopic colobomas and sinkhole in myopic conus may contribute the coalescence of intrachoroidal cavitation with optic nerve head. These qualitative and quantitative new findings will be beneficial for understanding its pathomorphological mechanism, and the impact on optic nerve tissue of myopic patients.

  20. Exploring Multi-Modal and Structured Representation Learning for Visual Image and Video Understanding

    OpenAIRE

    Xu, Dan

    2018-01-01

    As the explosive growth of the visual data, it is particularly important to develop intelligent visual understanding techniques for dealing with a large amount of data. Many efforts have been made in recent years to build highly effective and large-scale visual processing algorithms and systems. One of the core aspects in the research line is how to learn robust representations to better describe the data. In this thesis we study the problem of visual image and video understanding and specifi...

  1. Multi-modality Imaging: Bird's eye view from the 2015 American Heart Association Scientific Sessions.

    Science.gov (United States)

    Einstein, Andrew J; Lloyd, Steven G; Chaudhry, Farooq A; AlJaroudi, Wael A; Hage, Fadi G

    2016-04-01

    Multiple novel studies were presented at the 2015 American Heart Association Scientific Sessions which was considered a successful conference at many levels. In this review, we will summarize key studies in nuclear cardiology, cardiac magnetic resonance, echocardiography, and cardiac computed tomography that were presented at the Sessions. We hope that this bird's eye view will keep readers updated on the newest imaging studies presented at the meeting whether or not they were able to attend the meeting.

  2. Multi-modal neuroimaging in premanifest and early Huntington's disease: 18 month longitudinal data from the IMAGE-HD study.

    Directory of Open Access Journals (Sweden)

    Juan F Domínguez D

    Full Text Available IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively. In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume and microstructural (diffusivity longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter and in caudate and putamen (volume and diffusivity change. Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years, close to diagnosis (<15 years and after diagnosis. Of the two diffusion metrics (mean diffusivity, MD; fractional anisotropy, FA, only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.

  3. Mixing of multi-modal images for conformational radiotherapy: application to patient re positioning

    International Nuclear Information System (INIS)

    Vassal, P.

    1998-01-01

    This study shows a procedure of patient re positioning by comparative evaluation between the position of the patient and the theoretical expected position of the patient; the stagger between the two information gives the error of installation in translation and rotation. A correction is calculated and applied to the treatment environment (position and orientation of the patient, position and orientation of the irradiation source). The control system allows to determine the precise position of the tumor volume. The echography allows to determine the position of an organ.The surface captor is used to localize the tumors of the face or of the brain, with the respect to the face, the acquisition and the treatment of information take only few minutes. The X rays imager is applied for the localization of bones structures. (N.C.)

  4. Integration of XNAT/PACS, DICOM, and research software for automated multi-modal image analysis

    Science.gov (United States)

    Gao, Yurui; Burns, Scott S.; Lauzon, Carolyn B.; Fong, Andrew E.; James, Terry A.; Lubar, Joel F.; Thatcher, Robert W.; Twillie, David A.; Wirt, Michael D.; Zola, Marc A.; Logan, Bret W.; Anderson, Adam W.; Landman, Bennett A.

    2013-03-01

    Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software.

  5. Application of multi-modality image coregistration in paediatric prosthetic endocarditis

    International Nuclear Information System (INIS)

    Kitsos, T.; Chung, D.K.; Howman-Giles, R.; Lau, Y.H.; University of Technology, Sydney, NSW

    2003-01-01

    This is a case where coregistration of Gallium and chest CT scans provided important clinical information which had a significant impact on management decisions. A 13-year-old girl from Noumea was transferred to our hospital for further management of S.haemolyticus bacteraemia. She had a history of complex congenital heart disease, requiring several cardiac surgical procedures. Seven months earlier she had a patch repair of the ventricular septum and formation of a right ventricle to pulmonary artery conduit. On admission she was generally unwell and had hemoptysis. She had fever to 39.9 deg C, oximetry of 83 per cent on room air, finger clubbing and a cardiac murmur. Chest X-ray and CT scans showed widespread pulmonary consolidation with bilateral pleural effusions. An echocardiogram showed no evidence of endocarditis. The crucial diagnostic dilemma was whether she had pneumonia or prosthetic endocarditis: the latter was more ominous and entailed high risk surgery. A Gallium whole body scan with chest SPECT showed focal localisation in the right mid chest. However, its location could not be confidently defined. A specifically developed computer program was used to co-register the Gallium SPECT and chest CT scans. The co-registered images conclusively localised the Gallium scan lesion to the prosthetic pulmonary outflow conduit, consistent with endocarditis. This triggered referral for cardiac MRI, which confirmed the diagnosis. In summary co-registration allowed precise structural localisation of focal Gallium uptake in the prosthetic pulmonary outflow conduit, with profound impact on the patient's diagnosis and subsequent management. This is an example of the potential benefits of co-registering structural and functional imaging modalities. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

  6. Articulatory mediation of speech perception: a causal analysis of multi-modal imaging data.

    Science.gov (United States)

    Gow, David W; Segawa, Jennifer A

    2009-02-01

    The inherent confound between the organization of articulation and the acoustic-phonetic structure of the speech signal makes it exceptionally difficult to evaluate the competing claims of motor and acoustic-phonetic accounts of how listeners recognize coarticulated speech. Here we use Granger causation analyzes of high spatiotemporal resolution neural activation data derived from the integration of magnetic resonance imaging, magnetoencephalography and electroencephalography, to examine the role of lexical and articulatory mediation in listeners' ability to use phonetic context to compensate for place assimilation. Listeners heard two-word phrases such as pen pad and then saw two pictures, from which they had to select the one that depicted the phrase. Assimilation, lexical competitor environment and the phonological validity of assimilation context were all manipulated. Behavioral data showed an effect of context on the interpretation of assimilated segments. Analysis of 40 Hz gamma phase locking patterns identified a large distributed neural network including 16 distinct regions of interest (ROIs) spanning portions of both hemispheres in the first 200 ms of post-assimilation context. Granger analyzes of individual conditions showed differing patterns of causal interaction between ROIs during this interval, with hypothesized lexical and articulatory structures and pathways driving phonetic activation in the posterior superior temporal gyrus in assimilation conditions, but not in phonetically unambiguous conditions. These results lend strong support for the motor theory of speech perception, and clarify the role of lexical mediation in the phonetic processing of assimilated speech.

  7. ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

    Science.gov (United States)

    Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

    2018-02-01

    Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

  8. Perspectives on How Human Simultaneous Multi-Modal Imaging Adds Directionality to Spread Models of Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Julia Neitzel

    2018-01-01

    Full Text Available Previous animal research suggests that the spread of pathological agents in Alzheimer’s disease (AD follows the direction of signaling pathways. Specifically, tau pathology has been suggested to propagate in an infection-like mode along axons, from transentorhinal cortices to medial temporal lobe cortices and consequently to other cortical regions, while amyloid-beta (Aβ pathology seems to spread in an activity-dependent manner among and from isocortical regions into limbic and then subcortical regions. These directed connectivity-based spread models, however, have not been tested directly in AD patients due to the lack of an in vivo method to identify directed connectivity in humans. Recently, a new method—metabolic connectivity mapping (MCM—has been developed and validated in healthy participants that uses simultaneous FDG-PET and resting-state fMRI data acquisition to identify directed intrinsic effective connectivity (EC. To this end, postsynaptic energy consumption (FDG-PET is used to identify regions with afferent input from other functionally connected brain regions (resting-state fMRI. Here, we discuss how this multi-modal imaging approach allows quantitative, whole-brain mapping of signaling direction in AD patients, thereby pointing out some of the advantages it offers compared to other EC methods (i.e., Granger causality, dynamic causal modeling, Bayesian networks. Most importantly, MCM provides the basis on which models of pathology spread, derived from animal studies, can be tested in AD patients. In particular, future work should investigate whether tau and Aβ in humans propagate along the trajectories of directed connectivity in order to advance our understanding of the neuropathological mechanisms causing disease progression.

  9. A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification

    CSIR Research Space (South Africa)

    Brown, K

    2016-05-01

    Full Text Available after basic pre-processing, consist- ing of image alignment, pixel normalization and histogram equalization. The following results relate to the various face and fingerprint datasets only. Local Binary Pattern Histogram (LBPH) proved to be a versatile... descriptor by increasing the radius in correlation to the interpolated neighbours. The modified ELBP operator significantly outperformed the histogram equalization and pixel normalization under dynamic lighting conditions. This was used before the LOG filter...

  10. Two Phase Non-Rigid Multi-Modal Image Registration Using Weber Local Descriptor-Based Similarity Metrics and Normalized Mutual Information

    Directory of Open Access Journals (Sweden)

    Feng Yang

    2013-06-01

    Full Text Available Non-rigid multi-modal image registration plays an important role in medical image processing and analysis. Existing image registration methods based on similarity metrics such as mutual information (MI and sum of squared differences (SSD cannot achieve either high registration accuracy or high registration efficiency. To address this problem, we propose a novel two phase non-rigid multi-modal image registration method by combining Weber local descriptor (WLD based similarity metrics with the normalized mutual information (NMI using the diffeomorphic free-form deformation (FFD model. The first phase aims at recovering the large deformation component using the WLD based non-local SSD (wldNSSD or weighted structural similarity (wldWSSIM. Based on the output of the former phase, the second phase is focused on getting accurate transformation parameters related to the small deformation using the NMI. Extensive experiments on T1, T2 and PD weighted MR images demonstrate that the proposed wldNSSD-NMI or wldWSSIM-NMI method outperforms the registration methods based on the NMI, the conditional mutual information (CMI, the SSD on entropy images (ESSD and the ESSD-NMI in terms of registration accuracy and computation efficiency.

  11. Development of comprehensive image processing technique for differential diagnosis of liver disease by using multi-modality images. Pixel-based cross-correlation method using a profile

    International Nuclear Information System (INIS)

    Inoue, Akira; Okura, Yasuhiko; Akiyama, Mitoshi; Ishida, Takayuki; Kawashita, Ikuo; Ito, Katsuyoshi; Matsunaga, Naofumi; Sanada, Taizo

    2009-01-01

    Imaging techniques such as high magnetic field imaging and multidetector-row CT have been markedly improved recently. The final image-reading systems easily produce more than a thousand diagnostic images per patient. Therefore, we developed a comprehensive cross-correlation processing technique using multi-modality images, in order to decrease the considerable time and effort involved in the interpretation of a radiogram (multi-formatted display and/or stack display method, etc). In this scheme, the criteria of an attending radiologist for the differential diagnosis of liver cyst, hemangioma of liver, hepatocellular carcinoma, and metastatic liver cancer on magnetic resonance images with various sequences and CT images with and without contrast enhancement employ a cross-correlation coefficient. Using a one-dimensional cross-correlation method, comprehensive image processing could be also adapted for various artifacts (some depending on modality imaging, and some on patients), which may be encountered at the clinical scene. This comprehensive image-processing technique could assist radiologists in the differential diagnosis of liver diseases. (author)

  12. Diagnostic role of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for early and atypical bone metastases.

    Science.gov (United States)

    Chen, Xiao-Liang; Li, Qian; Cao, Lin; Jiang, Shi-Xi

    2014-01-01

    The bone metastasis appeared early before the bone imaging for most of the above patients. (99)Tc(m)-MDP ((99)Tc(m) marked methylene diphosphonate) bone imaging could diagnosis the bone metastasis with highly sensitivity, but with lower specificity. The aim of this study is to explore the diagnostic value of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for the early period atypical bone metastases. 15 to 30 mCi (99)Tc(m)-MDP was intravenously injected to the 34 malignant patients diagnosed as doubtful early bone metastases. SPECT, CT and SPECT/CT images were captured and analyzed consequently. For the patients diagnosed as early period atypical bone metastases by SPECT/CT, combining the SPECT/CT and MRI together as the SPECT/MRI integrated image. The obtained SPECT/MRI image was analyzed and compared with the pathogenic results of patients. The results indicated that 34 early period doubtful metastatic focus, including 34 SPECT positive focus, 17 focus without special changes by using CT method, 11 bone metastases focus by using SPECT/CT method, 23 doubtful bone metastases focus, 8 doubtful bone metastases focus, 14 doubtful bone metastases focus and 2 focus without clear image. Totally, SPECT/CT combined with SPECT/MRI method diagnosed 30 bone metastatic focus and 4 doubtfully metastatic focus. In conclusion, (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging shows a higher diagnostic value for the early period bone metastases, which also enhances the diagnostic accuracy rate.

  13. CT, MRI and PET image fusion using the ProSoma 3D simulation software

    International Nuclear Information System (INIS)

    Dalah, E.; Bradley, D.A.; Nisbet, A.; Reise, S.

    2008-01-01

    Full text: Multi-modality imaging is involved in almost all oncology applications focusing on the extent of disease and target volume delineation. Commercial image fusion software packages are becoming available but require comprehensive evaluation to ensure reliability of fusion and the underpinning registration algorithm particularly for radiotherapy. The present work seeks to assess such accuracy for a number of available registration methods provided by the commercial package ProSoma. A NEMA body phantom was used in evaluating CT, MR and PET images. In addition, discussion is provided concerning the choice and geometry of fiducial markers in phantom studies and the effect of window-level on target size, in particular in regard to the application of multi modality imaging in treatment planning. In general, the accuracy of fusion of multi-modality images was within 0.5-1.5 mm of actual feature diameters and < 2 ml volume of actual values, particularly in CT images. (author)

  14. Imaging brain activity during seizures in freely behaving rats using a miniature multi-modal imaging system.

    Science.gov (United States)

    Sigal, Iliya; Koletar, Margaret M; Ringuette, Dene; Gad, Raanan; Jeffrey, Melanie; Carlen, Peter L; Stefanovic, Bojana; Levi, Ofer

    2016-09-01

    We report on a miniature label-free imaging system for monitoring brain blood flow and blood oxygenation changes in awake, freely behaving rats. The device, weighing 15 grams, enables imaging in a ∼ 2 × 2 mm field of view with 4.4 μm lateral resolution and 1 - 8 Hz temporal sampling rate. The imaging is performed through a chronically-implanted cranial window that remains optically clear between 2 to > 6 weeks after the craniotomy. This imaging method is well suited for longitudinal studies of chronic models of brain diseases and disorders. In this work, it is applied to monitoring neurovascular coupling during drug-induced absence-like seizures 6 weeks following the craniotomy.

  15. Identification, diagnostic assistance and planning methods that use multi-modality imaging for prostate cancer focal therapies

    International Nuclear Information System (INIS)

    Makni, Nasr

    2010-01-01

    Prostate cancer is one of the leading causes of death from cancer among men. In In the last decade, new diagnosis procedures and treatment options have been developed and made possible thanks to the recent progress in prostate imaging modalities. The newest challenges in this field are to detect the smallest tumors and to treat locally to minimise the treatment morbidity. In this thesis, we introduce a set of automatic image processing methods for the guidance and assistance of diagnosis and treatment, in laser-based prostate cancer focal therapies. In the first part of this work, segmentation and computer-aided detection algorithms have been developed for the enhancement of image-based diagnosis of prostate cancer. First, we propose a novel approach that combines Markov Random Fields framework with an Active Shape Model, in order to extract three dimensional outlines of the gland from Magnetic Resonance Imaging (MRI) data. Second, prostate's MRI volume is segmented into peripheral and central zones: we introduce a method that explores features of multispectral MRI, and is based on belief functions and the modelling of an a priori knowledge as an additional source of information. Finally, computer-aided detection of prostate's peripheral zone tumors is investigated by experimenting novel texture features based on fractal geometry-based. These parameters, extracted from morphological MRI, were tested using both supervised and unsupervised classification methods. The results of these different approaches were studied and compared. The second part of this work addresses the guidance of laser-based focal ablation of prostate tumors. A novel non rigid registration method is introduced for fusion of pre-operative MRI and planning data, and per-operative ultrasound imaging. We test and evaluate our algorithms using simulated data and physical phantoms, which enable comparison to ground truth. Patients' data, combined to expert interpretation, are also used in the

  16. Multi-modality PET-CT imaging of breast cancer in an animal model using nanoparticle x-ray contrast agent and 18F-FDG

    Science.gov (United States)

    Badea, C. T.; Ghaghada, K.; Espinosa, G.; Strong, L.; Annapragada, A.

    2011-03-01

    Multi-modality PET-CT imaging is playing an important role in the field of oncology. While PET imaging facilitates functional interrogation of tumor status, the use of CT imaging is primarily limited to anatomical reference. In an attempt to extract comprehensive information about tumor cells and its microenvironment, we used a nanoparticle xray contrast agent to image tumor vasculature and vessel 'leakiness' and 18F-FDG to investigate the metabolic status of tumor cells. In vivo PET/CT studies were performed in mice implanted with 4T1 mammary breast cancer cells.Early-phase micro-CT imaging enabled visualization 3D vascular architecture of the tumors whereas delayedphase micro-CT demonstrated highly permeable vessels as evident by nanoparticle accumulation within the tumor. Both imaging modalities demonstrated the presence of a necrotic core as indicated by a hypo-enhanced region in the center of the tumor. At early time-points, the CT-derived fractional blood volume did not correlate with 18F-FDG uptake. At delayed time-points, the tumor enhancement in 18F-FDG micro-PET images correlated with the delayed signal enhanced due to nanoparticle extravasation seen in CT images. The proposed hybrid imaging approach could be used to better understand tumor angiogenesis and to be the basis for monitoring and evaluating anti-angiogenic and nano-chemotherapies.

  17. [Application of 3D virtual reality technology with multi-modality fusion in resection of glioma located in central sulcus region].

    Science.gov (United States)

    Chen, T N; Yin, X T; Li, X G; Zhao, J; Wang, L; Mu, N; Ma, K; Huo, K; Liu, D; Gao, B Y; Feng, H; Li, F

    2018-05-08

    Objective: To explore the clinical and teaching application value of virtual reality technology in preoperative planning and intraoperative guide of glioma located in central sulcus region. Method: Ten patients with glioma in the central sulcus region were proposed to surgical treatment. The neuro-imaging data, including CT, CTA, DSA, MRI, fMRI were input to 3dgo sczhry workstation for image fusion and 3D reconstruction. Spatial relationships between the lesions and the surrounding structures on the virtual reality image were obtained. These images were applied to the operative approach design, operation process simulation, intraoperative auxiliary decision and the training of specialist physician. Results: Intraoperative founding of 10 patients were highly consistent with preoperative simulation with virtual reality technology. Preoperative 3D reconstruction virtual reality images improved the feasibility of operation planning and operation accuracy. This technology had not only shown the advantages for neurological function protection and lesion resection during surgery, but also improved the training efficiency and effectiveness of dedicated physician by turning the abstract comprehension to virtual reality. Conclusion: Image fusion and 3D reconstruction based virtual reality technology in glioma resection is helpful for formulating the operation plan, improving the operation safety, increasing the total resection rate, and facilitating the teaching and training of the specialist physician.

  18. The Multi-modal Australian ScienceS Imaging and Visualisation Environment (MASSIVE high performance computing infrastructure: applications in neuroscience and neuroinformatics research

    Directory of Open Access Journals (Sweden)

    Wojtek James eGoscinski

    2014-03-01

    Full Text Available The Multi-modal Australian ScienceS Imaging and Visualisation Environment (MASSIVE is a national imaging and visualisation facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organisation (CSIRO, and the Victorian Partnership for Advanced Computing (VPAC, with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI, x-ray computer tomography (CT, electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i integrated multiple different neuroimaging analysis software components, (ii enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research.

  19. Prospective, longitudinal, multi-modal functional imaging for radical chemo-IMRT treatment of locally advanced head and neck cancer: the INSIGHT study

    International Nuclear Information System (INIS)

    Welsh, Liam; Panek, Rafal; McQuaid, Dualta; Dunlop, Alex; Schmidt, Maria; Riddell, Angela; Koh, Dow-Mu; Doran, Simon; Murray, Iain; Du, Yong; Chua, Sue; Hansen, Vibeke; Wong, Kee H.; Dean, Jamie; Gulliford, Sarah; Bhide, Shreerang; Leach, Martin O.; Nutting, Christopher; Harrington, Kevin; Newbold, Kate

    2015-01-01

    Radical chemo-radiotherapy (CRT) is an effective organ-sparing treatment option for patients with locally advanced head and neck cancer (LAHNC). Despite advances in treatment for LAHNC, a significant minority of these patients continue to fail to achieve complete response with standard CRT. By constructing a multi-modality functional imaging (FI) predictive biomarker for CRT outcome for patients with LAHNC we hope to be able to reliably identify those patients at high risk of failing standard CRT. Such a biomarker would in future enable CRT to be tailored to the specific biological characteristics of each patients’ tumour, potentially leading to improved treatment outcomes. The INSIGHT study is a single-centre, prospective, longitudinal multi-modality imaging study using functional MRI and FDG-PET/CT for patients with LAHNC squamous cell carcinomas receiving radical CRT. Two cohorts of patients are being recruited: one treated with, and another treated without, induction chemotherapy. All patients receive radical intensity modulated radiotherapy with concurrent chemotherapy. Patients undergo functional imaging before, during and 3 months after completion of radiotherapy, as well as at the time of relapse, should that occur within the first two years after treatment. Serum samples are collected from patients at the same time points as the FI scans for analysis of a panel of serum markers of tumour hypoxia. The primary aim of the INSIGHT study is to acquire a prospective multi-parametric longitudinal data set comprising functional MRI, FDG PET/CT, and serum biomarker data from patients with LAHNC undergoing primary radical CRT. This data set will be used to construct a predictive imaging biomarker for outcome after CRT for LAHNC. This predictive imaging biomarker will be used in future studies of functional imaging based treatment stratification for patients with LAHNC. Additional objectives are: defining the reproducibility of FI parameters; determining robust

  20. A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration.

    Directory of Open Access Journals (Sweden)

    Hengkai Guo

    Full Text Available Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US and magnetic resonance (MR. Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods.

  1. [A preliminary research on multi-source medical image fusion].

    Science.gov (United States)

    Kang, Yuanyuan; Li, Bin; Tian, Lianfang; Mao, Zongyuan

    2009-04-01

    Multi-modal medical image fusion has important value in clinical diagnosis and treatment. In this paper, the multi-resolution analysis of Daubechies 9/7 Biorthogonal Wavelet Transform is introduced for anatomical and functional image fusion, then a new fusion algorithm with the combination of local standard deviation and energy as texture measurement is presented. At last, a set of quantitative evaluation criteria is given. Experiments show that both anatomical and metabolism information can be obtained effectively, and both the edge and texture features can be reserved successfully. The presented algorithm is more effective than the traditional algorithms.

  2. Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging.

    Directory of Open Access Journals (Sweden)

    Danuta M Sampson

    Full Text Available To present en face optical coherence tomography (OCT images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities.En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO and microperimetry.Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE pathology due to segmentation error at the level of Bruch's membrane (BM. Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities.Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis.

  3. STTARR: a radiation treatment and multi-modal imaging facility for fast tracking novel agent development in small animal models

    International Nuclear Information System (INIS)

    Yeung, Ivan; McKee, Trevor; Jaffray, David; Hill, Richard

    2014-01-01

    Small animal models play a pivotal role in the pipeline development of novel agents and strategies in personalized cancer therapy. The Spatio-Temporal Targeting and Amplification of Radiation Response Program (STTARR) consists of an animal imaging and precision radiation facility designed to provide innovative biologic imaging and targeted radiation treatment strategies in small animals. The design is to mirror the imaging and radiation treatment facility in a modern cancer center. The STTARR features imaging equipment of small animal scale including CT, MRI, PET, SPECT, Optical devices as well as image guided irradiators. The fleet of imaging and irradiation equipment provides a platform for identification of biological targets of the specific molecular pathways that influence both tumor progression and a patient's response to radiation therapy. Examples will be given in the utilization of the imaging facilities for development in novel approaches in cancer therapy including a PET-FAZA study for hypoxia measurement in a pancreatic adenocarcinoma xenograft model. In addition, the cone-beam image guided small animal irradiator developed at our institute will also be described. The animal platform (couch) provides motion in 3 dimensions to position the animal to the isocentre of the beam. A pair of rotational arms supporting the X-ray/detector pair enables acquisition of cone-beam images of the animal which give rise to image guided precision of 0.5 mm. The irradiation energy ranges from 50 to 225 kVp at a dose rate from 10-400 cGy/min. The gantry is able to direct X-ray beam of different directions to give conformal radiation treatment to the animal. A dedicated treatment planning system is able to perform treatment planning and provide commonly used clinical metrics in the animal treatment plan. Examples will be given to highlight the use of the image guided irradiator for research of drug/irradiation regimen in animal models. (author)

  4. Superparamagnetic iron oxide nanoparticles function as a long-term, multi-modal imaging label for non-invasive tracking of implanted progenitor cells.

    Directory of Open Access Journals (Sweden)

    Christina A Pacak

    Full Text Available The purpose of this study was to determine the ability of superparamagnetic iron oxide (SPIO nanoparticles to function as a long-term tracking label for multi-modal imaging of implanted engineered tissues containing muscle-derived progenitor cells using magnetic resonance imaging (MRI and X-ray micro-computed tomography (μCT. SPIO-labeled primary myoblasts were embedded in fibrin sealant and imaged to obtain intensity data by MRI or radio-opacity information by μCT. Each imaging modality displayed a detection gradient that matched increasing SPIO concentrations. Labeled cells were then incorporated in fibrin sealant, injected into the atrioventricular groove of rat hearts, and imaged in vivo and ex vivo for up to 1 year. Transplanted cells were identified in intact animals and isolated hearts using both imaging modalities. MRI was better able to detect minuscule amounts of SPIO nanoparticles, while μCT more precisely identified the location of heavily-labeled cells. Histological analyses confirmed that iron oxide particles were confined to viable, skeletal muscle-derived cells in the implant at the expected location based on MRI and μCT. These analyses showed no evidence of phagocytosis of labeled cells by macrophages or release of nanoparticles from transplanted cells. In conclusion, we established that SPIO nanoparticles function as a sensitive and specific long-term label for MRI and μCT, respectively. Our findings will enable investigators interested in regenerative therapies to non-invasively and serially acquire complementary, high-resolution images of transplanted cells for one year using a single label.

  5. Development of a multi-scale and multi-modality imaging system to characterize tumours and their microenvironment in vivo

    Science.gov (United States)

    Rouffiac, Valérie; Ser-Leroux, Karine; Dugon, Emilie; Leguerney, Ingrid; Polrot, Mélanie; Robin, Sandra; Salomé-Desnoulez, Sophie; Ginefri, Jean-Christophe; Sebrié, Catherine; Laplace-Builhé, Corinne

    2015-03-01

    In vivo high-resolution imaging of tumor development is possible through dorsal skinfold chamber implantable on mice model. However, current intravital imaging systems are weakly tolerated along time by mice and do not allow multimodality imaging. Our project aims to develop a new chamber for: 1- long-term micro/macroscopic visualization of tumor (vascular and cellular compartments) and tissue microenvironment; and 2- multimodality imaging (photonic, MRI and sonography). Our new experimental device was patented in March 2014 and was primarily assessed on 75 mouse engrafted with 4T1-Luc tumor cell line, and validated in confocal and multiphoton imaging after staining the mice vasculature using Dextran 155KDa-TRITC or Dextran 2000kDa-FITC. Simultaneously, a universal stage was designed for optimal removal of respiratory and cardiac artifacts during microscopy assays. Experimental results from optical, ultrasound (Bmode and pulse subtraction mode) and MRI imaging (anatomic sequences) showed that our patented design, unlike commercial devices, improves longitudinal monitoring over several weeks (35 days on average against 12 for the commercial chamber) and allows for a better characterization of the early and late tissue alterations due to tumour development. We also demonstrated the compatibility for multimodality imaging and the increase of mice survival was by a factor of 2.9, with our new skinfold chamber. Current developments include: 1- defining new procedures for multi-labelling of cells and tissue (screening of fluorescent molecules and imaging protocols); 2- developing ultrasound and MRI imaging procedures with specific probes; 3- correlating optical/ultrasound/MRI data for a complete mapping of tumour development and microenvironment.

  6. MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

    International Nuclear Information System (INIS)

    Bergamaschi, A; Medjoubi, K; Somogyi, A; Messaoudi, C; Marco, S

    2017-01-01

    Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data. (paper)

  7. Multi-modal in vivo imaging of brain blood oxygenation, blood flow and neural calcium dynamics during acute seizures

    Science.gov (United States)

    Ringuette, Dene; Jeffrey, Melanie A.; Carlen, Peter L.; Levi, Ofer

    2016-03-01

    Dysfunction of the vascular endothelium has been implicated in the development of epilepsy. To better understand the relation between vascular function and seizure and provide a foundation for interpreting results from functional imaging in chronic disease models, we investigate the relationship between intracellular calcium dynamics and local cerebral blood flow and blood oxygen saturation during acute seizure-like events and pharmacological seizure rescue. To probe the relation between the aforementioned physiological markers in an acute model of epilepsy in rats, we integrated three different optical modalities together with electrophysiological recordings: Laser speckle contrast imaging (LSCI) was used to study changes in flow speeds, Intrinsic optical signal imaging (IOSI) was used to monitor changes in oxygenated, de-oxygenated, and total hemoglobin concentration, and Calcium-sensitive dye imaging was used to monitor intracellular calcium dynamics. We designed a dedicated cortical flow chamber to remove superficial blood and dye resulting from the injection procedure, which reduced spurious artifacts. The near infrared light used for IOSI and LSCI was delivered via a light pipe integrated with the flow chamber to minimize the effect of fluid surface movement on illumination stability. Calcium-sensitive dye was injected via a glass electrode used for recording the local field potential. Our system allowed us to observe and correlate increases in intracellular calcium, blood flow and blood volume during seizure-like events and provide a quantitative analysis of neurovascular coupling changes associated with seizure rescue via injection of an anti-convulsive agent.

  8. MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

    Science.gov (United States)

    Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A.

    2017-06-01

    Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data.

  9. Integration of multi-modality imaging for accurate 3D reconstruction of human coronary arteries in vivo

    International Nuclear Information System (INIS)

    Giannoglou, George D.; Chatzizisis, Yiannis S.; Sianos, George; Tsikaderis, Dimitrios; Matakos, Antonis; Koutkias, Vassilios; Diamantopoulos, Panagiotis; Maglaveras, Nicos; Parcharidis, George E.; Louridas, George E.

    2006-01-01

    In conventional intravascular ultrasound (IVUS)-based three-dimensional (3D) reconstruction of human coronary arteries, IVUS images are arranged linearly generating a straight vessel volume. However, with this approach real vessel curvature is neglected. To overcome this limitation an imaging method was developed based on integration of IVUS and biplane coronary angiography (BCA). In 17 coronary arteries from nine patients, IVUS and BCA were performed. From each angiographic projection, a single end-diastolic frame was selected and in each frame the IVUS catheter was interactively detected for the extraction of 3D catheter path. Ultrasound data was obtained with a sheath-based catheter and recorded on S-VHS videotape. S-VHS data was digitized and lumen and media-adventitia contours were semi-automatically detected in end-diastolic IVUS images. Each pair of contours was aligned perpendicularly to the catheter path and rotated in space by implementing an algorithm based on Frenet-Serret rules. Lumen and media-adventitia contours were interpolated through generation of intermediate contours creating a real 3D lumen and vessel volume, respectively. The absolute orientation of the reconstructed lumen was determined by back-projecting it onto both angiographic planes and comparing the projected lumen with the actual angiographic lumen. In conclusion, our method is capable of performing rapid and accurate 3D reconstruction of human coronary arteries in vivo. This technique can be utilized for reliable plaque morphometric, geometrical and hemodynamic analyses

  10. Automatic Quantification of Tumour Hypoxia From Multi-Modal Microscopy Images Using Weakly-Supervised Learning Methods.

    Science.gov (United States)

    Carneiro, Gustavo; Peng, Tingying; Bayer, Christine; Navab, Nassir

    2017-07-01

    In recently published clinical trial results, hypoxia-modified therapies have shown to provide more positive outcomes to cancer patients, compared with standard cancer treatments. The development and validation of these hypoxia-modified therapies depend on an effective way of measuring tumor hypoxia, but a standardized measurement is currently unavailable in clinical practice. Different types of manual measurements have been proposed in clinical research, but in this paper we focus on a recently published approach that quantifies the number and proportion of hypoxic regions using high resolution (immuno-)fluorescence (IF) and hematoxylin and eosin (HE) stained images of a histological specimen of a tumor. We introduce new machine learning-based methodologies to automate this measurement, where the main challenge is the fact that the clinical annotations available for training the proposed methodologies consist of the total number of normoxic, chronically hypoxic, and acutely hypoxic regions without any indication of their location in the image. Therefore, this represents a weakly-supervised structured output classification problem, where training is based on a high-order loss function formed by the norm of the difference between the manual and estimated annotations mentioned above. We propose four methodologies to solve this problem: 1) a naive method that uses a majority classifier applied on the nodes of a fixed grid placed over the input images; 2) a baseline method based on a structured output learning formulation that relies on a fixed grid placed over the input images; 3) an extension to this baseline based on a latent structured output learning formulation that uses a graph that is flexible in terms of the amount and positions of nodes; and 4) a pixel-wise labeling based on a fully-convolutional neural network. Using a data set of 89 weakly annotated pairs of IF and HE images from eight tumors, we show that the quantitative results of methods (3) and (4

  11. An automated multi-modal object analysis approach to coronary calcium scoring of adaptive heart isolated MSCT images

    Science.gov (United States)

    Wu, Jing; Ferns, Gordon; Giles, John; Lewis, Emma

    2012-02-01

    Inter- and intra- observer variability is a problem often faced when an expert or observer is tasked with assessing the severity of a disease. This issue is keenly felt in coronary calcium scoring of patients suffering from atherosclerosis where in clinical practice, the observer must identify firstly the presence, followed by the location of candidate calcified plaques found within the coronary arteries that may prevent oxygenated blood flow to the heart muscle. This can be challenging for a human observer as it is difficult to differentiate calcified plaques that are located in the coronary arteries from those found in surrounding anatomy such as the mitral valve or pericardium. The inclusion or exclusion of false positive or true positive calcified plaques respectively will alter the patient calcium score incorrectly, thus leading to the possibility of incorrect treatment prescription. In addition to the benefits to scoring accuracy, the use of fast, low dose multi-slice CT imaging to perform the cardiac scan is capable of acquiring the entire heart within a single breath hold. Thus exposing the patient to lower radiation dose, which for a progressive disease such as atherosclerosis where multiple scans may be required, is beneficial to their health. Presented here is a fully automated method for calcium scoring using both the traditional Agatston method, as well as the Volume scoring method. Elimination of the unwanted regions of the cardiac image slices such as lungs, ribs, and vertebrae is carried out using adaptive heart isolation. Such regions cannot contain calcified plaques but can be of a similar intensity and their removal will aid detection. Removal of both the ascending and descending aortas, as they contain clinical insignificant plaques, is necessary before the final calcium scores are calculated and examined against ground truth scores of three averaged expert observer results. The results presented here are intended to show the requirement and

  12. A fully automated multi-modal computer aided diagnosis approach to coronary calcium scoring of MSCT images

    Science.gov (United States)

    Wu, Jing; Ferns, Gordon; Giles, John; Lewis, Emma

    2012-03-01

    Inter- and intra- observer variability is a problem often faced when an expert or observer is tasked with assessing the severity of a disease. This issue is keenly felt in coronary calcium scoring of patients suffering from atherosclerosis where in clinical practice, the observer must identify firstly the presence, followed by the location of candidate calcified plaques found within the coronary arteries that may prevent oxygenated blood flow to the heart muscle. However, it can be difficult for a human observer to differentiate calcified plaques that are located in the coronary arteries from those found in surrounding anatomy such as the mitral valve or pericardium. In addition to the benefits to scoring accuracy, the use of fast, low dose multi-slice CT imaging to perform the cardiac scan is capable of acquiring the entire heart within a single breath hold. Thus exposing the patient to lower radiation dose, which for a progressive disease such as atherosclerosis where multiple scans may be required, is beneficial to their health. Presented here is a fully automated method for calcium scoring using both the traditional Agatston method, as well as the volume scoring method. Elimination of the unwanted regions of the cardiac image slices such as lungs, ribs, and vertebrae is carried out using adaptive heart isolation. Such regions cannot contain calcified plaques but can be of a similar intensity and their removal will aid detection. Removal of both the ascending and descending aortas, as they contain clinical insignificant plaques, is necessary before the final calcium scores are calculated and examined against ground truth scores of three averaged expert observer results. The results presented here are intended to show the feasibility and requirement for an automated scoring method to reduce the subjectivity and reproducibility error inherent with manual clinical calcium scoring.

  13. Robotic-Assisted Fluorescence Sentinel Lymph Node Mapping Using Multi-Modal Image-Guidance in an Animal Model

    Science.gov (United States)

    Liss, Michael A.; Stroup, Sean P.; Cand, Zhengtao Qin; Hoh, Carl; Hall, David J.; Vera, David R.; Kane, Christopher J.

    2015-01-01

    Objectives To investigate PET/CT pre-operative imaging and intraoperative detection of a fluorescent-labeled receptor-targeted radiopharmaceutical in a prostate cancer animal model. Methods Three male Beagle dogs underwent an intra-prostatic injection of fluorescent-tagged tilmanocept radio-labeled with both gallium-68 and technetium-99m. One hour after injection a pelvic PET/CT scan was performed for pre-operative sentinel lymph node (SLN) mapping. Definition of SLN was a standardized uptake value (SUV) that exceeded 5% of the lymph node with the highest SUV. Thirty-six hours later we performed robotic-assisted SLN dissection using a fluorescence-capable camera system. Fluorescent lymph nodes were clipped, the abdomen was opened, and the pelvic and retroperitoneal nodes were excised. All excised nodal packets were assayed by in vitro nuclear counting and reported as percent-of-injected dose. Results Pre-operative PET/CT imaging identified a median of three sentinel lymph nodes per animal. All sentinel lymph nodes (100%) identified by the PET/CT were fluorescent during robotic-assisted lymph node dissection. Of all fluorescent nodes visualized by the camera system, 83% (10/12) satisfied the 5%-rule defined by the PET/CT scan. The two lymph nodes that did not qualify accumulated less than 0.002% of the injected dose. Conclusions Fluorescent-labeled tilmanocept has optimal logistical properties to obtain pre-operative PET/CT and subsequent real-time intraoperative confirmation during robotic-assisted sentinel lymph node dissection. PMID:25139676

  14. Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation

    Directory of Open Access Journals (Sweden)

    Danny Eytan

    2016-01-01

    Full Text Available Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory, and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage

  15. Multi-modal magnetic resonance imaging and histology of vascular function in xenografts using macromolecular contrast agent hyperbranched polyglycerol (HPG-GdF).

    Science.gov (United States)

    Baker, Jennifer H E; McPhee, Kelly C; Moosvi, Firas; Saatchi, Katayoun; Häfeli, Urs O; Minchinton, Andrew I; Reinsberg, Stefan A

    2016-01-01

    Macromolecular gadolinium (Gd)-based contrast agents are in development as blood pool markers for MRI. HPG-GdF is a 583 kDa hyperbranched polyglycerol doubly tagged with Gd and Alexa 647 nm dye, making it both MR and histologically visible. In this study we examined the location of HPG-GdF in whole-tumor xenograft sections matched to in vivo DCE-MR images of both HPG-GdF and Gadovist. Despite its large size, we have shown that HPG-GdF extravasates from some tumor vessels and accumulates over time, but does not distribute beyond a few cell diameters from vessels. Fractional plasma volume (fPV) and apparent permeability-surface area product (aPS) parameters were derived from the MR concentration-time curves of HPG-GdF. Non-viable necrotic tumor tissue was excluded from the analysis by applying a novel bolus arrival time (BAT) algorithm to all voxels. aPS derived from HPG-GdF was the only MR parameter to identify a difference in vascular function between HCT116 and HT29 colorectal tumors. This study is the first to relate low and high molecular weight contrast agents with matched whole-tumor histological sections. These detailed comparisons identified tumor regions that appear distinct from each other using the HPG-GdF biomarkers related to perfusion and vessel leakiness, while Gadovist-imaged parameter measures in the same regions were unable to detect variation in vascular function. We have established HPG-GdF as a biocompatible multi-modal high molecular weight contrast agent with application for examining vascular function in both MR and histological modalities. Copyright © 2015 John Wiley & Sons, Ltd.

  16. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

    A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

  17. Investigations of image fusion

    Science.gov (United States)

    Zhang, Zhong

    1999-12-01

    The objective of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a single image which is more suitable for the purpose of human visual perception or further image processing tasks. In this thesis, a region-based fusion algorithm using the wavelet transform is proposed. The identification of important features in each image, such as edges and regions of interest, are used to guide the fusion process. The idea of multiscale grouping is also introduced and a generic image fusion framework based on multiscale decomposition is studied. The framework includes all of the existing multiscale-decomposition- based fusion approaches we found in the literature which did not assume a statistical model for the source images. Comparisons indicate that our framework includes some new approaches which outperform the existing approaches for the cases we consider. Registration must precede our fusion algorithms. So we proposed a hybrid scheme which uses both feature-based and intensity-based methods. The idea of robust estimation of optical flow from time- varying images is employed with a coarse-to-fine multi- resolution approach and feature-based registration to overcome some of the limitations of the intensity-based schemes. Experiments show that this approach is robust and efficient. Assessing image fusion performance in a real application is a complicated issue. In this dissertation, a mixture probability density function model is used in conjunction with the Expectation- Maximization algorithm to model histograms of edge intensity. Some new techniques are proposed for estimating the quality of a noisy image of a natural scene. Such quality measures can be used to guide the fusion. Finally, we study fusion of images obtained from several copies of a new type of camera developed for video surveillance. Our techniques increase the capability and reliability of the surveillance system and provide an easy way to obtain 3-D

  18. Highlights lecture EANM 2016: ''Embracing molecular imaging and multi-modal imaging: a smart move for nuclear medicine towards personalized medicine''

    Energy Technology Data Exchange (ETDEWEB)

    Aboagye, Eric O. [Imperial College London, Cancer Imaging Centre, Department of Surgery and Cancer, London (United Kingdom); Kraeber-Bodere, Francoise [Hotel Dieu University Hospital, Nuclear Medicine, Nantes (France); CRCINA, Inserm U1232, Nantes (France); ICO Cancer Center, Nuclear Medicine, Saint-Herblain (France)

    2017-08-15

    The 2016 EANM Congress took place in Barcelona, Spain, from 15 to 19 October under the leadership of Prof. Wim Oyen, chair of the EANM Scientific Committee. With more than 6,000 participants, this congress was the most important European event in nuclear medicine, bringing together a multidisciplinary community involved in the different fields of nuclear medicine. There were over 600 oral and 1,200 poster or e-Poster presentations with an overwhelming focus on development and application of imaging for personalized care, which is timely for the community. Beyond FDG PET, major highlights included progress in the use of PSMA and SSTR receptor-targeted radiopharmaceuticals and associated theranostics in oncology. Innovations in radiopharmaceuticals for imaging pathologies of the brain and cardiovascular system, as well as infection and inflammation, were also highlighted. In the areas of physics and instrumentation, multimodality imaging and radiomics were highlighted as promising areas of research. (orig.)

  19. Highlights lecture EANM 2016: "Embracing molecular imaging and multi-modal imaging: a smart move for nuclear medicine towards personalized medicine".

    Science.gov (United States)

    Aboagye, Eric O; Kraeber-Bodéré, Françoise

    2017-08-01

    The 2016 EANM Congress took place in Barcelona, Spain, from 15 to 19 October under the leadership of Prof. Wim Oyen, chair of the EANM Scientific Committee. With more than 6,000 participants, this congress was the most important European event in nuclear medicine, bringing together a multidisciplinary community involved in the different fields of nuclear medicine. There were over 600 oral and 1,200 poster or e-Poster presentations with an overwhelming focus on development and application of imaging for personalized care, which is timely for the community. Beyond FDG PET, major highlights included progress in the use of PSMA and SSTR receptor-targeted radiopharmaceuticals and associated theranostics in oncology. Innovations in radiopharmaceuticals for imaging pathologies of the brain and cardiovascular system, as well as infection and inflammation, were also highlighted. In the areas of physics and instrumentation, multimodality imaging and radiomics were highlighted as promising areas of research.

  20. Abdominal Organ Location, Morphology, and Rib Coverage for the 5(th), 50(th), and 95(th) Percentile Males and Females in the Supine and Seated Posture using Multi-Modality Imaging.

    Science.gov (United States)

    Hayes, Ashley R; Gayzik, F Scott; Moreno, Daniel P; Martin, R Shayn; Stitzel, Joel D

    The purpose of this study was to use data from a multi-modality image set of males and females representing the 5(th), 50(th), and 95(th) percentile (n=6) to examine abdominal organ location, morphology, and rib coverage variations between supine and seated postures. Medical images were acquired from volunteers in three image modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and upright MRI (uMRI). A manual and semi-automated segmentation method was used to acquire data and a registration technique was employed to conduct a comparative analysis between abdominal organs (liver, spleen, and kidneys) in both postures. Location of abdominal organs, defined by center of gravity movement, varied between postures and was found to be significant (p=0.002 to p=0.04) in multiple directions for each organ. In addition, morphology changes, including compression and expansion, were seen in each organ as a result of postural changes. Rib coverage, defined as the projected area of the ribs onto the abdominal organs, was measured in frontal, lateral, and posterior projections, and also varied between postures. A significant change in rib coverage between postures was measured for the spleen and right kidney (p=0.03 and p=0.02). The results indicate that posture affects the location, morphology and rib coverage area of abdominal organs and these implications should be noted in computational modeling efforts focused on a seated posture.

  1. A stereotactic method for the three-dimensional registration of multi-modality biologic images in animals: NMR, PET, histology, and autoradiography

    International Nuclear Information System (INIS)

    Humm, J.L.; Ballon, D.; Hu, Y.C.; Ruan, S.; Chui, C.; Tulipano, P.K.; Erdi, A.; Koutcher, J.; Zakian, K.; Urano, M.; Zanzonico, P.; Mattis, C.; Dyke, J.; Chen, Y.; Harrington, P.; O'Donoghue, J.A.; Ling, C.C.

    2003-01-01

    The objective of this work was to develop and then validate a stereotactic fiduciary marker system for tumor xenografts in rodents which could be used to co-register magnetic resonance imaging (MRI), PET, tissue histology, autoradiography, and measurements from physiologic probes. A Teflon TM fiduciary template has been designed which allows the precise insertion of small hollow Teflon rods (0.71 mm diameter) into a tumor. These rods can be visualized by MRI and PET as well as by histology and autoradiography on tissue sections. The methodology has been applied and tested on a rigid phantom, on tissue phantom material, and finally on tumor bearing mice. Image registration has been performed between the MRI and PET images for the rigid Teflon phantom and among MRI, digitized microscopy images of tissue histology, and autoradiograms for both tissue phantom and tumor-bearing mice. A registration accuracy, expressed as the average Euclidean distance between the centers of three fiduciary markers among the registered image sets, of 0.2±0.06 mm was achieved between MRI and microPET image sets of a rigid Teflon phantom. The fiduciary template allows digitized tissue sections to be co-registered with three-dimensional MRI images with an average accuracy of 0.21 and 0.25 mm for the tissue phantoms and tumor xenografts, respectively. Between histology and autoradiograms, it was 0.19 and 0.21 mm for tissue phantoms and tumor xenografts, respectively. The fiduciary marker system provides a coordinate system with which to correlate information from multiple image types, on a voxel-by-voxel basis, with sub-millimeter accuracy--even among imaging modalities with widely disparate spatial resolution and in the absence of identifiable anatomic landmarks

  2. Multi-modal magnetic resonance imaging in the acute and sub-acute phase of mild traumatic brain injury: can we see the difference?

    Science.gov (United States)

    Toth, Arnold; Kovacs, Noemi; Perlaki, Gabor; Orsi, Gergely; Aradi, Mihaly; Komaromy, Hedvig; Ezer, Erzsebet; Bukovics, Peter; Farkas, Orsolya; Janszky, Jozsef; Doczi, Tamas; Buki, Andras; Schwarcz, Attila

    2013-01-01

    Advanced magnetic resonance imaging (MRI) methods were shown to be able to detect the subtle structural consequences of mild traumatic brain injury (mTBI). The objective of this study was to investigate the acute structural alterations and recovery after mTBI, using diffusion tensor imaging (DTI) to reveal axonal pathology, volumetric analysis, and susceptibility weighted imaging (SWI) to detect microhemorrhage. Fourteen patients with mTBI who had computed tomography with negative results underwent MRI within 3 days and 1 month after injury. High resolution T1-weighted imaging, DTI, and SWI, were performed at both time points. A control group of 14 matched volunteers were also examined following the same imaging protocol and time interval. Tract-Based Spatial Statistics (TBSS) were performed on DTI data to reveal group differences. T1-weighted images were fed into Freesurfer volumetric analysis. TBSS showed fractional anisotropy (FA) to be significantly (corrected ptime points when performing MRI studies on patients with mTBI.

  3. FY1995 development of a endoscopic surgical system utilizing multi-modal functional images; 1995 nendo tashu kino gazo wo mochiiru teishinshu naishikyo shujutsu system no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-05-01

    The purpose of this study is to develop an endoscope system for neurosurgery that can provide not only conventional endoscopic images but also ultraviolet-visible spectra, fluorescence spectra, near infrared spectra, and ultra-soundimages of tissue aiming for real-time identification of pathological tissue. The system also incorporates surgical manipulator and devices such as micro forceps and laser surgical instruments for endoscopic image guided surgery. Surgical Manipulator should be a high performance and easy to operate surgical instrument as well as conventional surgical tools such as scissors and knife. Since living tissue deforms during surgical operation, pre-operative three dimensional information for registration of pathological tissue should be modified based on information obtained during surgery. Thus surgical manipulator should be operated under guidance of surgeon's observation. Consequently, surgical manipulator should have various types of imaging and measurement devices such as an endoscope and an ultrasound imaging probe at its end effectors. Based on this concept, a prototype of a new multi channel surgical manipulator system CM cube (CM3, Computer aided Micro Multichannel Manipulator) that has various types of imaging and measurement devices such as ultra-violet-visible camera for spectroscopic measurement, ultra-sound imaging probe, three dimensional endoscope, together with micro surgical instruments and laser surgical systems has been developed. Its performance was evaluated through in vitro/in vivo experiments and clinical application. (NEDO)

  4. [Image fusion in medical radiology].

    Science.gov (United States)

    Burger, C

    1996-07-20

    Image fusion supports the correlation between images of two or more studies of the same organ. First, the effect of differing geometries during image acquisitions, such as a head tilt, is compensated for. As a consequence, congruent images can easily be obtained. Instead of merely putting them side by side in a static manner and burdening the radiologist with the whole correlation task, image fusion supports him with interactive visualization techniques. This is especially worthwhile for small lesions as they can be more precisely located. Image fusion is feasible today. Easy and robust techniques are readily available, and furthermore DICOM, a rapidly evolving data exchange standard, diminishes the once severe compatibility problems for image data originating from systems of different manufacturers. However, the current solutions for image fusion are not yet established enough for a high throughput of fusion studies. Thus, for the time being image fusion is most appropriately confined to clinical research studies.

  5. Feasibility of CBCT-based target and normal structure delineation in prostate cancer radiotherapy: Multi-observer and image multi-modality study

    International Nuclear Information System (INIS)

    Luetgendorf-Caucig, Carola; Fotina, Irina; Stock, Markus; Poetter, Richard; Goldner, Gregor; Georg, Dietmar

    2011-01-01

    Background and purpose: In-room cone-beam CT (CBCT) imaging and adaptive treatment strategies are promising methods to decrease target volumes and to spare organs at risk. The aim of this work was to analyze the inter-observer contouring uncertainties of target volumes and organs at risks (oars) in localized prostate cancer radiotherapy using CBCT images. Furthermore, CBCT contouring was benchmarked against other image modalities (CT, MR) and the influence of subjective image quality perception on inter-observer variability was assessed. Methods and materials: Eight prostate cancer patients were selected. Seven radiation oncologists contoured target volumes and oars on CT, MRI and CBCT. Volumes, coefficient of variation (COV), conformity index (cigen), and coordinates of center-of-mass (COM) were calculated for each patient and image modality. Reliability analysis was performed for the support of the reported findings. Subjective perception of image quality was assessed via a ten-scored visual analog scale (VAS). Results: The median volume for prostate was larger on CT compared to MRI and CBCT images. The inter-observer variation for prostate was larger on CBCT (CIgen = 0.57 ± 0.09, 0.61 reliability) compared to CT (CIgen = 0.72 ± 0.07, 0.83 reliability) and MRI (CIgen = 0.66 ± 0.12, 0.87 reliability). On all image modalities values of the intra-observer reliability coefficient (0.97 for CT, 0.99 for MR and 0.94 for CBCT) indicated high reproducibility of results. For all patients the root mean square (RMS) of the inter-observer standard deviation (σ) of the COM was largest on CBCT with σ(x) = 0.4 mm, σ(y) = 1.1 mm, and σ(z) = 1.7 mm. The concordance in delineating OARs was much stronger than for target volumes, with average CIgen > 0.70 for rectum and CIgen > 0.80 for bladder. Positive correlations between CIgen and VAS score of the image quality were observed for the prostate, seminal vesicles and rectum. Conclusions: Inter-observer variability for target

  6. A Hybrid Technique for De-Noising Multi-Modality Medical Images by Employing Cuckoo’s Search with Curvelet Transform

    Directory of Open Access Journals (Sweden)

    Qaisar Javaid

    2018-01-01

    Full Text Available De-noising of the medical images is very difficult task. To improve the overall visual representation we need to apply a contrast enhancement techniques, this representation provide the physicians and clinicians a good and recovered diagnosis results. Various de-noising and contrast enhancements methods are develops. However, some of the methods are not good in providing the better results with accuracy and efficiency. In our paper we de-noise and enhance the medical images without any loss of information. We uses the curvelet transform in combination with ridglet transform along with CS (Cuckoo Search algorithm. The curvlet transform adapt and represents the sparse pixel informations with all edges. The edges play very important role in understanding of the images. Curvlet transform computes the edges very efficiently where the wavelets are failed. We used the CS to optimize the de-noising coefficients without loss of structural and morphological information. Our designed method would be accurate and efficient in de-noising the medical images. Our method attempts to remove the multiplicative and additive noises. Our proposed method is proved to be an efficient and reliable in removing all kind of noises from the medical images. Result indicates that our proposed approach is better than other approaches in removing impulse, Gaussian, and speckle noises.

  7. Multispectral analytical image fusion

    International Nuclear Information System (INIS)

    Stubbings, T.C.

    2000-04-01

    With new and advanced analytical imaging methods emerging, the limits of physical analysis capabilities and furthermore of data acquisition quantities are constantly pushed, claiming high demands to the field of scientific data processing and visualisation. Physical analysis methods like Secondary Ion Mass Spectrometry (SIMS) or Auger Electron Spectroscopy (AES) and others are capable of delivering high-resolution multispectral two-dimensional and three-dimensional image data; usually this multispectral data is available in form of n separate image files with each showing one element or other singular aspect of the sample. There is high need for digital image processing methods enabling the analytical scientist, confronted with such amounts of data routinely, to get rapid insight into the composition of the sample examined, to filter the relevant data and to integrate the information of numerous separate multispectral images to get the complete picture. Sophisticated image processing methods like classification and fusion provide possible solution approaches to this challenge. Classification is a treatment by multivariate statistical means in order to extract analytical information. Image fusion on the other hand denotes a process where images obtained from various sensors or at different moments of time are combined together to provide a more complete picture of a scene or object under investigation. Both techniques are important for the task of information extraction and integration and often one technique depends on the other. Therefore overall aim of this thesis is to evaluate the possibilities of both techniques regarding the task of analytical image processing and to find solutions for the integration and condensation of multispectral analytical image data in order to facilitate the interpretation of the enormous amounts of data routinely acquired by modern physical analysis instruments. (author)

  8. Multi modal child-to-child interaction

    DEFF Research Database (Denmark)

    Fisker, Tine Basse

    In this presentation the interaction and relation of three boys is analyzed using multi modal analysis. The analysis clearly, and surprisingly demonstrates that the boys interact via different modes and that they are able to handle several interaction partners at the same time. They co......-construct interaction in rather complex and unexpected ways using verbal as well as non-verbal modes in interaction....

  9. TU-AB-BRA-06: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An MRI Compatible Externally and Internally Deformable Lung Motion Phantom for Multi-Modality IGRT

    Energy Technology Data Exchange (ETDEWEB)

    Sabouri, P; Sawant, A [University of Texas Southwestern Medical Center, Dallas, TX (United States); Arai, T [University of Maryland School of Medicine, Baltimore, MD (United States)

    2016-06-15

    Purpose: MRI has become an attractive tool for tumor motion management. Current MR-compatible phantoms are only capable of reproducing translational motion. This study describes the construction and validation of a more realistic, MRI-compatible lung phantom that is deformable internally as well as externally. We demonstrate a radiotherapy application of this phantom by validating the geometric accuracy of the open-source deformable image registration software NiftyReg (UCL, UK). Methods: The outer shell of a commercially-available dynamic breathing torso phantom was filled with natural latex foam with eleven water tubes. A rigid foam cut-out served as the diaphragm. A high-precision programmable, in-house, MRI-compatible motion platform was used to drive the diaphragm. The phantom was imaged on a 3T scanner (Philips, Ingenia). Twenty seven tumor traces previously recorded from lung cancer patients were programmed into the phantom and 2D+t image sequences were acquired using a sparse-sampling sequence k-t BLAST (accn=3, resolution=0.66×0.66×5mm3; acquisition-time=110ms/slice). The geometric fidelity of the MRI-derived trajectories was validated against those obtained via fluoroscopy using the on board kV imager on a Truebeam linac. NiftyReg was used to perform frame by frame deformable image registration. The location of each marker predicted by using NiftyReg was compared with the values calculated by intensity-based segmentation on each frame. Results: In all cases, MR trajectories were within 1 mm of corresponding fluoroscopy trajectories. RMSE between centroid positions obtained from segmentation with those obtained by NiftyReg varies from 0.1 to 0.21 mm in the SI direction and 0.08 to 0.13 mm in the LR direction showing the high accuracy of deformable registration. Conclusion: We have successfully designed and demonstrated a phantom that can accurately reproduce deformable motion under a variety of imaging modalities including MRI, CT and x-ray fluodoscopy

  10. A phase I feasibility study of multi-modality imaging assessing rapid expansion of marrow fat and decreased bone mineral density in cancer patients.

    Science.gov (United States)

    Hui, Susanta K; Arentsen, Luke; Sueblinvong, Thanasak; Brown, Keenan; Bolan, Pat; Ghebre, Rahel G; Downs, Levi; Shanley, Ryan; Hansen, Karen E; Minenko, Anne G; Takhashi, Yutaka; Yagi, Masashi; Zhang, Yan; Geller, Melissa; Reynolds, Margaret; Lee, Chung K; Blaes, Anne H; Allen, Sharon; Zobel, Bruno Beomonte; Le, Chap; Froelich, Jerry; Rosen, Clifford; Yee, Douglas

    2015-04-01

    Cancer survivors are at an increased risk for fractures, but lack of effective and economical biomarkers limits quantitative assessments of marrow fat (MF), bone mineral density (BMD) and their relation in response to cytotoxic cancer treatment. We report dual energy CT (DECT) imaging, commonly used for cancer diagnosis, treatment and surveillance, as a novel biomarker of MF and BMD. We validated DECT in pre-clinical and phase I clinical trials and verified with water-fat MRI (WF-MRI), quantitative CT (QCT) and dual-energy X-ray absorptiometry (DXA). Basis material composition framework was validated using water and small-chain alcohols simulating different components of bone marrow. Histologic validation was achieved by measuring percent adipocyte in the cadaver vertebrae and compared with DECT and WF-MRI. For a phase I trial, sixteen patients with gynecologic malignancies (treated with oophorectomy, radiotherapy or chemotherapy) underwent DECT, QCT, WF-MRI and DXA before and 12months after treatment. BMD and MF percent and distribution were quantified in the lumbar vertebrae and the right femoral neck. Measured precision (3mg/cm(3)) was sufficient to distinguish test solutions. Adiposity in cadaver bone histology was highly correlated with MF measured using DECT and WF-MRI (r=0.80 and 0.77, respectively). In the clinical trial, DECT showed high overall correlation (r=0.77, 95% CI: 0.69, 0.83) with WF-MRI. MF increased significantly after treatment (p<0.002). Chemotherapy and radiation caused greater increases in MF than oophorectomy (p<0.032). L4 BMD decreased 14% by DECT, 20% by QCT, but only 5% by DXA (p<0.002 for all). At baseline, we observed a statistically significant inverse association between MF and BMD which was dramatically attenuated after treatment. Our study demonstrated that DECT, similar to WF-MRI, can accurately measure marrow adiposity. Both imaging modalities show rapid increase in MF following cancer treatment. Our results suggest that MF and

  11. Spinal fusion-hardware construct: Basic concepts and imaging review

    Science.gov (United States)

    Nouh, Mohamed Ragab

    2012-01-01

    The interpretation of spinal images fixed with metallic hardware forms an increasing bulk of daily practice in a busy imaging department. Radiologists are required to be familiar with the instrumentation and operative options used in spinal fixation and fusion procedures, especially in his or her institute. This is critical in evaluating the position of implants and potential complications associated with the operative approaches and spinal fixation devices used. Thus, the radiologist can play an important role in patient care and outcome. This review outlines the advantages and disadvantages of commonly used imaging methods and reports on the best yield for each modality and how to overcome the problematic issues associated with the presence of metallic hardware during imaging. Baseline radiographs are essential as they are the baseline point for evaluation of future studies should patients develop symptoms suggesting possible complications. They may justify further imaging workup with computed tomography, magnetic resonance and/or nuclear medicine studies as the evaluation of a patient with a spinal implant involves a multi-modality approach. This review describes imaging features of potential complications associated with spinal fusion surgery as well as the instrumentation used. This basic knowledge aims to help radiologists approach everyday practice in clinical imaging. PMID:22761979

  12. Development of positron sensor for multi-modal endoscopy

    Energy Technology Data Exchange (ETDEWEB)

    Shimazoe, Kenji, E-mail: shimazoe@it-club.jp [Department of Bioengineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Takahashi, Hiroyuki [Department of Nuclear Engineering and Management, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Fujita, Kaoru [Japan Atomic Energy Agency, 4-29 Tokaimura, 319-1184 Ibaraki (Japan); Mori, Hiroshi; Momose, Toshimitsu [Department of Bioengineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2011-08-21

    Endoscopy is an important inspection device to detect cancers in the human body, but there exists the case of cancer that is hard to detect with only an optical device. Double inspection with optical and radio images is preferable for high accuracy diagnosis, and real time radio imaging is also promising for real time surgery with an endoscope. We have simulated, designed and fabricated a Si-based positron imaging probe for more accurate cancer detection in multi-modality endoscope systems. The fabricated Si-based detector with 2 mm diameter and 1 mm thickness was tested with gamma and positron sources, and also tested to detect cancers in a tumor bearing mouse. The direct positron imaging could have an advantage over gamma imaging in its high sensitivity and resolution.

  13. MINERVA - a multi-modal radiation treatment planning system

    Energy Technology Data Exchange (ETDEWEB)

    Wemple, C.A. E-mail: cew@enel.gov; Wessol, D.E.; Nigg, D.W.; Cogliati, J.J.; Milvich, M.L.; Frederickson, C.; Perkins, M.; Harkin, G.J

    2004-11-01

    Researchers at the Idaho National Engineering and Environmental Laboratory and Montana State University have undertaken development of MINERVA, a patient-centric, multi-modal, radiation treatment planning system. This system can be used for planning and analyzing several radiotherapy modalities, either singly or combined, using common modality independent image and geometry construction and dose reporting and guiding. It employs an integrated, lightweight plugin architecture to accommodate multi-modal treatment planning using standard interface components. The MINERVA design also facilitates the future integration of improved planning technologies. The code is being developed with the Java Virtual Machine for interoperability. A full computation path has been established for molecular targeted radiotherapy treatment planning, with the associated transport plugin developed by researchers at the Lawrence Livermore National Laboratory. Development of the neutron transport plugin module is proceeding rapidly, with completion expected later this year. Future development efforts will include development of deformable registration methods, improved segmentation methods for patient model definition, and three-dimensional visualization of the patient images, geometry, and dose data. Transport and source plugins will be created for additional treatment modalities, including brachytherapy, external beam proton radiotherapy, and the EGSnrc/BEAMnrc codes for external beam photon and electron radiotherapy.

  14. Fusion Imaging for Procedural Guidance.

    Science.gov (United States)

    Wiley, Brandon M; Eleid, Mackram F; Thaden, Jeremy J

    2018-05-01

    The field of percutaneous structural heart interventions has grown tremendously in recent years. This growth has fueled the development of new imaging protocols and technologies in parallel to help facilitate these minimally-invasive procedures. Fusion imaging is an exciting new technology that combines the strength of 2 imaging modalities and has the potential to improve procedural planning and the safety of many commonly performed transcatheter procedures. In this review we discuss the basic concepts of fusion imaging along with the relative strengths and weaknesses of static vs dynamic fusion imaging modalities. This review will focus primarily on echocardiographic-fluoroscopic fusion imaging and its application in commonly performed transcatheter structural heart procedures. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  15. FWFusion: Fuzzy Whale Fusion model for MRI multimodal image ...

    Indian Academy of Sciences (India)

    Hanmant Venketrao Patil

    2018-03-14

    Mar 14, 2018 ... consider multi-modality medical images other than PET and MRI images. ... cipal component averaging based on DWT for fusing CT-. MRI and MRI ..... sub-band LH of the fused image, the distance measure is given based on the ...... sustainable integrated dynamic ship routing and scheduling optimization.

  16. A Hybrid FPGA/Coarse Parallel Processing Architecture for Multi-modal Visual Feature Descriptors

    DEFF Research Database (Denmark)

    Jensen, Lars Baunegaard With; Kjær-Nielsen, Anders; Alonso, Javier Díaz

    2008-01-01

    This paper describes the hybrid architecture developed for speeding up the processing of so-called multi-modal visual primitives which are sparse image descriptors extracted along contours. In the system, the first stages of visual processing are implemented on FPGAs due to their highly parallel...

  17. Manifold regularized multi-task feature selection for multi-modality classification in Alzheimer's disease.

    Science.gov (United States)

    Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

    2013-01-01

    Accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method.

  18. Multi-Modal Intelligent Traffic Signal Systems GPS

    Data.gov (United States)

    Department of Transportation — Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to...

  19. Multi-Modal Traveler Information System - Gateway Functional Requirements

    Science.gov (United States)

    1997-11-17

    The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

  20. Multi-modal RGB–Depth–Thermal Human Body Segmentation

    DEFF Research Database (Denmark)

    Palmero, Cristina; Clapés, Albert; Bahnsen, Chris

    2016-01-01

    This work addresses the problem of human body segmentation from multi-modal visual cues as a first stage of automatic human behavior analysis. We propose a novel RGB-Depth-Thermal dataset along with a multi-modal seg- mentation baseline. The several modalities are registered us- ing a calibration...... to other state-of-the-art meth- ods, obtaining an overlap above 75% on the novel dataset when compared to the manually annotated ground-truth of human segmentations....

  1. Multi-modal MRI of mild traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Ponnada A. Narayana

    2015-01-01

    Full Text Available Multi-modal magnetic resonance imaging (MRI that included high resolution structural imaging, diffusion tensor imaging (DTI, magnetization transfer ratio (MTR imaging, and magnetic resonance spectroscopic imaging (MRSI were performed in mild traumatic brain injury (mTBI patients with negative computed tomographic scans and in an orthopedic-injured (OI group without concomitant injury to the brain. The OI group served as a comparison group for mTBI. MRI scans were performed both in the acute phase of injury (~24 h and at follow-up (~90 days. DTI data was analyzed using tract based spatial statistics (TBSS. Global and regional atrophies were calculated using tensor-based morphometry (TBM. MTR values were calculated using the standard method. MRSI was analyzed using LC Model. At the initial scan, the mean diffusivity (MD was significantly higher in the mTBI cohort relative to the comparison group in several white matter (WM regions that included internal capsule, external capsule, superior corona radiata, anterior corona radiata, posterior corona radiata, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, forceps major and forceps minor of the corpus callosum, superior longitudinal fasciculus, and corticospinal tract in the right hemisphere. TBSS analysis failed to detect significant differences in any DTI measures between the initial and follow-up scans either in the mTBI or OI group. No significant differences were found in MRSI, MTR or morphometry between the mTBI and OI cohorts either at the initial or follow-up scans with or without family wise error (FWE correction. Our study suggests that a number of WM tracts are affected in mTBI in the acute phase of injury and that these changes disappear by 90 days. This study also suggests that none of the MRI-modalities used in this study, with the exception of DTI, is sensitive in detecting changes in the acute phase of mTBI.

  2. Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

    Science.gov (United States)

    Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

    2016-02-01

    The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

  3. Android Based Behavioral Biometric Authentication via Multi-Modal Fusion

    Science.gov (United States)

    2014-06-12

    mobile devices. In order to validate the method proposed in this work data was collected from a Samsung 2 Galaxy S4, running Cyanogenmod version 10.2. The...profile for each user, Al-Khazzar, et al. used a three dimensional maze where users could make diverse decisions and they identified each user from his...performed on a Samsung Galaxy S4 with the following software configuration: • Custom version of Cyanogenmod 10.2 • GApps for Cyanogenmod (Google’s

  4. Multi-modal aggression detection in trains

    NARCIS (Netherlands)

    Yang, Z.

    2009-01-01

    In many public places multiple sensing devices, such as cameras, are installed to help prevent unwanted situations such as aggression and violence. At the moment, the best solution to reach a safe environment requires human operators to monitor the camera images and take appropriate actions when

  5. Utilizing Multi-Modal Literacies in Middle Grades Science

    Science.gov (United States)

    Saurino, Dan; Ogletree, Tamra; Saurino, Penelope

    2010-01-01

    The nature of literacy is changing. Increased student use of computer-mediated, digital, and visual communication spans our understanding of adolescent multi-modal capabilities that reach beyond the traditional conventions of linear speech and written text in the science curriculum. Advancing technology opens doors to learning that involve…

  6. Reference Resolution in Multi-modal Interaction: Position paper

    NARCIS (Netherlands)

    Fernando, T.; Nijholt, Antinus

    2002-01-01

    In this position paper we present our research on multimodal interaction in and with virtual environments. The aim of this presentation is to emphasize the necessity to spend more research on reference resolution in multimodal contexts. In multi-modal interaction the human conversational partner can

  7. Reference resolution in multi-modal interaction: Preliminary observations

    NARCIS (Netherlands)

    González González, G.R.; Nijholt, Antinus

    2002-01-01

    In this paper we present our research on multimodal interaction in and with virtual environments. The aim of this presentation is to emphasize the necessity to spend more research on reference resolution in multimodal contexts. In multi-modal interaction the human conversational partner can apply

  8. MIDA - Optimizing control room performance through multi-modal design

    International Nuclear Information System (INIS)

    Ronan, A. M.

    2006-01-01

    Multi-modal interfaces can support the integration of humans with information processing systems and computational devices to maximize the unique qualities that comprise a complex system. In a dynamic environment, such as a nuclear power plant control room, multi-modal interfaces, if designed correctly, can provide complementary interaction between the human operator and the system which can improve overall performance while reducing human error. Developing such interfaces can be difficult for a designer without explicit knowledge of Human Factors Engineering principles. The Multi-modal Interface Design Advisor (MIDA) was developed as a support tool for system designers and developers. It provides design recommendations based upon a combination of Human Factors principles, a knowledge base of historical research, and current interface technologies. MIDA's primary objective is to optimize available multi-modal technologies within a human computer interface in order to balance operator workload with efficient operator performance. The purpose of this paper is to demonstrate MIDA and illustrate its value as a design evaluation tool within the nuclear power industry. (authors)

  9. Multi-modal locomotion: from animal to application

    International Nuclear Information System (INIS)

    Lock, R J; Burgess, S C; Vaidyanathan, R

    2014-01-01

    The majority of robotic vehicles that can be found today are bound to operations within a single media (i.e. land, air or water). This is very rarely the case when considering locomotive capabilities in natural systems. Utility for small robots often reflects the exact same problem domain as small animals, hence providing numerous avenues for biological inspiration. This paper begins to investigate the various modes of locomotion adopted by different genus groups in multiple media as an initial attempt to determine the compromise in ability adopted by the animals when achieving multi-modal locomotion. A review of current biologically inspired multi-modal robots is also presented. The primary aim of this research is to lay the foundation for a generation of vehicles capable of multi-modal locomotion, allowing ambulatory abilities in more than one media, surpassing current capabilities. By identifying and understanding when natural systems use specific locomotion mechanisms, when they opt for disparate mechanisms for each mode of locomotion rather than using a synergized singular mechanism, and how this affects their capability in each medium, similar combinations can be used as inspiration for future multi-modal biologically inspired robotic platforms. (topical review)

  10. A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

    Science.gov (United States)

    Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

    2015-12-01

    In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

  11. Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation

    Directory of Open Access Journals (Sweden)

    Timo Korthals

    2018-03-01

    Full Text Available Today, agricultural vehicles are available that can automatically perform tasks such as weed detection and spraying, mowing, and sowing while being steered automatically. However, for such systems to be fully autonomous and self-driven, not only their specific agricultural tasks must be automated. An accurate and robust perception system automatically detecting and avoiding all obstacles must also be realized to ensure safety of humans, animals, and other surroundings. In this paper, we present a multi-modal obstacle and environment detection and recognition approach for process evaluation in agricultural fields. The proposed pipeline detects and maps static and dynamic obstacles globally, while providing process-relevant information along the traversed trajectory. Detection algorithms are introduced for a variety of sensor technologies, including range sensors (lidar and radar and cameras (stereo and thermal. Detection information is mapped globally into semantical occupancy grid maps and fused across all sensors with late fusion, resulting in accurate traversability assessment and semantical mapping of process-relevant categories (e.g., crop, ground, and obstacles. Finally, a decoding step uses a Hidden Markov model to extract relevant process-specific parameters along the trajectory of the vehicle, thus informing a potential control system of unexpected structures in the planned path. The method is evaluated on a public dataset for multi-modal obstacle detection in agricultural fields. Results show that a combination of multiple sensor modalities increases detection performance and that different fusion strategies must be applied between algorithms detecting similar and dissimilar classes.

  12. Combined Sparsifying Transforms for Compressive Image Fusion

    Directory of Open Access Journals (Sweden)

    ZHAO, L.

    2013-11-01

    Full Text Available In this paper, we present a new compressive image fusion method based on combined sparsifying transforms. First, the framework of compressive image fusion is introduced briefly. Then, combined sparsifying transforms are presented to enhance the sparsity of images. Finally, a reconstruction algorithm based on the nonlinear conjugate gradient is presented to get the fused image. The simulations demonstrate that by using the combined sparsifying transforms better results can be achieved in terms of both the subjective visual effect and the objective evaluation indexes than using only a single sparsifying transform for compressive image fusion.

  13. Multi-modal Social Networks: A MRF Learning Approach

    Science.gov (United States)

    2016-06-20

    Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

  14. Multi-modal Behavioural Biometric Authentication for Mobile Devices

    OpenAIRE

    Saevanee , Hataichanok; Clarke , Nathan ,; Furnell , Steven ,

    2012-01-01

    Part 12: Authentication and Delegation; International audience; The potential advantages of behavioural biometrics are that they can be utilised in a transparent (non-intrusive) and continuous authentication system. However, individual biometric techniques are not suited to all users and scenarios. One way to increase the reliability of transparent and continuous authentication systems is create a multi-modal behavioural biometric authentication system. This research investigated three behavi...

  15. Coronary plaque morphology on multi-modality imagining and periprocedural myocardial infarction after percutaneous coronary intervention

    Directory of Open Access Journals (Sweden)

    Akira Sato

    2016-06-01

    Full Text Available Percutaneous coronary intervention (PCI may be complicated by periprocedural myocardial infarction (PMI as manifested by elevated cardiac biomarkers such as creatine kinase (CK-MB or troponin T. The occurrence of PMI has been shown to be associated with worse short- and long-term clinical outcome. However, recent studies suggest that PMI defined by biomarker levels alone is a marker of atherosclerosis burden and procedural complexity but in most cases does not have independent prognostic significance. Diagnostic multi-modality imaging such as intravascular ultrasound, optical coherence tomography, coronary angioscopy, near-infrared spectroscopy, multidetector computed tomography, and magnetic resonance imaging can be used to closely investigate the atherosclerotic lesion in order to detect morphological markers of unstable and vulnerable plaques in the patients undergoing PCI. With the improvement of technical aspects of multimodality coronary imaging, clinical practice and research are increasingly shifting toward defining the clinical implication of plaque morphology and patients outcomes. There were numerous published data regarding the relationship between pre-PCI lesion subsets on multi-modality imaging and post-PCI biomarker levels. In this review, we discuss the relationship between coronary plaque morphology estimated by invasive or noninvasive coronary imaging and the occurrence of PMI. Furthermore, this review underlies that the value of the multimodality coronary imaging approach will become the gold standard for invasive or noninvasive prediction of PMI in clinical practice.

  16. Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease

    Science.gov (United States)

    Jie, Biao; Cheng, Bo

    2014-01-01

    Accurate diagnosis of Alzheimer’s disease (AD), as well as its pro-dromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method. PMID:24505676

  17. A novel APD-based detector module for multi-modality PET/SPECT/CT scanners

    International Nuclear Information System (INIS)

    Saoudi, A.; Lecomte, R.

    1999-01-01

    The lack of anatomical information in SPECT and PET images is one of the major factors limiting the ability to localize and accurately quantify radionuclide uptake in small regions of interest. This problem could be resolved by using multi-modality scanners having the capability to acquire anatomical and functional images simultaneously. The feasibility of a novel detector suitable for measuring high-energy annihilation radiation in PET, medium-energy γ-rays in SPECT and low-energy X-rays in transmission CT is demonstrated and its performance is evaluated for potential use in multi-modality PET/SPECT/CT imaging. The proposed detector consists of a thin CsI(Tl) scintillator sitting on top of a deep GSO/LSO pair read out by an avalanche photodiode. The GSO/LOS pair provides depth-of-interaction information for 511 keV detection in PET, while the thin CsI(Tl) that is essentially transparent to annihilation radiation is used for detecting lower energy X- and γ-rays. The detector performance is compared to that of an LSO/YSO phoswich. Although the implementation of the proposed GSO/LSO/CsI(Tl) detector raises special problems that increase complexity, it generally outperforms the LSO/YSO phoswich for simultaneous PET, SPECT and CT imaging

  18. Image fusion tool: Validation by phantom measurements

    International Nuclear Information System (INIS)

    Zander, A.; Geworski, L.; Richter, M.; Ivancevic, V.; Munz, D.L.; Muehler, M.; Ditt, H.

    2002-01-01

    Aim: Validation of a new image fusion tool with regard to handling, application in a clinical environment and fusion precision under different acquisition and registration settings. Methods: The image fusion tool investigated allows fusion of imaging modalities such as PET, CT, MRI. In order to investigate fusion precision, PET and MRI measurements were performed using a cylinder and a body contour-shaped phantom. The cylinder phantom (diameter and length 20 cm each) contained spheres (10 to 40 mm in diameter) which represented 'cold' or 'hot' lesions in PET measurements. The body contour-shaped phantom was equipped with a heart model containing two 'cold' lesions. Measurements were done with and without four external markers placed on the phantoms. The markers were made of plexiglass (2 cm diameter and 1 cm thickness) and contained a Ga-Ge-68 core for PET and Vitamin E for MRI measurements. Comparison of fusion results with and without markers was done visually and by computer assistance. This algorithm was applied to the different fusion parameters and phantoms. Results: Image fusion of PET and MRI data without external markers yielded a measured error of 0 resulting in a shift at the matrix border of 1.5 mm. Conclusion: The image fusion tool investigated allows a precise fusion of PET and MRI data with a translation error acceptable for clinical use. The error is further minimized by using external markers, especially in the case of missing anatomical orientation. Using PET the registration error depends almost only on the low resolution of the data

  19. Image fusion for enhanced forest structural assessment

    CSIR Research Space (South Africa)

    Roberts, JW

    2011-01-01

    Full Text Available This research explores the potential benefits of fusing active and passive medium resolution satellite-borne sensor data for forest structural assessment. Image fusion was applied as a means of retaining disparate data features relevant to modeling...

  20. Fusion of Images from Dissimilar Sensor Systems

    National Research Council Canada - National Science Library

    Chow, Khin

    2004-01-01

    Different sensors exploit different regions of the electromagnetic spectrum; therefore a multi-sensor image fusion system can take full advantage of the complementary capabilities of individual sensors in the suit...

  1. Quantitative image fusion in infrared radiometry

    Science.gov (United States)

    Romm, Iliya; Cukurel, Beni

    2018-05-01

    Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.

  2. MINERVA: A multi-modality plug-in-based radiation therapy treatment planning system

    International Nuclear Information System (INIS)

    Wemple, C. A.; Wessol, D. E.; Nigg, D. W.; Cogliati, J. J.; Milvich, M.; Fredrickson, C. M.; Perkins, M.; Harkin, G. J.; Hartmann-Siantar, C. L.; Lehmann, J.; Flickinger, T.; Pletcher, D.; Yuan, A.; DeNardo, G. L.

    2005-01-01

    Researchers at the INEEL, MSU, LLNL and UCD have undertaken development of MINERVA, a patient-centric, multi-modal, radiation treatment planning system, which can be used for planning and analysing several radiotherapy modalities, either singly or combined, using common treatment planning tools. It employs an integrated, lightweight plug-in architecture to accommodate multi-modal treatment planning using standard interface components. The design also facilitates the future integration of improved planning technologies. The code is being developed with the Java programming language for inter-operability. The MINERVA design includes the image processing, model definition and data analysis modules with a central module to coordinate communication and data transfer. Dose calculation is performed by source and transport plug-in modules, which communicate either directly through the database or through MINERVA's openly published, extensible markup language (XML)-based application programmer's interface (API). All internal data are managed by a database management system and can be exported to other applications or new installations through the API data formats. A full computation path has been established for molecular-targeted radiotherapy treatment planning, with additional treatment modalities presently under development. (authors)

  3. Contribution to the detection of changes in multi-modal 3D MRI sequences

    International Nuclear Information System (INIS)

    Bosc, Marcel

    2003-01-01

    This research thesis reports the study of automatic techniques for the detection of changes in image sequences of brain magnetic resonance imagery (MRI), and more particularly the study of localised intensity changes occurring during pathological evolutions such as evolutions of lesions into multiple sclerosis. Thus, this work focused on the development of image processing tools allowing to decide whether changes are statistically significant or not. The author developed automatic techniques of identification and correction of the main artefacts (position, deformations, intensity variation, and so on), and proposes an original technique for cortex segmentation which introduced anatomic information for an improved automatic detection. The developed change detection system has been assessed within the frame of the study of the evolution of lesions of multiple sclerosis. Performance have been determined on a large number of multi-modal images, and the automatic system has shown better performance than a human expert [fr

  4. Image fusion techniques in permanent seed implantation

    Directory of Open Access Journals (Sweden)

    Alfredo Polo

    2010-10-01

    Full Text Available Over the last twenty years major software and hardware developments in brachytherapy treatment planning, intraoperative navigation and dose delivery have been made. Image-guided brachytherapy has emerged as the ultimate conformal radiation therapy, allowing precise dose deposition on small volumes under direct image visualization. In thisprocess imaging plays a central role and novel imaging techniques are being developed (PET, MRI-MRS and power Doppler US imaging are among them, creating a new paradigm (dose-guided brachytherapy, where imaging is used to map the exact coordinates of the tumour cells, and to guide applicator insertion to the correct position. Each of these modalities has limitations providing all of the physical and geometric information required for the brachytherapy workflow.Therefore, image fusion can be used as a solution in order to take full advantage of the information from each modality in treatment planning, intraoperative navigation, dose delivery, verification and follow-up of interstitial irradiation.Image fusion, understood as the visualization of any morphological volume (i.e. US, CT, MRI together with an additional second morpholo gical volume (i.e. CT, MRI or functional dataset (functional MRI, SPECT, PET, is a well known method for treatment planning, verification and follow-up of interstitial irradiation. The term image fusion is used when multiple patient image datasets are registered and overlaid or merged to provide additional information. Fused images may be created from multiple images from the same imaging modality taken at different moments (multi-temporalapproach, or by combining information from multiple modalities. Quality means that the fused images should provide additional information to the brachythe rapy process (diagnosis and staging, treatment planning, intraoperative imaging, treatment delivery and follow-up that cannot be obtained in other ways. In this review I will focus on the role of

  5. A digital 3D atlas of the marmoset brain based on multi-modal MRI.

    Science.gov (United States)

    Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

    2018-04-01

    The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

  6. Pellet bed reactor for multi-modal space power

    International Nuclear Information System (INIS)

    Buden, D.; Williams, K.; Mast, P.; Mims, J.

    1987-01-01

    A review of forthcoming space power needs for both civil and military missions indicates that power requirements will be in the tens of megawatts. The electrical power requirements are envisioned to be twofold: long-duration lower power levels will be needed for station keeping, communications, and/or surveillance; short-duration higher power levels will be required for pulsed power devices. These power characteristics led to the proposal of a multi-modal space power reactor using a pellet bed design. Characteristics desired for such a multimegawatt reactor power source are standby, alert, and pulsed power modes; high-thermal output heat source (approximately 1000 MWt peak power); long lifetime station keeping power (10 to 30 years); high temperature output (1500 K to 1800 K); rapid-burst power transition; high reliability (above 95 percent); and stringent safety standards compliance. The proposed pellet bed reactor is designed to satisfy these characteristics

  7. Multi-modal intervention improved oral intake in hospitalized patients

    DEFF Research Database (Denmark)

    Holst, M; Beermann, T; Mortensen, M N

    2015-01-01

    BACKGROUND: Good nutritional practice (GNP) includes screening, nutrition plan and monitoring, and is mandatory for targeted treatment of malnourished patients in hospital. AIMS: To optimize energy- and protein-intake in patients at nutritional risk and to improve GNP in a hospital setting. METHODS......: A 12-months observational multi-modal intervention study was done, using the top-down and bottom-up principle. All hospitalized patients (>3 days) were included. Setting: A university hospital with 758 beds and all specialities. Measurements: Record audit of GNP, energy- and protein-intake by 24-h...... recall, patient interviews and staff questionnaire before and after the intervention. Interventions: Based on pre-measurements, nutrition support teams in each department made targeted action plans, supervised by an expert team. Education, diagnose-specific nutrition plans, improved menus and eating...

  8. Game of Objects: vicarious causation and multi-modal media

    Directory of Open Access Journals (Sweden)

    Aaron Pedinotti

    2013-09-01

    Full Text Available This paper applies philosopher Graham Harman's object-oriented theory of "vicarious causation" to an analysis of the multi-modal media phenomenon known as "Game of Thrones." Examining the manner in which George R.R. Martin's best-selling series of fantasy novels has been adapted into a board game, a video game, and a hit HBO television series, it uses the changes entailed by these processes to trace the contours of vicariously generative relations. In the course of the resulting analysis, it provides new suggestions concerning the eidetic dimensions of Harman's causal model, particularly with regard to causation in linear networks and in differing types of game systems.

  9. MEDCIS: Multi-Modality Epilepsy Data Capture and Integration System.

    Science.gov (United States)

    Zhang, Guo-Qiang; Cui, Licong; Lhatoo, Samden; Schuele, Stephan U; Sahoo, Satya S

    2014-01-01

    Sudden Unexpected Death in Epilepsy (SUDEP) is the leading mode of epilepsy-related death and is most common in patients with intractable, frequent, and continuing seizures. A statistically significant cohort of patients for SUDEP study requires meticulous, prospective follow up of a large population that is at an elevated risk, best represented by the Epilepsy Monitoring Unit (EMU) patient population. Multiple EMUs need to collaborate, share data for building a larger cohort of potential SUDEP patient using a state-of-the-art informatics infrastructure. To address the challenges of data integration and data access from multiple EMUs, we developed the Multi-Modality Epilepsy Data Capture and Integration System (MEDCIS) that combines retrospective clinical free text processing using NLP, prospective structured data capture using an ontology-driven interface, interfaces for cohort search and signal visualization, all in a single integrated environment. A dedicated Epilepsy and Seizure Ontology (EpSO) has been used to streamline the user interfaces, enhance its usability, and enable mappings across distributed databases so that federated queries can be executed. MEDCIS contained 936 patient data sets from the EMUs of University Hospitals Case Medical Center (UH CMC) in Cleveland and Northwestern Memorial Hospital (NMH) in Chicago. Patients from UH CMC and NMH were stored in different databases and then federated through MEDCIS using EpSO and our mapping module. More than 77GB of multi-modal signal data were processed using the Cloudwave pipeline and made available for rendering through the web-interface. About 74% of the 40 open clinical questions of interest were answerable accurately using the EpSO-driven VISual AGregagator and Explorer (VISAGE) interface. Questions not directly answerable were either due to their inherent computational complexity, the unavailability of primary information, or the scope of concept that has been formulated in the existing Ep

  10. Strategic Mobility 21, Inland Port - Multi-Modal Terminal Operating System Design Specification

    National Research Council Canada - National Science Library

    Mallon, Lawrence G; Dougherty, Edmond J

    2007-01-01

    ...) Specification identifies technical and functional requirements for procuring and integrating services required for a multi-modal node operating software system operating within a Service Oriented Architecture (SOA...

  11. Multi-modality imaging of transient osteoporosis of the hip

    NARCIS (Netherlands)

    Gemmel, Filip; Van der Veen, Hugo C.; Van Schelven, Willem D.; Collins, James M. P.; Vanneuville, Isabelle; Rijk, Paul C.

    2012-01-01

    Transient osteoporosis of the hip (TOH), also referred to as bone marrow edema syndrome (BMES) of the femoral head and neck, is an uncommon and therefore underdiagnosed benign skeletal disorder, affecting primarily women, particularly in their last trimester of pregnancy, and middle-aged men. The

  12. Linked statistical shape models for multi-modal segmentation: application to prostate CT-MR segmentation in radiotherapy planning

    Science.gov (United States)

    Chowdhury, Najeeb; Chappelow, Jonathan; Toth, Robert; Kim, Sung; Hahn, Stephen; Vapiwala, Neha; Lin, Haibo; Both, Stefan; Madabhushi, Anant

    2011-03-01

    We present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate delineations of a SOI's boundary on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. We apply the LSSM in the context of multi-modal prostate segmentation for radiotherapy planning, where we segment the prostate on MRI and CT simultaneously. Prostate capsule segmentation is a critical step in prostate radiotherapy planning, where dose plans have to be formulated on CT. Since accurate delineations of the prostate boundary are very difficult to obtain on CT, pre-treatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to do compared to CT. Hence, our framework incorporates multi-modal registration of MRI and CT to map 2D boundary delineations of prostate (obtained from an expert radiation oncologist) on MR training images onto corresponding CT images. The delineations of the prostate capsule on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. We acquired 7 MRI-CT patient studies and used the leave-one-out strategy to train and evaluate our LSSM (fLSSM), built using expert ground truth delineations on MRI and MRI-CT fusion derived capsule delineations on CT. A unique attribute of our fLSSM is that it does not require expert delineations of the capsule on CT. In order to perform prostate MRI segmentation using the fLSSM, we employed a regionbased approach where we deformed the evolving prostate boundary to optimize a mutual information based cost criterion, which took into account region-based intensity statistics of the image being segmented. The final prostate segmentation was then

  13. Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

    Science.gov (United States)

    Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

    2015-08-01

    Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

  14. Three dimensional image alignment, registration and fusion

    International Nuclear Information System (INIS)

    Treves, S.T.; Mitchell, K.D.; Habboush, I.H.

    1998-01-01

    Combined assessment of three dimensional anatomical and functional images (SPECT, PET, MRI, CT) is useful to determine the nature and extent of lesions in many parts of the body. Physicians principally rely on their spatial sense of mentally re-orient and overlap images obtained with different imaging modalities. Objective methods that enable easy and intuitive image registration can help the physician arrive at more optimal diagnoses and better treatment decisions. This review describes a simple, intuitive and robust image registration approach developed in our laboratory. It differs from most other registration techniques in that it allows the user to incorporate all of the available information within the images in the registration process. This method takes full advantage of the ability of knowledgeable operators to achieve image registration and fusion using an intuitive interactive visual approach. It can register images accurately and quickly without the use of elaborate mathematical modeling or optimization techniques. The method provides the operator with tools to manipulate images in three dimensions, including visual feedback techniques to assess the accuracy of registration (grids, overlays, masks, and fusion of images in different colors). Its application is not limited to brain imaging and can be applied to images from any region in the body. The overall effect is a registration algorithm that is easy to implement and can achieve accuracy on the order of one pixel

  15. Alternate method for to realize image fusion

    International Nuclear Information System (INIS)

    Vargas, L.; Hernandez, F.; Fernandez, R.

    2005-01-01

    At the present time the image departments have the necessity of carrying out image fusion obtained of diverse apparatuses. Conventionally its fuse resonance or tomography images by X-rays with functional images as the gammagrams and PET images. The fusion technology is for sale with the modern image equipment and not all the cabinets of nuclear medicine have access to it. By this reason we analyze, study and we find a solution so that all the cabinets of nuclear medicine can benefit of the image fusion. The first indispensable requirement is to have a personal computer with capacity to put up image digitizer cards. It is also possible, if one has a gamma camera that can export images in JPG, GIF, TIFF or BMP formats, to do without of the digitizer card and to record the images in a disk to be able to use them in the personal computer. It is required of one of the following commercially available graph design programs: Corel Draw, Photo Shop, FreeHand, Illustrator or Macromedia Flash that are those that we evaluate and that its allow to make the images fusion. Anyone of them works well and a short training is required to be able to manage them. It is necessary a photographic digital camera with a resolution of at least 3.0 mega pixel. The procedure consists on taking photographic images of the radiological studies that the patient already has, selecting those demonstrative images of the pathology in study and that its can also be concordant with the images that we have created in the gammagraphic studies, whether for planar or tomographic. We transfer the images to the personal computer and we read them with the graph design program. To continuation also reads the gammagraphic images. We use those digital tools to make transparent the images, to clip them, to adjust the sizes and to create the fused images. The process is manual and it is requires of ability and experience to choose the images, the cuts, those sizes and the transparency grade. (Author)

  16. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  17. Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

    Science.gov (United States)

    Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

    2018-03-23

    Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging

  18. Contemporary Multi-Modal Historical Representations and the Teaching of Disciplinary Understandings in History

    Science.gov (United States)

    Donnelly, Debra J.

    2018-01-01

    Traditional privileging of the printed text has been considerably eroded by rapid technological advancement and in Australia, as elsewhere, many History teaching programs feature an array of multi-modal historical representations. Research suggests that engagement with the visual and multi-modal constructs has the potential to enrich the pedagogy…

  19. Live Imaging of Mouse Secondary Palate Fusion

    Czech Academy of Sciences Publication Activity Database

    Kim, S.; Procházka, Jan; Bush, J.O.

    jaro, č. 125 (2017), č. článku e56041. ISSN 1940-087X Institutional support: RVO:68378050 Keywords : Developmental Biology * Issue 125 * live imaging * secondary palate * tissue fusion * cleft * craniofacial Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Developmental biology Impact factor: 1.232, year: 2016

  20. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  1. Biometric image enhancement using decision rule based image fusion techniques

    Science.gov (United States)

    Sagayee, G. Mary Amirtha; Arumugam, S.

    2010-02-01

    Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

  2. Image fusion for dynamic contrast enhanced magnetic resonance imaging

    Directory of Open Access Journals (Sweden)

    Leach Martin O

    2004-10-01

    Full Text Available Abstract Background Multivariate imaging techniques such as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI have been shown to provide valuable information for medical diagnosis. Even though these techniques provide new information, integrating and evaluating the much wider range of information is a challenging task for the human observer. This task may be assisted with the use of image fusion algorithms. Methods In this paper, image fusion based on Kernel Principal Component Analysis (KPCA is proposed for the first time. It is demonstrated that a priori knowledge about the data domain can be easily incorporated into the parametrisation of the KPCA, leading to task-oriented visualisations of the multivariate data. The results of the fusion process are compared with those of the well-known and established standard linear Principal Component Analysis (PCA by means of temporal sequences of 3D MRI volumes from six patients who took part in a breast cancer screening study. Results The PCA and KPCA algorithms are able to integrate information from a sequence of MRI volumes into informative gray value or colour images. By incorporating a priori knowledge, the fusion process can be automated and optimised in order to visualise suspicious lesions with high contrast to normal tissue. Conclusion Our machine learning based image fusion approach maps the full signal space of a temporal DCE-MRI sequence to a single meaningful visualisation with good tissue/lesion contrast and thus supports the radiologist during manual image evaluation.

  3. Multi-Modal Inference in Animacy Perception for Artificial Object

    Directory of Open Access Journals (Sweden)

    Kohske Takahashi

    2011-10-01

    Full Text Available Sometimes we feel animacy for artificial objects and their motion. Animals usually interact with environments through multiple sensory modalities. Here we investigated how the sensory responsiveness of artificial objects to the environment would contribute to animacy judgment for them. In a 90-s trial, observers freely viewed four objects moving in a virtual 3D space. The objects, whose position and motion were determined following Perlin-noise series, kept drifting independently in the space. Visual flashes, auditory bursts, or synchronous flashes and bursts appeared with 1–2 s intervals. The first object abruptly accelerated their motion just after visual flashes, giving an impression of responding to the flash. The second object responded to bursts. The third object responded to synchronous flashes and bursts. The forth object accelerated at a random timing independent of flashes and bursts. The observers rated how strongly they felt animacy for each object. The results showed that the object responding to the auditory bursts was rated as having weaker animacy compared to the other objects. This implies that sensory modality through which an object interacts with the environment may be a factor for animacy perception in the object and may serve as the basis of multi-modal and cross-modal inference of animacy.

  4. Embedded security system for multi-modal surveillance in a railway carriage

    Science.gov (United States)

    Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

    2015-10-01

    Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

  5. Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation.

    Science.gov (United States)

    Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

    2013-01-01

    Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6-8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods.

  6. Color image guided depth image super resolution using fusion filter

    Science.gov (United States)

    He, Jin; Liang, Bin; He, Ying; Yang, Jun

    2018-04-01

    Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.

  7. Development of technology for medical image fusion

    International Nuclear Information System (INIS)

    Yamaguchi, Takashi; Amano, Daizou

    2012-01-01

    With entry into a field of medical diagnosis in mind, we have developed positron emission tomography (PET) ''MIP-100'' system, of which spatial resolution is far higher than the conventional one, using semiconductor detectors for preclinical imaging for small animals. In response to the recently increasing market demand to fuse functional images by PET and anatomical ones by CT or MRI, we have been developing software to implement image fusion function that enhances marketability of the PET Camera. This paper describes the method of fusing with high accuracy the PET images and anatomical ones by CT system. It also explains that a computer simulation proved the image overlay accuracy to be ±0.3 mm as a result of the development, and that effectiveness of the developed software is confirmed in case of experiment to obtain measured data. Achieving such high accuracy as ±0.3 mm by the software allows us to present fusion images with high resolution (<0.6 mm) without degrading the spatial resolution (<0.5 mm) of the PET system using semiconductor detectors. (author)

  8. Fusion in computer vision understanding complex visual content

    CERN Document Server

    Ionescu, Bogdan; Piatrik, Tomas

    2014-01-01

    This book presents a thorough overview of fusion in computer vision, from an interdisciplinary and multi-application viewpoint, describing successful approaches, evaluated in the context of international benchmarks that model realistic use cases. Features: examines late fusion approaches for concept recognition in images and videos; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, fo

  9. Assessment of fusion operators for medical imaging: application to MR images fusion

    International Nuclear Information System (INIS)

    Barra, V.; Boire, J.Y.

    2000-01-01

    We propose in the article to assess the results provided by several fusion operators in the case of T 1 - and T 2 -weighted magnetic resonance images fusion of the brain. This assessment deals with an expert visual inspection of the results and with a numerical analysis of some comparison measures found in the literature. The aim of this assessment is to find the 'best' operator according to the clinical study. This method is here applied to the quantification of brain tissue volumes on a brain phantom, and allows to select a fusion operator in any clinical study where several information is available. (authors)

  10. A novel technique to incorporate structural prior information into multi-modal tomographic reconstruction

    International Nuclear Information System (INIS)

    Kazantsev, Daniil; Dobson, Katherine J; Withers, Philip J; Lee, Peter D; Ourselin, Sébastien; Arridge, Simon R; Hutton, Brian F; Kaestner, Anders P; Lionheart, William R B

    2014-01-01

    There has been a rapid expansion of multi-modal imaging techniques in tomography. In biomedical imaging, patients are now regularly imaged using both single photon emission computed tomography (SPECT) and x-ray computed tomography (CT), or using both positron emission tomography and magnetic resonance imaging (MRI). In non-destructive testing of materials both neutron CT (NCT) and x-ray CT are widely applied to investigate the inner structure of material or track the dynamics of physical processes. The potential benefits from combining modalities has led to increased interest in iterative reconstruction algorithms that can utilize the data from more than one imaging mode simultaneously. We present a new regularization term in iterative reconstruction that enables information from one imaging modality to be used as a structural prior to improve resolution of the second modality. The regularization term is based on a modified anisotropic tensor diffusion filter, that has shape-adapted smoothing properties. By considering the underlying orientations of normal and tangential vector fields for two co-registered images, the diffusion flux is rotated and scaled adaptively to image features. The images can have different greyscale values and different spatial resolutions. The proposed approach is particularly good at isolating oriented features in images which are important for medical and materials science applications. By enhancing the edges it enables both easy identification and volume fraction measurements aiding segmentation algorithms used for quantification. The approach is tested on a standard denoising and deblurring image recovery problem, and then applied to 2D and 3D reconstruction problems; thereby highlighting the capabilities of the algorithm. Using synthetic data from SPECT co-registered with MRI, and real NCT data co-registered with x-ray CT, we show how the method can be used across a range of imaging modalities. (paper)

  11. A dynamically weighted multi-modal biometric security system

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-09-01

    Full Text Available The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than...

  12. Multi-modal Virtual Scenario Enhances Neurofeedback Learning

    Directory of Open Access Journals (Sweden)

    Avihay Cohen

    2016-08-01

    Full Text Available In the past decade neurofeedback has become the focus of a growing body of research. With real-time fMRI enabling on-line monitoring of emotion related areas such as the amygdala, many have begun testing its therapeutic benefits. However most existing neurofeedback procedures still use monotonic uni-modal interfaces, thus possibly limiting user engagement and weakening learning efficiency. The current study tested a novel multi-sensory neurofeedback animated scenario aimed at enhancing user experience and improving learning. We examined whether relative to a simple uni-modal 2D interface, learning via an interface of complex multi-modal 3D scenario will result in improved neurofeedback learning. As a neural-probe, we used the recently developed fMRI-inspired EEG model of amygdala activity (amygdala-EEG finger print; amygdala-EFP, enabling low-cost and mobile limbic neurofeedback training. Amygdala-EFP was reflected in the animated scenario by the unrest level of a hospital waiting-room in which virtual characters become impatient, approach the admission-desk and complain loudly. Successful down-regulation was reflected as an ease in the room unrest-level. We tested whether relative to a standard uni-modal 2D graphic thermometer interface, this animated scenario could facilitate more effective learning and improve the training experience. Thirty participants underwent two separated neurofeedback sessions (one-week apart practicing down-regulation of the amygdala-EFP signal. In the first session, half trained via the animated scenario and half via a thermometer interface. Learning efficiency was tested by three parameters: (a effect-size of the change in amygdala-EFP following training, (b sustainability of the learned down-regulation in the absence of online feedback, and (c transferability to an unfamiliar context. Comparing amygdala-EFP signal amplitude between the last and the first neurofeedback trials revealed that the animated scenario

  13. Multi-Modal Intelligent Traffic Signal Systems Signal Plans for Roadside Equipment

    Data.gov (United States)

    Department of Transportation — Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to...

  14. Multi-Modal Intelligent Traffic Signal Systems (MMITSS) Basic Safety Message

    Data.gov (United States)

    Department of Transportation — Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to...

  15. Multi-Modal Intelligent Traffic Signal Systems Vehicle Trajectories for Roadside Equipment

    Data.gov (United States)

    Department of Transportation — Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to...

  16. Multi-modal trip planning system : Northeastern Illinois Regional Transportation Authority.

    Science.gov (United States)

    2013-01-01

    This report evaluates the Multi-Modal Trip Planner System (MMTPS) implemented by the Northeastern Illinois Regional Transportation Authority (RTA) against the specific functional objectives enumerated by the Federal Transit Administration (FTA) in it...

  17. Multi-Modal Traveler Information System - GCM Corridor Architecture Interface Control Requirements

    Science.gov (United States)

    1997-10-31

    The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

  18. Multi-Modal Traveler Information System - GCM Corridor Architecture Functional Requirements

    Science.gov (United States)

    1997-11-17

    The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

  19. Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

    Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

  20. Histopathology in 3D: From three-dimensional reconstruction to multi-stain and multi-modal analysis

    Directory of Open Access Journals (Sweden)

    Derek Magee

    2015-01-01

    Full Text Available Light microscopy applied to the domain of histopathology has traditionally been a two-dimensional imaging modality. Several authors, including the authors of this work, have extended the use of digital microscopy to three dimensions by stacking digital images of serial sections using image-based registration. In this paper, we give an overview of our approach, and of extensions to the approach to register multi-modal data sets such as sets of interleaved histopathology sections with different stains, and sets of histopathology images to radiology volumes with very different appearance. Our approach involves transforming dissimilar images into a multi-channel representation derived from co-occurrence statistics between roughly aligned images.

  1. Color Multifocus Image Fusion Using Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    S. Savić

    2013-11-01

    Full Text Available In this paper, a recently proposed grayscale multifocus image fusion method based on the first level of Empirical Mode Decomposition (EMD has been extended to color images. In addition, this paper deals with low contrast multifocus image fusion. The major advantages of the proposed methods are simplicity, absence of artifacts and control of contrast, while this isn’t the case with other pyramidal multifocus fusion methods. The efficiency of the proposed method is tested subjectively and with a vector gradient based objective measure, that is proposed in this paper for multifocus color image fusion. Subjective analysis performed on a multifocus image dataset has shown its superiority to the existing EMD and DWT based methods. The objective measures of grayscale and color image fusion show significantly better scores for this method than for the classic complex EMD fusion method.

  2. Anato-metabolic fusion of PET, CT and MRI images

    International Nuclear Information System (INIS)

    Przetak, C.; Baum, R.P.; Niesen, A.; Slomka, P.; Proeschild, A.; Leonhardi, J.

    2000-01-01

    The fusion of cross-sectional images - especially in oncology - appears to be a very helpful tool to improve the diagnostic and therapeutic accuracy. Though many advantages exist, image fusion is applied routinely only in a few hospitals. To introduce image fusion as a common procedure, technical and logistical conditions have to be fulfilled which are related to long term archiving of digital data, data transfer and improvement of the available software in terms of usefulness and documentation. The accuracy of coregistration and the quality of image fusion has to be validated by further controlled studies. (orig.) [de

  3. An FPGA-based heterogeneous image fusion system design method

    Science.gov (United States)

    Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong

    2011-08-01

    Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.

  4. Joint Multi-Focus Fusion and Bayer ImageRestoration

    Institute of Scientific and Technical Information of China (English)

    Ling Guo; Bin Yang; Chao Yang

    2015-01-01

    In this paper, a joint multifocus image fusion and Bayer pattern image restoration algorithm for raw images of single-sensor colorimaging devices is proposed. Different from traditional fusion schemes, the raw Bayer pattern images are fused before colorrestoration. Therefore, the Bayer image restoration operation is only performed one time. Thus, the proposed algorithm is moreefficient than traditional fusion schemes. In detail, a clarity measurement of Bayer pattern image is defined for raw Bayer patternimages, and the fusion operator is performed on superpixels which provide powerful grouping cues of local image feature. Theraw images are merged with refined weight map to get the fused Bayer pattern image, which is restored by the demosaicingalgorithm to get the full resolution color image. Experimental results demonstrate that the proposed algorithm can obtain betterfused results with more natural appearance and fewer artifacts than the traditional algorithms.

  5. INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    H. Shen

    2012-08-01

    Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.

  6. Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

    Science.gov (United States)

    Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

    2013-12-01

    The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

  7. Holographic Raman tweezers controlled by multi-modal natural user interface

    International Nuclear Information System (INIS)

    Tomori, Zoltán; Keša, Peter; Nikorovič, Matej; Valušová, Eva; Antalík, Marián; Kaňka, Jan; Jákl, Petr; Šerý, Mojmír; Bernatová, Silvie; Zemánek, Pavel

    2016-01-01

    Holographic optical tweezers provide a contactless way to trap and manipulate several microobjects independently in space using focused laser beams. Although the methods of fast and efficient generation of optical traps are well developed, their user friendly control still lags behind. Even though several attempts have appeared recently to exploit touch tablets, 2D cameras, or Kinect game consoles, they have not yet reached the level of natural human interface. Here we demonstrate a multi-modal ‘natural user interface’ approach that combines finger and gaze tracking with gesture and speech recognition. This allows us to select objects with an operator’s gaze and voice, to trap the objects and control their positions via tracking of finger movement in space and to run semi-automatic procedures such as acquisition of Raman spectra from preselected objects. This approach takes advantage of the power of human processing of images together with smooth control of human fingertips and downscales these skills to control remotely the motion of microobjects at microscale in a natural way for the human operator. (paper)

  8. Image fusion via nonlocal sparse K-SVD dictionary learning.

    Science.gov (United States)

    Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

    2016-03-01

    Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

  9. A framework of region-based dynamic image fusion

    Institute of Scientific and Technical Information of China (English)

    WANG Zhong-hua; QIN Zheng; LIU Yu

    2007-01-01

    A new framework of region-based dynamic image fusion is proposed. First, the technique of target detection is applied to dynamic images (image sequences) to segment images into different targets and background regions. Then different fusion rules are employed in different regions so that the target information is preserved as much as possible. In addition, steerable non-separable wavelet frame transform is used in the process of multi-resolution analysis, so the system achieves favorable characters of orientation and invariant shift. Compared with other image fusion methods, experimental results showed that the proposed method has better capabilities of target recognition and preserves clear background information.

  10. Multi-sensor image fusion and its applications

    CERN Document Server

    Blum, Rick S

    2005-01-01

    Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies.After a review of state-of-the-art image fusion techniques,

  11. Geophysical data fusion for subsurface imaging

    International Nuclear Information System (INIS)

    Hoekstra, P.; Vandergraft, J.; Blohm, M.; Porter, D.

    1993-08-01

    A geophysical data fusion methodology is under development to combine data from complementary geophysical sensors and incorporate geophysical understanding to obtain three dimensional images of the subsurface. The research reported here is the first phase of a three phase project. The project focuses on the characterization of thin clay lenses (aquitards) in a highly stratified sand and clay coastal geology to depths of up to 300 feet. The sensor suite used in this work includes time-domain electromagnetic induction (TDEM) and near surface seismic techniques. During this first phase of the project, enhancements to the acquisition and processing of TDEM data were studied, by use of simulated data, to assess improvements for the detection of thin clay layers. Secondly, studies were made of the use of compressional wave and shear wave seismic reflection data by using state-of-the-art high frequency vibrator technology. Finally, a newly developed processing technique, called ''data fusion,'' was implemented to process the geophysical data, and to incorporate a mathematical model of the subsurface strata. Examples are given of the results when applied to real seismic data collected at Hanford, WA, and for simulated data based on the geology of the Savannah River Site

  12. Fast single image dehazing based on image fusion

    Science.gov (United States)

    Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

    2015-01-01

    Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

  13. Making Faces - State-Space Models Applied to Multi-Modal Signal Processing

    DEFF Research Database (Denmark)

    Lehn-Schiøler, Tue

    2005-01-01

    The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....

  14. Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

    KAUST Repository

    Elsheikh, Ahmed H.

    2013-05-01

    A novel multi-modal parameter estimation algorithm is introduced. Parameter estimation is an ill-posed inverse problem that might admit many different solutions. This is attributed to the limited amount of measured data used to constrain the inverse problem. The proposed multi-modal model calibration algorithm uses an iterative stochastic ensemble method (ISEM) for parameter estimation. ISEM employs an ensemble of directional derivatives within a Gauss-Newton iteration for nonlinear parameter estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging of close clusters approaching the same local minima. Numerical testing demonstrates the potential of the proposed algorithm in dealing with multi-modal nonlinear parameter estimation for subsurface flow models. © 2013 Elsevier B.V.

  15. Remote sensing image fusion in the context of Digital Earth

    International Nuclear Information System (INIS)

    Pohl, C

    2014-01-01

    The increase in the number of operational Earth observation satellites gives remote sensing image fusion a new boost. As a powerful tool to integrate images from different sensors it enables multi-scale, multi-temporal and multi-source information extraction. Image fusion aims at providing results that cannot be obtained from a single data source alone. Instead it enables feature and information mining of higher reliability and availability. The process required to prepare remote sensing images for image fusion comprises most of the necessary steps to feed the database of Digital Earth. The virtual representation of the planet uses data and information that is referenced and corrected to suit interpretation and decision-making. The same pre-requisite is valid for image fusion, the outcome of which can directly flow into a geographical information system. The assessment and description of the quality of the results remains critical. Depending on the application and information to be extracted from multi-source images different approaches are necessary. This paper describes the process of image fusion based on a fusion and classification experiment, explains the necessary quality measures involved and shows with this example which criteria have to be considered if the results of image fusion are going to be used in Digital Earth

  16. Development of EndoTOFPET-US, a multi-modal endoscope for ultrasound and time of flight positron emission tomography

    International Nuclear Information System (INIS)

    Pizzichemi, M

    2014-01-01

    The EndoTOFPET-US project aims at delevoping a multi-modal imaging device that combines Ultrasound with Time-Of-Flight Positron Emission Tomography into an endoscopic imaging device. The goal is to obtain a coincidence time resolution of about 200 ps FWHM and sub-millimetric spatial resolution for the PET head, integrating the components in a very compact detector suitable for endoscopic use. The scanner will be exploited for the clinical test of new bio-markers especially targeted for prostate and pancreatic cancer as well as for diagnostic and surgical oncology. This paper focuses on the status of the Time-Of-Flight Positron Emission Tomograph under development for the EndoTOFPET-US project

  17. Improving efficiency of multi-modality registration of brain scans based on mutual information

    International Nuclear Information System (INIS)

    Thurfjell, L.; Lau, Y.; Hutton, B.; Westmead Hospital, Sydney, NSW; University of Technology, Sydney, NSW

    1999-01-01

    Full text: One approach for multi-modality registration uses a similarity measure based on mutual information (MI) of voxel intensities. MI measures the statistical dependence between two images by comparing the joint probability distribution (approximated by the 2D joint histogram), with the distribution in the case of complete independence (approximated from the I D histograms). The MI measure reaches a maximum when the images are aligned. The purpose of the current work was to investigate if the registration process could be accelerated through subsampling, i.e. by using only a subset of all voxels for the calculations. The behaviour of the MI measure at different subsampling factors was studied. It was observed that subsampling caused MI to exhibit multiple local maxima unless it was accompanied by a reduction in the number of bins used for the histograms. However, too few bins in the histograms made the peak of the MI measure broader. It was therefore concluded that a coarse-to-fine subsampling procedure, followed by a corresponding increase in the number of bins in the histogram, would be the best choice. The method was validated on SPET-MRI data from seven healthy volunteers. Using a 64:1, 32:1 and 16:1 subsampling scheme with a corresponding bin size of 24, 32 and 48, the new method converged in an average time of 2.5 min as compared to 46 min for the original method (PC Pentium 200). The average absolute differences were 0.24, 0.34, 0.30 mm translation and 0.58, 0.41, 0.66 degrees rotation. We conclude that the suggested scheme renders the registration method sufficiently rapid for routine use in the clinical setting

  18. Advances in fusion of PET, SPET, CT und MRT images

    International Nuclear Information System (INIS)

    Pietrzyk, U.

    2003-01-01

    Image fusion as part of the correlative analysis for medical images has gained ever more interest and the fact that combined systems for PET and CT are commercially available demonstrates the importance for medical diagnostics, therapy and research oriented applications. In this work the basics of image registration, its different strategies and the mathematical and physical background are described. A successful image registration is an essential prerequisite for the next steps, namely correlative medical image analysis. Means to verify image registration and the different modes for integrated display are presented and its usefulness is discussed. Possible limitations in applying image fusion in order to avoid misinterpretation will be pointed out. (orig.) [de

  19. Multi-modal Video Surveillance Aided by Pyroelectric Infrared Sensors

    OpenAIRE

    Magno , Michele; Tombari , Federico; Brunelli , Davide; Di Stefano , Luigi; Benini , Luca

    2008-01-01

    International audience; The interest in low-cost and small size video surveillance systems able to collaborate in a network has been increasing over the last years. Thanks to the progress in low-power design, research has greatly reduced the size and the power consumption of such distributed embedded systems providing flexibility, quick deployment and allowing the implementation of effective vision algorithms performing image processing directly on the embedded node. In this paper we present ...

  20. Fusion of multispectral and panchromatic images using multirate filter banks

    Institute of Scientific and Technical Information of China (English)

    Wang Hong; Jing Zhongliang; Li Jianxun

    2005-01-01

    In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.

  1. Graduate Student Perceptions of Multi-Modal Tablet Use in Academic Environments

    Science.gov (United States)

    Bryant, Ezzard C., Jr.

    2016-01-01

    The purpose of this study was to explore graduate student perceptions of use and the ease of use of multi-modal tablets to access electronic course materials, and the perceived differences based on students' gender, age, college of enrollment, and previous experience. This study used the Unified Theory of Acceptance and Use of Technology to…

  2. Multi-criteria appraisal of multi-modal urban public transport systems

    NARCIS (Netherlands)

    Keyvan Ekbatani, M.; Cats, O.

    2015-01-01

    This study proposes a multi-criteria decision making (MCDM) modelling framework for the appraisal of multi-modal urban public transportation services. MCDM is commonly used to obtain choice alternatives that satisfy a range of performance indicators. The framework embraces both compensatory and

  3. (In)Flexibility of Constituency in Japanese in Multi-Modal Categorial Grammar with Structured Phonology

    Science.gov (United States)

    Kubota, Yusuke

    2010-01-01

    This dissertation proposes a theory of categorial grammar called Multi-Modal Categorial Grammar with Structured Phonology. The central feature that distinguishes this theory from the majority of contemporary syntactic theories is that it decouples (without completely segregating) two aspects of syntax--hierarchical organization (reflecting…

  4. Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma.

    Science.gov (United States)

    Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

    2015-02-28

    To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P<0.001) and objective tumor response (P=0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P=0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P<0.001). Multivariate analysis identified tumor stage (P<0.001) and tumor type (P=0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P<0.001), surgical treatment (P=0.009), and multi-modal treatment (P=0.002) were identified as independent post-treatment prognostic factors. TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC.

  5. Neutron imaging for inertial confinement fusion and molecular optic imaging

    International Nuclear Information System (INIS)

    Delage, O.

    2010-01-01

    Scientific domains that require imaging of micrometric/nano-metric objects are dramatically increasing (Plasma Physics, Astrophysics, Biotechnology, Earth Sciences...). Difficulties encountered in imaging smaller and smaller objects make this research area more and more challenging and in constant evolution. The two scientific domains, through which this study has been led, are the neutron imaging in the context of the inertial confinement fusion and the fluorescence molecular imaging. Work presented in this thesis has two main objectives. The first one is to describe the instrumentation characteristics that require such imagery and, relatively to the scientific domains considered, identify parameters likely to optimize the imaging system accuracy. The second one is to present the developed data analysis and reconstruction methods able to provide spatial resolution adapted to the size of the observed object. Similarities of numerical algorithms used in these two scientific domains, which goals are quiet different, show how micrometric/nano-metric object imaging is a research area at the border of a large number of scientific disciplines. (author)

  6. Fusion of colour and monochromatic images with edge emphasis

    Directory of Open Access Journals (Sweden)

    Rade M. Pavlović

    2014-02-01

    Full Text Available We propose a novel method to fuse true colour images with monochromatic non-visible range images that seeks to encode important structural information from monochromatic images efficiently but also preserve the natural appearance of the available true chromacity information. We utilise the β colour opponency channel of the lαβ colour as the domain to fuse information from the monochromatic input into the colour input by the way of robust grayscale fusion. This is followed by an effective gradient structure visualisation step that enhances the visibility of monochromatic information in the final colour fused image. Images fused using this method preserve their natural appearance and chromacity better than conventional methods while at the same time clearly encode structural information from the monochormatic input. This is demonstrated on a number of well-known true colour fusion examples and confirmed by the results of subjective trials on the data from several colour fusion scenarios. Introduction The goal of image fusion can be broadly defined as: the representation of visual information contained in a number of input images into a single fused image without distortion or loss of information. In practice, however, a representation of all available information from multiple inputs in a single image is almost impossible and fusion is generally a data reduction task.  One of the sensors usually provides a true colour image that by definition has all of its data dimensions already populated by the spatial and chromatic information. Fusing such images with information from monochromatic inputs in a conventional manner can severely affect natural appearance of the fused image. This is a difficult problem and partly the reason why colour fusion received only a fraction of the attention than better behaved grayscale fusion even long after colour sensors became widespread. Fusion method Humans tend to see colours as contrasts between opponent

  7. A new hyperspectral image compression paradigm based on fusion

    Science.gov (United States)

    Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

    2016-10-01

    The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

  8. The optimal algorithm for Multi-source RS image fusion.

    Science.gov (United States)

    Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

    2016-01-01

    In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

  9. Multifocus Image Fusion in Q-Shift DTCWT Domain Using Various Fusion Rules

    Directory of Open Access Journals (Sweden)

    Yingzhong Tian

    2016-01-01

    Full Text Available Multifocus image fusion is a process that integrates partially focused image sequence into a fused image which is focused everywhere, with multiple methods proposed in the past decades. The Dual Tree Complex Wavelet Transform (DTCWT is one of the most precise ones eliminating two main defects caused by the Discrete Wavelet Transform (DWT. Q-shift DTCWT was proposed afterwards to simplify the construction of filters in DTCWT, producing better fusion effects. A different image fusion strategy based on Q-shift DTCWT is presented in this work. According to the strategy, firstly, each image is decomposed into low and high frequency coefficients, which are, respectively, fused by using different rules, and then various fusion rules are innovatively combined in Q-shift DTCWT, such as the Neighborhood Variant Maximum Selectivity (NVMS and the Sum Modified Laplacian (SML. Finally, the fused coefficients could be well extracted from the source images and reconstructed to produce one fully focused image. This strategy is verified visually and quantitatively with several existing fusion methods based on a plenty of experiments and yields good results both on standard images and on microscopic images. Hence, we can draw the conclusion that the rule of NVMS is better than others after Q-shift DTCWT.

  10. Research on fusion algorithm of polarization image in tetrolet domain

    Science.gov (United States)

    Zhang, Dexiang; Yuan, BaoHong; Zhang, Jingjing

    2015-12-01

    Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. A fusion method for polarization images based on tetrolet transform is proposed. Firstly, the magnitude of polarization image and angle of polarization image can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions using tetrolet transform. For the low-frequency coefficients, the average fusion method is used. According to edge distribution differences in high frequency sub-band images, for the directional high-frequency coefficients are used to select the better coefficients by region spectrum entropy algorithm for fusion. At last the fused image can be obtained by utilizing inverse transform for fused tetrolet coefficients. Experimental results show that the proposed method can detect image features more effectively and the fused image has better subjective visual effect

  11. Medium resolution image fusion, does it enhance forest structure assessment

    CSIR Research Space (South Africa)

    Roberts, JW

    2008-07-01

    Full Text Available This research explored the potential benefits of fusing optical and Synthetic Aperture Radar (SAR) medium resolution satellite-borne sensor data for forest structural assessment. Image fusion was applied as a means of retaining disparate data...

  12. Radar image and data fusion for natural hazards characterisation

    Science.gov (United States)

    Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

    2010-01-01

    Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

  13. NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

    Science.gov (United States)

    Chirayath, Ved

    2018-01-01

    We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with

  14. Neutron penumbral imaging of laser-fusion targets

    International Nuclear Information System (INIS)

    Lerche, R.A.; Ress, D.B.

    1988-01-01

    Using a new technique, penumbral coded-aperture imaging, the first neutron images of laser-driven, inertial-confinement fusion targets were obtained. With these images the deuterium-tritium burn region within a compressed target can be measured directly. 4 references, 11 figures

  15. Image enhancement using thermal-visible fusion for human detection

    Science.gov (United States)

    Zaihidee, Ezrinda Mohd; Hawari Ghazali, Kamarul; Zuki Saleh, Mohd

    2017-09-01

    An increased interest in detecting human beings in video surveillance system has emerged in recent years. Multisensory image fusion deserves more research attention due to the capability to improve the visual interpretability of an image. This study proposed fusion techniques for human detection based on multiscale transform using grayscale visual light and infrared images. The samples for this study were taken from online dataset. Both images captured by the two sensors were decomposed into high and low frequency coefficients using Stationary Wavelet Transform (SWT). Hence, the appropriate fusion rule was used to merge the coefficients and finally, the final fused image was obtained by using inverse SWT. From the qualitative and quantitative results, the proposed method is more superior than the two other methods in terms of enhancement of the target region and preservation of details information of the image.

  16. Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

    Science.gov (United States)

    Awumah, Anna; Mahanti, Prasun; Robinson, Mark

    2016-10-01

    Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

  17. Fusion of Geophysical Images in the Study of Archaeological Sites

    Science.gov (United States)

    Karamitrou, A. A.; Petrou, M.; Tsokas, G. N.

    2011-12-01

    This paper presents results from different fusion techniques between geophysical images from different modalities in order to combine them into one image with higher information content than the two original images independently. The resultant image will be useful for the detection and mapping of buried archaeological relics. The examined archaeological area is situated in Kampana site (NE Greece) near the ancient theater of Maronia city. Archaeological excavations revealed an ancient theater, an aristocratic house and the temple of the ancient Greek God Dionysus. Numerous ceramic objects found in the broader area indicated the probability of the existence of buried urban structure. In order to accurately locate and map the latter, geophysical measurements performed with the use of the magnetic method (vertical gradient of the magnetic field) and of the electrical method (apparent resistivity). We performed a semi-stochastic pixel based registration method between the geophysical images in order to fine register them by correcting their local spatial offsets produced by the use of hand held devices. After this procedure we applied to the registered images three different fusion approaches. Image fusion is a relatively new technique that not only allows integration of different information sources, but also takes advantage of the spatial and spectral resolution as well as the orientation characteristics of each image. We have used three different fusion techniques, fusion with mean values, with wavelets by enhancing selected frequency bands and curvelets giving emphasis at specific bands and angles (according the expecting orientation of the relics). In all three cases the fused images gave significantly better results than each of the original geophysical images separately. The comparison of the results of the three different approaches showed that the fusion with the use of curvelets, giving emphasis at the features' orientation, seems to give the best fused image

  18. APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Jabari

    2017-08-01

    Full Text Available Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan camera along with either a colour camera or a four-band multi-spectral (MS camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC. We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  19. Application of Sensor Fusion to Improve Uav Image Classification

    Science.gov (United States)

    Jabari, S.; Fathollahi, F.; Zhang, Y.

    2017-08-01

    Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  20. Design and experimental study of a multi-modal piezoelectric energy harvester

    Energy Technology Data Exchange (ETDEWEB)

    Xiong, Xing Yu [School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing (China); Oyadiji, S. Olutunde [School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester (United States)

    2017-01-15

    A multi-modal piezoelectric vibration energy harvester is designed in this article. It consists of a cantilevered base beam and some upper and lower layer beams with rigid masses bonded between the beams as spacers. For a four-layer harvester subjected to random base excitations, relocating the mass positions leads to the generation of up to four close resonance frequencies over the frequency range from 10 Hz to 100 Hz with relative large power output. The harvesters are connected with a resistance decade box and the frequency response functions of the voltage and power on resistive loads are determined. The experimental results are validated with the simulation results using the finite element method. On a certain level of power output, the experimental results show that the multi-modal harvesters can generate a frequency band that is more than two times greater than the frequency band produced by a cantilevered beam harvester.

  1. Distributed MIMO-ISAR Sub-image Fusion Method

    Directory of Open Access Journals (Sweden)

    Gu Wenkun

    2017-02-01

    Full Text Available The fast fluctuation associated with maneuvering a target’s radar cross-section often affects the imaging performance stability of traditional monostatic Inverse Synthetic Aperture Radar (ISAR. To address this problem, in this study, we propose an imaging method based on the fusion of sub-images of frequencydiversity-distributed multiple Input-Multiple Output-Inverse Synthetic Aperture Radar (MIMO-ISAR. First, we establish the analytic expression of a two-dimensional ISAR sub-image acquired by different channels of distributed MIMO-ISAR. Then, we derive the distance and azimuth distortion factors of the image acquired by the different channels. By compensating for the distortion of the ISAR image, we ultimately realize distributed MIMO-ISAR fusion imaging. Simulations verify the validity of this imaging method using distributed MIMO-ISAR.

  2. FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Zhao

    2017-09-01

    Full Text Available The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.

  3. Low Complexity Track Initialization and Fusion for Multi-Modal Sensor Networks

    Science.gov (United States)

    2012-11-08

    that is, freely available to any visitor to IEEE Xplore . Authors who choose open access must do so by electing this option by notifying the Editor-In...Publications 1. Q. Le and L.M. Kaplan, “Target localization using proximity binary sensors,” Proceedings of IEEE Aerospace conference, Big Sky, MT... IEEE Aerospace Conference, Big Sky, MT, Mar. 2011. 5. Q. Le, and L. M. Kaplan, “Effects of Operation Parameters on Multitarget Tracking in Proximity

  4. Hand hygiene and healthcare system change within multi-modal promotion: a narrative review.

    Science.gov (United States)

    Allegranzi, B; Sax, H; Pittet, D

    2013-02-01

    Many factors may influence the level of compliance with hand hygiene recommendations by healthcare workers. Lack of products and facilities as well as their inappropriate and non-ergonomic location represent important barriers. Targeted actions aimed at making hand hygiene practices feasible during healthcare delivery by ensuring that the necessary infrastructure is in place, defined as 'system change', are essential to improve hand hygiene in healthcare. In particular, access to alcohol-based hand rubs (AHRs) enables appropriate and timely hand hygiene performance at the point of care. The feasibility and impact of system change within multi-modal strategies have been demonstrated both at institutional level and on a large scale. The introduction of AHRs overcomes some important barriers to best hand hygiene practices and is associated with higher compliance, especially when integrated within multi-modal strategies. Several studies demonstrated the association between AHR consumption and reduction in healthcare-associated infection, in particular, meticillin-resistant Staphylococcus aureus bacteraemia. Recent reports demonstrate the feasibility and success of system change implementation on a large scale. The World Health Organization and other investigators have reported the challenges and encouraging results of implementing hand hygiene improvement strategies, including AHR introduction, in settings with limited resources. This review summarizes the available evidence demonstrating the need for system change and its importance within multi-modal hand hygiene improvement strategies. This topic is also discussed in a global perspective and highlights some controversial issues. Copyright © 2013 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  5. Imaging fusion (SPECT/CT) in degenerative disease of spine

    International Nuclear Information System (INIS)

    Bernal, P.; Ucros, G.; Bermudez, S.; Ocampo, M.

    2007-01-01

    Full text: Objective: To determine the utility of Fusion Imaging SPECT/CT in degenerative pathology of the spine and to establish the impact of the use of fusion imaging in spinal pain due to degenerative changes of the spine. Materials and methods: 44 Patients (M=21, F=23) average age of 63 years and with degenerative pathology of spine were sent to Diagnosis Imaging department in FSFB. Bone scintigraphy (SPECT), CT of spine (cervical: 30%, Lumbar 70%) and fusion imaging were performed in all of them. Bone scintigraphy was carried out in a gamma camera Siemens Diacam double head attached to ESOFT computer. The images were acquired in matrix 128 x 128, 20 seg/imag, 64 images. CT of spine was performed same day or two days after in Helycoidal Siemens somatom emotion CT. The fusion was done in a Dicom workstation in sagital, axial and coronal reconstruction. The findings were evaluated by 2 Nuclear Medicine physicians and 2 radiologists of the staff of FSFB in an independent way. Results: Bone scan (SPECT) and CT of 44 patients were evaluated. CT showed facet joint osteoarthrities in 27 (61.3%) patients, uncovertebral joint arthrosis in 7 (15.9%), bulging disc in 9(20.4%), spinal nucleus lesion in 7(15.9%), osteophytes in 9 (20.4%), spinal foraminal stenosis in 7 (15.9%), spondylolysis/spondylolisthesis in 4 (9%). Bone scan showed facet joint osteoarthrities in 29 (65.9%), uncovertebral joint arthrosis in 4 (9%), osteophytes in 9 (20.4%) and normal 3 (6.8%). The imaging fusion showed coincidence findings (main lesion in CT with high uptake in scintigraphy) in 34 patients (77.2%) and no coincidence in 10 (22.8%). In 15 (34.09%) patients the fusion provided additional information. The analysis of the findings of CT and SPECT showed similar results in most of the cases and the fusion didn't provide additional information but it allowed to confirm the findings but when the findings didn't match where the CT showed several findings and SPECT only one area with high uptake

  6. X-ray imaging in the laser-fusion program

    International Nuclear Information System (INIS)

    McCall, G.H.

    1977-01-01

    Imaging devices which are used or planned for x-ray imaging in the laser-fusion program are discussed. Resolution criteria are explained, and a suggestion is made for using the modulation transfer function as a uniform definition of resolution for these devices

  7. Three-dimensional imaging of lumbar spinal fusions

    International Nuclear Information System (INIS)

    Chafetz, N.; Hunter, J.C.; Cann, C.E.; Morris, J.M.; Ax, L.; Catterling, K.F.

    1986-01-01

    Using a Cemax 1000 three-dimensional (3D) imaging computer/workstation, the author evaluated 15 patients with lumbar spinal fusions (four with pseudarthrosis). Both axial images with sagittal and coronal reformations and 3D images were obtained. The diagnoses (spinal stenosis and psuedarthrosis) were changed in four patients, confirmed in six patients, and unchanged in five patients with the addition of the 3D images. The ''cut-away'' 3D images proved particularly helpful for evaluation of central and lateral spinal stenosis, whereas the ''external'' 3D images were most useful for evaluation of the integrity of the fusion. Additionally, orthopedic surgeons found 3D images superior for both surgical planning and explaining pathology to patients

  8. Visible and NIR image fusion using weight-map-guided Laplacian ...

    Indian Academy of Sciences (India)

    Ashish V Vanmali

    fusion perspective, instead of the conventional haze imaging model. The proposed ... Image dehazing; Laplacian–Gaussian pyramid; multi-resolution fusion; visible–NIR image fusion; weight map. 1. .... Tan's [8] work is based on two assumptions: first, images ... responding colour image, since NIR can penetrate through.

  9. External marker-based fusion of functional and morphological images

    International Nuclear Information System (INIS)

    Kremp, S.; Schaefer, A.; Alexander, C.; Kirsch, C.M.

    1999-01-01

    The fusion of image data resulting from methods oriented toward morphology like CT, MRI with functional information coming from nuclear medicine (SPECT, PET) is frequently applied to allow for a better association between functional findings and anatomical structures. A new software was developed to provide image fusion using PET, SPECT, MRI and CT data within a short processing periode for brain as well as whole body examinations in particular thorax and abdomen. The software utilizes external markers (brain) or anatomical landmarks (thorax) for correlation. The fusion requires a periode of approx. 15 min. The examples shown emphasize the high gain in diagnostic information by fusing image data of anatomical and functional methods. (orig.) [de

  10. Alternate method for to realize image fusion; Metodo alterno para realizar fusion de imagenes

    Energy Technology Data Exchange (ETDEWEB)

    Vargas, L; Hernandez, F; Fernandez, R [Departamento de Medicina Nuclear, Imagenologia Diagnostica. Centro Medico de Xalapa, Veracruz (Mexico)

    2005-07-01

    At the present time the image departments have the necessity of carrying out image fusion obtained of diverse apparatuses. Conventionally its fuse resonance or tomography images by X-rays with functional images as the gammagrams and PET images. The fusion technology is for sale with the modern image equipment and not all the cabinets of nuclear medicine have access to it. By this reason we analyze, study and we find a solution so that all the cabinets of nuclear medicine can benefit of the image fusion. The first indispensable requirement is to have a personal computer with capacity to put up image digitizer cards. It is also possible, if one has a gamma camera that can export images in JPG, GIF, TIFF or BMP formats, to do without of the digitizer card and to record the images in a disk to be able to use them in the personal computer. It is required of one of the following commercially available graph design programs: Corel Draw, Photo Shop, FreeHand, Illustrator or Macromedia Flash that are those that we evaluate and that its allow to make the images fusion. Anyone of them works well and a short training is required to be able to manage them. It is necessary a photographic digital camera with a resolution of at least 3.0 mega pixel. The procedure consists on taking photographic images of the radiological studies that the patient already has, selecting those demonstrative images of the pathology in study and that its can also be concordant with the images that we have created in the gammagraphic studies, whether for planar or tomographic. We transfer the images to the personal computer and we read them with the graph design program. To continuation also reads the gammagraphic images. We use those digital tools to make transparent the images, to clip them, to adjust the sizes and to create the fused images. The process is manual and it is requires of ability and experience to choose the images, the cuts, those sizes and the transparency grade. (Author)

  11. Image fusion and denoising using fractional-order gradient information

    DEFF Research Database (Denmark)

    Mei, Jin-Jin; Dong, Yiqiu; Huang, Ting-Zhu

    Image fusion and denoising are significant in image processing because of the availability of multi-sensor and the presence of the noise. The first-order and second-order gradient information have been effectively applied to deal with fusing the noiseless source images. In this paper, due to the adv...... show that the proposed method outperforms the conventional total variation in methods for simultaneously fusing and denoising....

  12. Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images.

    Science.gov (United States)

    Kwan, Chiman; Zhu, Xiaolin; Gao, Feng; Chou, Bryan; Perez, Daniel; Li, Jiang; Shen, Yuzhong; Koperski, Krzysztof; Marchisio, Giovanni

    2018-03-31

    Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.

  13. Fusion of imaging and nonimaging data for surveillance aircraft

    Science.gov (United States)

    Shahbazian, Elisa; Gagnon, Langis; Duquet, Jean Remi; Macieszczak, Maciej; Valin, Pierre

    1997-06-01

    This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight synthetic aperture radar (SSAR), a forward looking infra-red (FLIR) sensor and a link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (1) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (2) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (3) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as multi-sensor data fusion (MSDF), situation and threat assessment (STA) and resource management (RM).

  14. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  15. Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

    Science.gov (United States)

    Liu, Min; Wang, Xueping; Zhang, Hongzhong

    2018-03-01

    In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. New false color mapping for image fusion

    NARCIS (Netherlands)

    Toet, A.; Walraven, J.

    1996-01-01

    A pixel based colour mapping algorithm is presented that produces a fused false colour rendering of two gray level images representing different sensor modalities. The result-ing fused false colour images have a higher information content than each of the original images and retain sensor-specific

  17. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  18. Sustainable Multi-Modal Sensing by a Single Sensor Utilizing the Passivity of an Elastic Actuator

    Directory of Open Access Journals (Sweden)

    Takashi Takuma

    2014-05-01

    Full Text Available When a robot equipped with compliant joints driven by elastic actuators contacts an object and its joints are deformed, multi-modal information, including the magnitude and direction of the applied force and the deformation of the joint, is used to enhance the performance of the robot such as dexterous manipulation. In conventional approaches, some types of sensors used to obtain the multi-modal information are attached to the point of contact where the force is applied and at the joint. However, this approach is not sustainable for daily use in robots, i.e., not durable or robust, because the sensors can undergo damage due to the application of excessive force and wear due to repeated contacts. Further, multiple types of sensors are required to measure such physical values, which add to the complexity of the device system of the robot. In our approach, a single type of sensor is used and it is located at a point distant from the contact point and the joint, and the information is obtained indirectly by the measurement of certain physical parameters that are influenced by the applied force and the joint deformation. In this study, we employ the McKibben pneumatic actuator whose inner pressure changes passively when a force is applied to the actuator. We derive the relationships between information and the pressures of a two-degrees-of-freedom (2-DoF joint mechanism driven by four pneumatic actuators. Experimental results show that the multi-modal information can be obtained by using the set of pressures measured before and after the force is applied. Further, we apply our principle to obtain the stiffness values of certain contacting objects that can subsequently be categorized by using the aforementioned relationships.

  19. Percolated microstructures for multi-modal transport enhancement in porous active materials

    Energy Technology Data Exchange (ETDEWEB)

    McKay, Ian Salmon; Yang, Sungwoo; Wang, Evelyn N.; Kim, Hyunho

    2018-03-13

    A method of forming a composite material for use in multi-modal transport includes providing three-dimensional graphene having hollow channels, enabling a polymer to wick into the hollow channels of the three-dimensional graphene, curing the polymer to form a cured three-dimensional graphene, adding an active material to the cured three-dimensional graphene to form a composite material, and removing the polymer from within the hollow channels. A composite material formed according to the method is also provided.

  20. Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

    Science.gov (United States)

    Hearn, Tristan A.

    2015-01-01

    This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

  1. A Single Rod Multi-modality Multi-interface Level Sensor Using an AC Current Source

    Directory of Open Access Journals (Sweden)

    Abdulgader Hwili

    2008-05-01

    Full Text Available Crude oil separation is an important process in the oil industry. To make efficient use of the separators, it is important to know their internal behaviour, and to measure the levels of multi-interfaces between different materials, such as gas-foam, foam-oil, oil-emulsion, emulsion-water and water-solids. A single-rod multi-modality multi-interface level sensor is presented, which has a current source, and electromagnetic modalities. Some key issues have been addressed, including the effect of salt content and temperature i.e. conductivity on the measurement.

  2. Image fusion using sparse overcomplete feature dictionaries

    Science.gov (United States)

    Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

    2015-10-06

    Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

  3. Real-time image fusion involving diagnostic ultrasound

    DEFF Research Database (Denmark)

    Ewertsen, Caroline; Săftoiu, Adrian; Gruionu, Lucian G

    2013-01-01

    The aim of our article is to give an overview of the current and future possibilities of real-time image fusion involving ultrasound. We present a review of the existing English-language peer-reviewed literature assessing this technique, which covers technical solutions (for ultrasound...

  4. Performance comparison of different graylevel image fusion schemes through a universal image quality index

    NARCIS (Netherlands)

    Toet, A.; Hogervorst, M.A.

    2003-01-01

    We applied a recently introduced universal image quality index Q that quantifies the distortion of a processed image relative to its original version, to assess the performance of different graylevel image fusion schemes. The method is as follows. First, we adopt an original test image as the

  5. Multimodality imaging of reporter gene expression using a novel fusion vector in living cells and animals

    Science.gov (United States)

    Gambhir, Sanjiv [Portola Valley, CA; Pritha, Ray [Mountain View, CA

    2011-06-07

    Novel double and triple fusion reporter gene constructs harboring distinct imagable reporter genes are provided, as well as applications for the use of such double and triple fusion constructs in living cells and in living animals using distinct imaging technologies.

  6. Perceptual evaluation of different image fusion schemes

    NARCIS (Netherlands)

    Toet, A.; IJspeert, J.K.

    2001-01-01

    Human perceptual performance was tested with images of nighttime outdoor scenes. The scenes were registered both with a dual band (visual and near infrared) image intensified low-light CCD camera (DII) and with a thermal middle wavelength band (3-5 μm) infrared (IR) camera. Fused imagery was

  7. Perceptual evaluation of different image fusion schemes

    NARCIS (Netherlands)

    Toet, A.; Franken, E.M.

    2003-01-01

    Human scene recognition performance was tested with images of night-time outdoor scenes. The scenes were registered both with a dual band (visual and near infrared) image intensified low-light CCD camera (DII) and with a thermal middle wavelength band (3–5 mm) infrared (IR) camera. Fused imagery was

  8. Coherence imaging spectro-polarimetry for magnetic fusion diagnostics

    International Nuclear Information System (INIS)

    Howard, J

    2010-01-01

    This paper presents an overview of developments in imaging spectro-polarimetry for magnetic fusion diagnostics. Using various multiplexing strategies, it is possible to construct optical polarization interferometers that deliver images of underlying physical parameters such as flow speed, temperature (Doppler effect) or magnetic pitch angle (motional Stark and Zeeman effects). This paper also describes and presents first results for a new spatial heterodyne interferometric system used for both Doppler and polarization spectroscopy.

  9. Image Fusion Technologies In Commercial Remote Sensing Packages

    OpenAIRE

    Al-Wassai, Firouz Abdullah; Kalyankar, N. V.

    2013-01-01

    Several remote sensing software packages are used to the explicit purpose of analyzing and visualizing remotely sensed data, with the developing of remote sensing sensor technologies from last ten years. Accord-ing to literature, the remote sensing is still the lack of software tools for effective information extraction from remote sensing data. So, this paper provides a state-of-art of multi-sensor image fusion technologies as well as review on the quality evaluation of the single image or f...

  10. 3D Image Fusion to Localise Intercostal Arteries During TEVAR

    Directory of Open Access Journals (Sweden)

    G. Koutouzi

    Full Text Available Purpose: Preservation of intercostal arteries during thoracic aortic procedures reduces the risk of post-operative paraparesis. The origins of the intercostal arteries are visible on pre-operative computed tomography angiography (CTA, but rarely on intra-operative angiography. The purpose of this report is to suggest an image fusion technique for intra-operative localisation of the intercostal arteries during thoracic endovascular repair (TEVAR. Technique: The ostia of the intercostal arteries are identified and manually marked with rings on the pre-operative CTA. The optimal distal landing site in the descending aorta is determined and marked, allowing enough length for an adequate seal and attachment without covering more intercostal arteries than necessary. After 3D/3D fusion of the pre-operative CTA with an intra-operative cone-beam CT (CBCT, the markings are overlaid on the live fluoroscopy screen for guidance. The accuracy of the overlay is confirmed with digital subtraction angiography (DSA and the overlay is adjusted when needed. Stent graft deployment is guided by the markings. The initial experience of this technique in seven patients is presented. Results: 3D image fusion was feasible in all cases. Follow-up CTA after 1 month revealed that all intercostal arteries planned for preservation, were patent. None of the patients developed signs of spinal cord ischaemia. Conclusion: 3D image fusion can be used to localise the intercostal arteries during TEVAR. This may preserve some intercostal arteries and reduce the risk of post-operative spinal cord ischaemia. Keywords: TEVAR, Intercostal artery, Spinal cord ischaemia, 3D image fusion, Image guidance, Cone-beam CT

  11. Online multi-modal robust non-negative dictionary learning for visual tracking.

    Science.gov (United States)

    Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

    2015-01-01

    Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

  12. A multi-modal approach to assessing recovery in youth athletes following concussion.

    Science.gov (United States)

    Reed, Nick; Murphy, James; Dick, Talia; Mah, Katie; Paniccia, Melissa; Verweel, Lee; Dobney, Danielle; Keightley, Michelle

    2014-09-25

    Concussion is one of the most commonly reported injuries amongst children and youth involved in sport participation. Following a concussion, youth can experience a range of short and long term neurobehavioral symptoms (somatic, cognitive and emotional/behavioral) that can have a significant impact on one's participation in daily activities and pursuits of interest (e.g., school, sports, work, family/social life, etc.). Despite this, there remains a paucity in clinically driven research aimed specifically at exploring concussion within the youth sport population, and more specifically, multi-modal approaches to measuring recovery. This article provides an overview of a novel and multi-modal approach to measuring recovery amongst youth athletes following concussion. The presented approach involves the use of both pre-injury/baseline testing and post-injury/follow-up testing to assess performance across a wide variety of domains (post-concussion symptoms, cognition, balance, strength, agility/motor skills and resting state heart rate variability). The goal of this research is to gain a more objective and accurate understanding of recovery following concussion in youth athletes (ages 10-18 years). Findings from this research can help to inform the development and use of improved approaches to concussion management and rehabilitation specific to the youth sport community.

  13. The Review of Visual Analysis Methods of Multi-modal Spatio-temporal Big Data

    Directory of Open Access Journals (Sweden)

    ZHU Qing

    2017-10-01

    Full Text Available The visual analysis of spatio-temporal big data is not only the state-of-art research direction of both big data analysis and data visualization, but also the core module of pan-spatial information system. This paper reviews existing visual analysis methods at three levels:descriptive visual analysis, explanatory visual analysis and exploratory visual analysis, focusing on spatio-temporal big data's characteristics of multi-source, multi-granularity, multi-modal and complex association.The technical difficulties and development tendencies of multi-modal feature selection, innovative human-computer interaction analysis and exploratory visual reasoning in the visual analysis of spatio-temporal big data were discussed. Research shows that the study of descriptive visual analysis for data visualizationis is relatively mature.The explanatory visual analysis has become the focus of the big data analysis, which is mainly based on interactive data mining in a visual environment to diagnose implicit reason of problem. And the exploratory visual analysis method needs a major break-through.

  14. Quantitative multi-modal MRI of the Hippocampus and cognitive ability in community-dwelling older subjects.

    Science.gov (United States)

    Aribisala, Benjamin S; Royle, Natalie A; Maniega, Susana Muñoz; Valdés Hernández, Maria C; Murray, Catherine; Penke, Lars; Gow, Alan; Starr, John M; Bastin, Mark E; Deary, Ian J; Wardlaw, Joanna M

    2014-04-01

    Hippocampal structural integrity is commonly quantified using volumetric measurements derived from brain magnetic resonance imaging (MRI). Previously reported associations with cognitive decline have not been consistent. We investigate hippocampal integrity using quantitative MRI techniques and its association with cognitive abilities in older age. Participants from the Lothian Birth Cohort 1936 underwent brain MRI at mean age 73 years. Longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) were measured in the hippocampus. General factors of fluid-type intelligence (g), cognitive processing speed (speed) and memory were obtained at age 73 years, as well as childhood IQ test results at age 11 years. Amongst 565 older adults, multivariate linear regression showed that, after correcting for ICV, gender and age 11 IQ, larger left hippocampal volume was significantly associated with better memory ability (β = .11, p = .003), but not with speed or g. Using quantitative MRI and after correcting for multiple testing, higher T1 and MD were significantly associated with lower scores of g (β range = -.11 to -.14, p multi-modal MRI assessments were more sensitive at detecting cognition-hippocampal integrity associations than volumetric measurements, resulting in stronger associations between MRI biomarkers and age-related cognition changes. Copyright © 2014. Published by Elsevier Ltd.

  15. Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques.

    Science.gov (United States)

    Franchi, G; Angulo, J; Moreaud, M; Sorbier, L

    2018-01-01

    The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have discriminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

  16. A Geometric Dictionary Learning Based Approach for Fluorescence Spectroscopy Image Fusion

    OpenAIRE

    Zhiqin Zhu; Guanqiu Qi; Yi Chai; Penghua Li

    2017-01-01

    In recent years, sparse representation approaches have been integrated into multi-focus image fusion methods. The fused images of sparse-representation-based image fusion methods show great performance. Constructing an informative dictionary is a key step for sparsity-based image fusion method. In order to ensure sufficient number of useful bases for sparse representation in the process of informative dictionary construction, image patches from all source images are classified into different ...

  17. Multimodality Image Fusion and Planning and Dose Delivery for Radiation Therapy

    International Nuclear Information System (INIS)

    Saw, Cheng B.; Chen Hungcheng; Beatty, Ron E.; Wagner, Henry

    2008-01-01

    Image-guided radiation therapy (IGRT) relies on the quality of fused images to yield accurate and reproducible patient setup prior to dose delivery. The registration of 2 image datasets can be characterized as hardware-based or software-based image fusion. Hardware-based image fusion is performed by hybrid scanners that combine 2 distinct medical imaging modalities such as positron emission tomography (PET) and computed tomography (CT) into a single device. In hybrid scanners, the patient maintains the same position during both studies making the fusion of image data sets simple. However, it cannot perform temporal image registration where image datasets are acquired at different times. On the other hand, software-based image fusion technique can merge image datasets taken at different times or with different medical imaging modalities. Software-based image fusion can be performed either manually, using landmarks, or automatically. In the automatic image fusion method, the best fit is evaluated using mutual information coefficient. Manual image fusion is typically performed at dose planning and for patient setup prior to dose delivery for IGRT. The fusion of orthogonal live radiographic images taken prior to dose delivery to digitally reconstructed radiographs will be presented. Although manual image fusion has been routinely used, the use of fiducial markers has shortened the fusion time. Automated image fusion should be possible for IGRT because the image datasets are derived basically from the same imaging modality, resulting in further shortening the fusion time. The advantages and limitations of both hardware-based and software-based image fusion methodologies are discussed

  18. Color image fusion for concealed weapon detection

    NARCIS (Netherlands)

    Toet, A.

    2003-01-01

    Recent advances in passive and active imaging sensor technology offer the potential to detect weapons that are concealed underneath a person's clothing or carried along in bags. Although the concealed weapons can sometimes easily be detected, it can be difficult to perceive their context, due to the

  19. Spectral edge: gradient-preserving spectral mapping for image fusion.

    Science.gov (United States)

    Connah, David; Drew, Mark S; Finlayson, Graham D

    2015-12-01

    This paper describes a novel approach to image fusion for color display. Our goal is to generate an output image whose gradient matches that of the input as closely as possible. We achieve this using a constrained contrast mapping paradigm in the gradient domain, where the structure tensor of a high-dimensional gradient representation is mapped exactly to that of a low-dimensional gradient field which is then reintegrated to form an output. Constraints on output colors are provided by an initial RGB rendering. Initially, we motivate our solution with a simple "ansatz" (educated guess) for projecting higher-D contrast onto color gradients, which we expand to a more rigorous theorem to incorporate color constraints. The solution to these constrained optimizations is closed-form, allowing for simple and hence fast and efficient algorithms. The approach can map any N-D image data to any M-D output and can be used in a variety of applications using the same basic algorithm. In this paper, we focus on the problem of mapping N-D inputs to 3D color outputs. We present results in five applications: hyperspectral remote sensing, fusion of color and near-infrared or clear-filter images, multilighting imaging, dark flash, and color visualization of magnetic resonance imaging diffusion-tensor imaging.

  20. Self-assessed performance improves statistical fusion of image labels

    International Nuclear Information System (INIS)

    Bryan, Frederick W.; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M.; Reich, Daniel S.; Landman, Bennett A.

    2014-01-01

    Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone to inter-individual differences. While fully automated methods have successfully targeted many anatomies, automated methods have not yet been developed for numerous essential structures (e.g., the internal structure of the spinal cord as seen on magnetic resonance imaging). Collaborative labeling is a new paradigm that offers a robust alternative that may realize both the throughput of automation and the guidance of experts. Yet, distributing manual labeling expertise across individuals and sites introduces potential human factors concerns (e.g., training, software usability) and statistical considerations (e.g., fusion of information, assessment of confidence, bias) that must be further explored. During the labeling process, it is simple to ask raters to self-assess the confidence of their labels, but this is rarely done and has not been previously quantitatively studied. Herein, the authors explore the utility of self-assessment in relation to automated assessment of rater performance in the context of statistical fusion. Methods: The authors conducted a study of 66 volumes manually labeled by 75 minimally trained human raters recruited from the university undergraduate population. Raters were given 15 min of training during which they were shown examples of correct segmentation, and the online segmentation tool was demonstrated. The volumes were labeled 2D slice-wise, and the slices were unordered. A self-assessed quality metric was produced by raters for each slice by marking a confidence bar superimposed on the slice. Volumes produced by both voting and statistical fusion algorithms were compared against a set of expert segmentations of the same volumes. Results: Labels for 8825 distinct slices were obtained. Simple majority voting resulted in statistically poorer performance than voting weighted by self-assessed performance

  1. Self-assessed performance improves statistical fusion of image labels

    Energy Technology Data Exchange (ETDEWEB)

    Bryan, Frederick W., E-mail: frederick.w.bryan@vanderbilt.edu; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Reich, Daniel S. [Translational Neuroradiology Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892 (United States); Landman, Bennett A. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); and Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee 37235 (United States)

    2014-03-15

    Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone to inter-individual differences. While fully automated methods have successfully targeted many anatomies, automated methods have not yet been developed for numerous essential structures (e.g., the internal structure of the spinal cord as seen on magnetic resonance imaging). Collaborative labeling is a new paradigm that offers a robust alternative that may realize both the throughput of automation and the guidance of experts. Yet, distributing manual labeling expertise across individuals and sites introduces potential human factors concerns (e.g., training, software usability) and statistical considerations (e.g., fusion of information, assessment of confidence, bias) that must be further explored. During the labeling process, it is simple to ask raters to self-assess the confidence of their labels, but this is rarely done and has not been previously quantitatively studied. Herein, the authors explore the utility of self-assessment in relation to automated assessment of rater performance in the context of statistical fusion. Methods: The authors conducted a study of 66 volumes manually labeled by 75 minimally trained human raters recruited from the university undergraduate population. Raters were given 15 min of training during which they were shown examples of correct segmentation, and the online segmentation tool was demonstrated. The volumes were labeled 2D slice-wise, and the slices were unordered. A self-assessed quality metric was produced by raters for each slice by marking a confidence bar superimposed on the slice. Volumes produced by both voting and statistical fusion algorithms were compared against a set of expert segmentations of the same volumes. Results: Labels for 8825 distinct slices were obtained. Simple majority voting resulted in statistically poorer performance than voting weighted by self-assessed performance

  2. Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2012-01-01

    measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet packet transformation (WPT). Based on the extracted features all data segments were classified using a support vector machine (SVM) algorithm as simulated seizure or normal activity. A case study...... of the seizure from the patient showed that the simulated seizures were visually similar to the epileptic one. The multi-modal intelligent seizure acquisition (MISA) system showed high sensitivity, short detection latency and low false detection rate. The results showed superiority of the multi- modal detection...... system compared to the uni-modal one. The presented system has a promising potential for seizure detection based on multi-modal data....

  3. Compact imaging Bragg spectrometer for fusion devices

    International Nuclear Information System (INIS)

    Bertschinger, G.; Biel, W.; Jaegers, H.; Marchuk, O.

    2004-01-01

    A compact imaging x-ray spectrometer has been designed for tokamaks and stellarators to measure the plasma parameters at different spatial chords. It has been optimized for high spectral resolution and high sensitivity. High spectral resolution is obtained by using solid state detectors and minimizing the imaging errors of the spherical crystals. It is shown, that using spherical crystals the solid angle and hence the throughput can be increased significantly, without compromising the spectral resolution. The design is useful for the measurement of the spectra of He- and H-like ions from Si to Kr. The spectral resolution is sufficient for the measurement of plasma parameters. The temporal resolution is high enough for transport studies by gas puff and laser ablation experiments. The design is based on a modified Johann spectrometer mount, utilizing a spherically bent crystal instead of the cylindrically bent crystal in the traditional Johann mount. The astigmatism of the wavelength selective reflection on the spherical crystal is applied to obtain imaging of an extended plasma source on a two-dimensional detector. For each element, a separate crystal is required, only in few cases, a crystal can be used for the spectra of two elements. For the spectra of most of the He-like ions from Si up to Kr, suitable crystal cuts have been found on quartz, silicon and germanium crystals with Bragg angles in a small interval around the design value of 53.5 deg. All of the crystals have the same radius. They are fixed on a rotational table. The distance to the detector is adjusted by an x-y table to fit to the Rowland circle

  4. An efficient multiple exposure image fusion in JPEG domain

    Science.gov (United States)

    Hebbalaguppe, Ramya; Kakarala, Ramakrishna

    2012-01-01

    In this paper, we describe a method to fuse multiple images taken with varying exposure times in the JPEG domain. The proposed algorithm finds its application in HDR image acquisition and image stabilization for hand-held devices like mobile phones, music players with cameras, digital cameras etc. Image acquisition at low light typically results in blurry and noisy images for hand-held camera's. Altering camera settings like ISO sensitivity, exposure times and aperture for low light image capture results in noise amplification, motion blur and reduction of depth-of-field respectively. The purpose of fusing multiple exposures is to combine the sharp details of the shorter exposure images with high signal-to-noise-ratio (SNR) of the longer exposure images. The algorithm requires only a single pass over all images, making it efficient. It comprises of - sigmoidal boosting of shorter exposed images, image fusion, artifact removal and saturation detection. Algorithm does not need more memory than a single JPEG macro block to be kept in memory making it feasible to be implemented as the part of a digital cameras hardware image processing engine. The Artifact removal step reuses the JPEGs built-in frequency analysis and hence benefits from the considerable optimization and design experience that is available for JPEG.

  5. Development and application of PET-MRI image fusion technology

    International Nuclear Information System (INIS)

    Song Jianhua; Zhao Jinhua; Qiao Wenli

    2011-01-01

    The emerging and growing in popularity of PET-CT scanner brings us the convenience and cognizes the advantages such as diagnosis, staging, curative effect evaluation and prognosis for malignant tumor. And the PET-MRI installing maybe a new upsurge when the machine gradually mature, because of the MRI examination without the radiation exposure and with the higher soft tissue resolution. This paper summarized the developing course of image fusion technology and some researches of clinical application about PET-MRI at present, in order to help people to understand the functions and know its wide application of the upcoming new instrument, mainly focuses the application on the central nervous system and some soft tissue lesions. And before PET-MRI popularization, people can still carry out some researches of various image fusion and clinical application on the current equipment. (authors)

  6. Study on Efficiency of Fusion Techniques for IKONOS Images

    International Nuclear Information System (INIS)

    Liu, Yanmei; Yu, Haiyang; Guijun, Yang; Nie, Chenwei; Yang, Xiaodong; Ren, Dong

    2014-01-01

    Many image fusion techniques have been proposed to achieve optimal resolution in the spatial and spectral domains. Six different merging methods were listed in this paper and the efficiency of fusion techniques was assessed in qualitative and quantitative aspect. Both local and global evaluation parameters were used in the spectral quality and a Laplace filter method was used in spatial quality assessment. By simulation, the spectral quality of the images merged by Brovery was demonstrated to be the worst. In contrast, GS and PCA algorithms, especially the Pansharpening provided higher spectral quality than the standard Brovery, wavelet and CN methods. In spatial quality assessment, the CN method represented best compared with that of others, while the Brovery algorithm was worst. The wavelet parameters that performed best achieved acceptable spectral and spatial quality compared to the others

  7. Fourier domain image fusion for differential X-ray phase-contrast breast imaging

    International Nuclear Information System (INIS)

    Coello, Eduardo; Sperl, Jonathan I.; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

    2017-01-01

    X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well.

  8. Fourier domain image fusion for differential X-ray phase-contrast breast imaging

    Energy Technology Data Exchange (ETDEWEB)

    Coello, Eduardo, E-mail: eduardo.coello@tum.de [GE Global Research, Garching (Germany); Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality, Institut für Informatik, Technische Universität München, Garching (Germany); Sperl, Jonathan I.; Bequé, Dirk [GE Global Research, Garching (Germany); Benz, Tobias [Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality, Institut für Informatik, Technische Universität München, Garching (Germany); Scherer, Kai; Herzen, Julia [Lehrstuhl für Biomedizinische Physik, Physik-Department & Institut für Medizintechnik, Technische Universität München, Garching (Germany); Sztrókay-Gaul, Anikó; Hellerhoff, Karin [Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich (Germany); Pfeiffer, Franz [Lehrstuhl für Biomedizinische Physik, Physik-Department & Institut für Medizintechnik, Technische Universität München, Garching (Germany); Cozzini, Cristina [GE Global Research, Garching (Germany); Grandl, Susanne [Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich (Germany)

    2017-04-15

    X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well.

  9. Study on change of multi-modally evoked potentials in nasopharyngeal carcinoma patients after radiotherapy

    International Nuclear Information System (INIS)

    Qin Ling; Chen Jiaxin; Zhang Lixiang; Wang Tiejian; Han Min; Lu Xiaoling

    2001-01-01

    Objective: To investigate possible changes of multi-modally evoked potentials in nasopharyngeal carcinoma patients after radiotherapy. Methods: Altogether 48 nasopharyngeal carcinoma patients receiving primary conventional external beam irradiation were examined before and after radiotherapy to determine their brainstem auditory-evoked potential (BAEP), short-latency somatosensory-evoked potential (SLSEP) and pattern reversal visual-evoked potential (PRVEP). Results: In comparison with the conditions before radiotherapy, in different periods after radiotherapy abnormal peak latency and interval latency difference were found in BAEP, SLSEP and PRVEP. Conclusion: Nasopharyngeal carcinoma after radiotherapy may cause abnormal function of nerve conduction in early periods, which can be showed by BAEP, SLSEP, PRVEP, and injury can be timely detected if the three evoked potentials are used together. Thus authors suggest BAEP, SLSEP, PRVEP should be examined in nasopharyngeal carcinoma patients during and after the radiotherapy so as to find early damage in auditory somatosensory and visual conduction pathways

  10. Incidental acquisition of foreign language vocabulary through brief multi-modal exposure.

    Science.gov (United States)

    Bisson, Marie-Josée; van Heuven, Walter J B; Conklin, Kathy; Tunney, Richard J

    2013-01-01

    First language acquisition requires relatively little effort compared to foreign language acquisition and happens more naturally through informal learning. Informal exposure can also benefit foreign language learning, although evidence for this has been limited to speech perception and production. An important question is whether informal exposure to spoken foreign language also leads to vocabulary learning through the creation of form-meaning links. Here we tested the impact of exposure to foreign language words presented with pictures in an incidental learning phase on subsequent explicit foreign language learning. In the explicit learning phase, we asked adults to learn translation equivalents of foreign language words, some of which had appeared in the incidental learning phase. Results revealed rapid learning of the foreign language words in the incidental learning phase showing that informal exposure to multi-modal foreign language leads to foreign language vocabulary acquisition. The creation of form-meaning links during the incidental learning phase is discussed.

  11. Exploiting Higher Order and Multi-modal Features for 3D Object Detection

    DEFF Research Database (Denmark)

    Kiforenko, Lilita

    that describe object visual appearance such as shape, colour, texture etc. This thesis focuses on robust object detection and pose estimation of rigid objects using 3D information. The thesis main contributions are novel feature descriptors together with object detection and pose estimation algorithms....... The initial work introduces a feature descriptor that uses edge categorisation in combination with a local multi-modal histogram descriptor in order to detect objects with little or no texture or surface variation. The comparison is performed with a state-of-the-art method, which is outperformed...... of the methods work well for one type of objects in a specific scenario, in another scenario or with different objects they might fail, therefore more robust solutions are required. The typical problem solution is the design of robust feature descriptors, where feature descriptors contain information...

  12. Architecture of the Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet)

    Energy Technology Data Exchange (ETDEWEB)

    Aiken, R.J.; Carlson, R.A.; Foster, I.T. [and others

    1997-01-01

    The research and education (R&E) community requires persistent and scaleable network infrastructure to concurrently support production and research applications as well as network research. In the past, the R&E community has relied on supporting parallel network and end-node infrastructures, which can be very expensive and inefficient for network service managers and application programmers. The grand challenge in networking is to provide support for multiple, concurrent, multi-layer views of the network for the applications and the network researchers, and to satisfy the sometimes conflicting requirements of both while ensuring one type of traffic does not adversely affect the other. Internet and telecommunications service providers will also benefit from a multi-modal infrastructure, which can provide smoother transitions to new technologies and allow for testing of these technologies with real user traffic while they are still in the pre-production mode. The authors proposed approach requires the use of as much of the same network and end system infrastructure as possible to reduce the costs needed to support both classes of activities (i.e., production and research). Breaking the infrastructure into segments and objects (e.g., routers, switches, multiplexors, circuits, paths, etc.) gives the capability to dynamically construct and configure the virtual active networks to address these requirements. These capabilities must be supported at the campus, regional, and wide-area network levels to allow for collaboration by geographically dispersed groups. The Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet) described in this report is an initial architecture and framework designed to identify and support the capabilities needed for the proposed combined infrastructure and to address related research issues.

  13. Enabling image fusion for a CT guided needle placement robot

    Science.gov (United States)

    Seifabadi, Reza; Xu, Sheng; Aalamifar, Fereshteh; Velusamy, Gnanasekar; Puhazhendi, Kaliyappan; Wood, Bradford J.

    2017-03-01

    Purpose: This study presents development and integration of hardware and software that enables ultrasound (US) and computer tomography (CT) fusion for a FDA-approved CT-guided needle placement robot. Having real-time US image registered to a priori-taken intraoperative CT image provides more anatomic information during needle insertion, in order to target hard-to-see lesions or avoid critical structures invisible to CT, track target motion, and to better monitor ablation treatment zone in relation to the tumor location. Method: A passive encoded mechanical arm is developed for the robot in order to hold and track an abdominal US transducer. This 4 degrees of freedom (DOF) arm is designed to attach to the robot end-effector. The arm is locked by default and is released by a press of button. The arm is designed such that the needle is always in plane with US image. The articulated arm is calibrated to improve its accuracy. Custom designed software (OncoNav, NIH) was developed to fuse real-time US image to a priori-taken CT. Results: The accuracy of the end effector before and after passive arm calibration was 7.07mm +/- 4.14mm and 1.74mm +/-1.60mm, respectively. The accuracy of the US image to the arm calibration was 5mm. The feasibility of US-CT fusion using the proposed hardware and software was demonstrated in an abdominal commercial phantom. Conclusions: Calibration significantly improved the accuracy of the arm in US image tracking. Fusion of US to CT using the proposed hardware and software was feasible.

  14. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

    Science.gov (United States)

    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

  15. T2*-weighted image/T2-weighted image fusion in postimplant dosimetry of prostate brachytherapy

    International Nuclear Information System (INIS)

    Katayama, Norihisa; Takemoto, Mitsuhiro; Yoshio, Kotaro

    2011-01-01

    Computed tomography (CT)/magnetic resonance imaging (MRI) fusion is considered to be the best method for postimplant dosimetry of permanent prostate brachytherapy; however, it is inconvenient and costly. In T2 * -weighted image (T2 * -WI), seeds can be easily detected without the use of an intravenous contrast material. We present a novel method for postimplant dosimetry using T2 * -WI/T2-weighted image (T2-WI) fusion. We compared the outcomes of T2 * -WI/T2-WI fusion-based and CT/T2-WI fusion-based postimplant dosimetry. Between April 2008 and July 2009, 50 consecutive prostate cancer patients underwent brachytherapy. All the patients were treated with 144 Gy of brachytherapy alone. Dose-volume histogram (DVH) parameters (prostate D90, prostate V100, prostate V150, urethral D10, and rectal D2cc) were prospectively compared between T2 * -WI/T2-WI fusion-based and CT/T2-WI fusion-based dosimetry. All the DVH parameters estimated by T2 * -WI/T2-WI fusion-based dosimetry strongly correlated to those estimated by CT/T2-WI fusion-based dosimetry (0.77≤ R ≤0.91). No significant difference was observed in these parameters between the two methods, except for prostate V150 (p=0.04). These results show that T2 * -WI/T2-WI fusion-based dosimetry is comparable or superior to MRI-based dosimetry as previously reported, because no intravenous contrast material is required. For some patients, rather large differences were observed in the value between the 2 methods. We thought these large differences were a result of seed miscounts in T2 * -WI and shifts in fusion. Improving the image quality of T2 * -WI and the image acquisition speed of T2 * -WI and T2-WI may decrease seed miscounts and fusion shifts. Therefore, in the future, T2 * -WI/T2-WI fusion may be more useful for postimplant dosimetry of prostate brachytherapy. (author)

  16. Improving Accuracy for Image Fusion in Abdominal Ultrasonography

    Directory of Open Access Journals (Sweden)

    Caroline Ewertsen

    2012-08-01

    Full Text Available Image fusion involving real-time ultrasound (US is a technique where previously recorded computed tomography (CT or magnetic resonance images (MRI are reformatted in a projection to fit the real-time US images after an initial co-registration. The co-registration aligns the images by means of common planes or points. We evaluated the accuracy of the alignment when varying parameters as patient position, respiratory phase and distance from the co-registration points/planes. We performed a total of 80 co-registrations and obtained the highest accuracy when the respiratory phase for the co-registration procedure was the same as when the CT or MRI was obtained. Furthermore, choosing co-registration points/planes close to the area of interest also improved the accuracy. With all settings optimized a mean error of 3.2 mm was obtained. We conclude that image fusion involving real-time US is an accurate method for abdominal examinations and that the accuracy is influenced by various adjustable factors that should be kept in mind.

  17. Image fusion in x-ray differential phase-contrast imaging

    Science.gov (United States)

    Haas, W.; Polyanskaya, M.; Bayer, F.; Gödel, K.; Hofmann, H.; Rieger, J.; Ritter, A.; Weber, T.; Wucherer, L.; Durst, J.; Michel, T.; Anton, G.; Hornegger, J.

    2012-02-01

    Phase-contrast imaging is a novel modality in the field of medical X-ray imaging. The pioneer method is the grating-based interferometry which has no special requirements to the X-ray source and object size. Furthermore, it provides three different types of information of an investigated object simultaneously - absorption, differential phase-contrast and dark-field images. Differential phase-contrast and dark-field images represent a completely new information which has not yet been investigated and studied in context of medical imaging. In order to introduce phase-contrast imaging as a new modality into medical environment the resulting information about the object has to be correctly interpreted. The three output images reflect different properties of the same object the main challenge is to combine and visualize these data in such a way that it diminish the information explosion and reduce the complexity of its interpretation. This paper presents an intuitive image fusion approach which allows to operate with grating-based phase-contrast images. It combines information of the three different images and provides a single image. The approach is implemented in a fusion framework which is aimed to support physicians in study and analysis. The framework provides the user with an intuitive graphical user interface allowing to control the fusion process. The example given in this work shows the functionality of the proposed method and the great potential of phase-contrast imaging in medical practice.

  18. Research on Methods of Infrared and Color Image Fusion Based on Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Zhao Rentao

    2014-06-01

    Full Text Available There is significant difference in the imaging features of infrared image and color image, but their fusion images also have very good complementary information. In this paper, based on the characteristics of infrared image and color image, first of all, wavelet transform is applied to the luminance component of the infrared image and color image. In multi resolution the relevant regional variance is regarded as the activity measure, relevant regional variance ratio as the matching measure, and the fusion image is enhanced in the process of integration, thus getting the fused images by final synthesis module and multi-resolution inverse transform. The experimental results show that the fusion image obtained by the method proposed in this paper is better than the other methods in keeping the useful information of the original infrared image and the color information of the original color image. In addition, the fusion image has stronger adaptability and better visual effect.

  19. Multiscale infrared and visible image fusion using gradient domain guided image filtering

    Science.gov (United States)

    Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

    2018-03-01

    For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.

  20. Risk factors for insufficient perioperative oral nutrition after hip fracture surgery within a multi-modal rehabilitation programme

    DEFF Research Database (Denmark)

    Foss, Nicolai B; Jensen, Pia S; Kehlet, Henrik

    2007-01-01

    To examine oral nutritional intake in the perioperative phase in elderly hip fracture patients treated according to a well-defined multi-modal rehabilitation program, including unselected oral nutritional supplementation, and to identify independent risk factors for insufficient nutritional intake....

  1. Sex in the Curriculum: The Effect of a Multi-Modal Sexual History-Taking Module on Medical Student Skills

    Science.gov (United States)

    Lindau, Stacy Tessler; Goodrich, Katie G.; Leitsch, Sara A.; Cook, Sandy

    2008-01-01

    Purpose: The objective of this study was to determine the effect of a multi-modal curricular intervention designed to teach sexual history-taking skills to medical students. The Association of Professors of Gynecology and Obstetrics, the National Board of Medical Examiners, and others, have identified sexual history-taking as a learning objective…

  2. HALO: a reconfigurable image enhancement and multisensor fusion system

    Science.gov (United States)

    Wu, F.; Hickman, D. L.; Parker, Steve J.

    2014-06-01

    Contemporary high definition (HD) cameras and affordable infrared (IR) imagers are set to dramatically improve the effectiveness of security, surveillance and military vision systems. However, the quality of imagery is often compromised by camera shake, or poor scene visibility due to inadequate illumination or bad atmospheric conditions. A versatile vision processing system called HALO™ is presented that can address these issues, by providing flexible image processing functionality on a low size, weight and power (SWaP) platform. Example processing functions include video distortion correction, stabilisation, multi-sensor fusion and image contrast enhancement (ICE). The system is based around an all-programmable system-on-a-chip (SoC), which combines the computational power of a field-programmable gate array (FPGA) with the flexibility of a CPU. The FPGA accelerates computationally intensive real-time processes, whereas the CPU provides management and decision making functions that can automatically reconfigure the platform based on user input and scene content. These capabilities enable a HALO™ equipped reconnaissance or surveillance system to operate in poor visibility, providing potentially critical operational advantages in visually complex and challenging usage scenarios. The choice of an FPGA based SoC is discussed, and the HALO™ architecture and its implementation are described. The capabilities of image distortion correction, stabilisation, fusion and ICE are illustrated using laboratory and trials data.

  3. Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

    Science.gov (United States)

    Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

    2018-06-15

    Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

  4. Structural changes in socio-affective networks: Multi-modal MRI findings in long-term meditation practitioners.

    Science.gov (United States)

    Engen, Haakon G; Bernhardt, Boris C; Skottnik, Leon; Ricard, Matthieu; Singer, Tania

    2017-08-31

    Our goal was to assess the effects of long-term mental training in socio-affective skills on structural brain networks. We studied a group of long-term meditation practitioners (LTMs) who have focused on cultivating socio-affective skills using loving-kindness and compassion meditation for an average of 40k h, comparing these to meditation-naïve controls. To maximize homogeneity of prior practice, LTMs were included only if they had undergone extensive full-time meditation retreats in the same center. MRI-based cortical thickness analysis revealed increased thickness in the LTM cohort relative to meditation-native controls in fronto-insular cortices. To identify functional networks relevant for the generation of socio-affective states, structural imaging analysis were complemented by fMRI analysis in LTMs, showing amplitude increases during a loving-kindness meditation session relative to non-meditative rest in multiple prefrontal and insular regions bilaterally. Importantly, functional findings partially overlapped with regions of cortical thickness increases in the left ventrolateral prefrontal cortex and anterior insula, suggesting that these regions may play a central role in the generation of emotional states relevant for the meditative practice. Our multi-modal MRI approach revealed structural changes in LTMs who have cultivated loving-kindness and compassion for a significant period of their life in functional networks activated by these practices. These preliminary cross-sectional findings motivate future longitudinal work studying brain plasticity following the regular practice of skills aiming at enhancing human altruism and prosocial motivation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Multimodality imaging: transfer and fusion of SPECT and MRI data

    International Nuclear Information System (INIS)

    Knesaurek, K.

    1994-01-01

    Image fusion is a technique which offers the best of both worlds. It unites the two basic types of medical images: functional body images(PET or SPECT scans), which provide physiological information, and structural images (CT or MRI), which provide an anatomic map of the body. Control-point based registration technique was developed and used. Tc-99m point sources were used as external markers in SPECT studies while, for MRI and CT imaging only anatomic landmarks were used as a control points. The MRI images were acquired on GE Signa 1.2 system and CT data on a GE 9800 scanner. SPECT studies were performed 1h after intravenous injection of the 740 MBq of the Tc-99m-HMPAO on the triple-headed TRIONIX gamma camera. B-spline and bilinear interpolation were used for the rotation, scaling and translation of the images. In the process of creation of a single composite image, in order to retain information from the individual images, MRI (or CT) image was scaled to one color range and a SPECT image to another. In some situations the MRI image was kept black-and-white while the SPECT image was pasted on top of it in 'opaque' mode. Most errors which propagate through the matching process are due to sample size, imperfection of the acquisition system, noise and interpolations used. Accuracy of the registration was investigated by SPECT-CT study performed on a phantom study. The results has shown that accuracy of the matching process is better, or at worse, equal to 2 mm. (author)

  6. An enhanced approach for biomedical image restoration using image fusion techniques

    Science.gov (United States)

    Karam, Ghada Sabah; Abbas, Fatma Ismail; Abood, Ziad M.; Kadhim, Kadhim K.; Karam, Nada S.

    2018-05-01

    Biomedical image is generally noisy and little blur due to the physical mechanisms of the acquisition process, so one of the common degradations in biomedical image is their noise and poor contrast. The idea of biomedical image enhancement is to improve the quality of the image for early diagnosis. In this paper we are using Wavelet Transformation to remove the Gaussian noise from biomedical images: Positron Emission Tomography (PET) image and Radiography (Radio) image, in different color spaces (RGB, HSV, YCbCr), and we perform the fusion of the denoised images resulting from the above denoising techniques using add image method. Then some quantive performance metrics such as signal -to -noise ratio (SNR), peak signal-to-noise ratio (PSNR), and Mean Square Error (MSE), etc. are computed. Since this statistical measurement helps in the assessment of fidelity and image quality. The results showed that our approach can be applied of Image types of color spaces for biomedical images.

  7. Thought–shape fusion and body image in eating disorders

    Directory of Open Access Journals (Sweden)

    Jáuregui-Lobera I

    2012-10-01

    Full Text Available Ignacio Jáuregui-Lobera,1 Patricia Bolaños-Ríos,2 Inmaculada Ruiz-Prieto21Department of Nutrition and Bromatology, Pablo de Olavide University, Seville, Spain; 2Behavioral Sciences Institute, Seville, SpainPurpose: The aim of this study was to analyze the relationships among thought–shape fusion (TSF, specific instruments to assess body image disturbances, and body image quality of life in eating disorder patients in order to improve the understanding of the links between body image concerns and a specific bias consisting of beliefs about the consequences of thinking about forbidden foods.Patients and methods: The final sample included 76 eating disorder patients (mean age 20.13 ± 2.28 years; 59 women and seven men. After having obtained informed consent, the following questionnaires were administered: Body Appreciation Scale (BAS, Body Image Quality of Life Inventory (BIQLI-SP, Body Shape Questionnaire (BSQ, Eating Disorders Inventory-2 (EDI-2, State-Trait Anxiety Inventory (STAI, Symptom Checklist-90-Revised (SCL-90-R and Thought-Shape Fusion Questionnaire (TSF-Q.Results: Significant correlations were found between TSF-Q and body image-related variables. Those with higher scores in TSF showed higher scores in the BSQ (P < 0.0001, Eating Disorder Inventory – Drive for Thinness (EDI-DT (P < 0.0001, and Eating Disorder Inventory – Body Dissatisfaction (EDI-BD (P < 0.0001. The same patients showed lower scores in the BAS (P < 0.0001. With respect to the psychopathological variables, patients with high TSF obtained higher scores in all SCL-90-R subscales as well as in the STAI.Conclusion: The current study shows the interrelations among different body image-related variables, TSF, and body image quality of life.Keywords: cognitive distortions, quality of life, body appreciation, psychopathology, anorexia nervosa, bulimia nervosa

  8. [Research progress of multi-model medical image fusion and recognition].

    Science.gov (United States)

    Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

    2013-10-01

    Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

  9. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

    Directory of Open Access Journals (Sweden)

    Yuanshen Zhao

    2016-01-01

    Full Text Available Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

  10. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion.

    Science.gov (United States)

    Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

    2016-01-29

    Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

  11. Multi-modal MRI analysis with disease-specific spatial filtering: initial testing to predict mild cognitive impairment patients who convert to Alzheimer’s disease

    Directory of Open Access Journals (Sweden)

    Kenichi eOishi

    2011-08-01

    Full Text Available Background: Alterations of the gray and white matter have been identified in Alzheimer’s disease (AD by structural MRI and diffusion tensor imaging (DTI. However, whether the combination of these modalities could increase the diagnostic performance is unknown.Methods: Participants included 19 AD patients, 22 amnestic mild cognitive impairment (aMCI patients, and 22 cognitively normal elderly (NC. The aMCI group was further divided into an aMCI-converter group (converted to AD dementia within three years, and an aMCI-stable group who did not convert in this time period. A T1-weighted image, a T2 map, and a DTI of each participant were normalized, and voxel-based comparisons between AD and NC groups were performed. Regions-of-interest, which defined the areas with significant differences between AD and NC, were created for each modality and named disease-specific spatial filters (DSF. Linear discriminant analysis was used to optimize the combination of multiple MRI measurements extracted by DSF to effectively differentiate AD from NC. The resultant DSF and the discriminant function were applied to the aMCI group to investigate the power to differentiate the aMCI-converters from the aMCI-stable patients. Results: The multi-modal approach with AD-specific filters led to a predictive model with an area under the receiver operating characteristic curve (AUC of 0.93, in differentiating aMCI-converters from aMCI-stable patients. This AUC was better than that of a single-contrast-based approach, such as T1-based morphometry or diffusion anisotropy analysis. Conclusion: The multi-modal approach has the potential to increase the value of MRI in predicting conversion from aMCI to AD.

  12. Optical asymmetric watermarking using modified wavelet fusion and diffractive imaging

    Science.gov (United States)

    Mehra, Isha; Nishchal, Naveen K.

    2015-05-01

    In most of the existing image encryption algorithms the generated keys are in the form of a noise like distribution with a uniform distributed histogram. However, the noise like distribution is an apparent sign indicating the presence of the keys. If the keys are to be transferred through some communication channels, then this may lead to a security problem. This is because; the noise like features may easily catch people's attention and bring more attacks. To address this problem it is required to transfer the keys to some other meaningful images to disguise the attackers. The watermarking schemes are complementary to image encryption schemes. In most of the iterative encryption schemes, support constraints play an important role of the keys in order to decrypt the meaningful data. In this article, we have transferred the support constraints which are generated by axial translation of CCD camera using amplitude-, and phase- truncation approach, into different meaningful images. This has been done by developing modified fusion technique in wavelet transform domain. The second issue is, in case, the meaningful images are caught by the attacker then how to solve the copyright protection. To resolve this issue, watermark detection plays a crucial role. For this purpose, it is necessary to recover the original image using the retrieved watermarks/support constraints. To address this issue, four asymmetric keys have been generated corresponding to each watermarked image to retrieve the watermarks. For decryption, an iterative phase retrieval algorithm is applied to extract the plain-texts from corresponding retrieved watermarks.

  13. Fusion of PET and MRI for Hybrid Imaging

    Science.gov (United States)

    Cho, Zang-Hee; Son, Young-Don; Kim, Young-Bo; Yoo, Seung-Schik

    Recently, the development of the fusion PET-MRI system has been actively studied to meet the increasing demand for integrated molecular and anatomical imaging. MRI can provide detailed anatomical information on the brain, such as the locations of gray and white matter, blood vessels, axonal tracts with high resolution, while PET can measure molecular and genetic information, such as glucose metabolism, neurotransmitter-neuroreceptor binding and affinity, protein-protein interactions, and gene trafficking among biological tissues. State-of-the-art MRI systems, such as the 7.0 T whole-body MRI, now can visualize super-fine structures including neuronal bundles in the pons, fine blood vessels (such as lenticulostriate arteries) without invasive contrast agents, in vivo hippocampal substructures, and substantia nigra with excellent image contrast. High-resolution PET, known as High-Resolution Research Tomograph (HRRT), is a brain-dedicated system capable of imaging minute changes of chemicals, such as neurotransmitters and -receptors, with high spatial resolution and sensitivity. The synergistic power of the two, i.e., ultra high-resolution anatomical information offered by a 7.0 T MRI system combined with the high-sensitivity molecular information offered by HRRT-PET, will significantly elevate the level of our current understanding of the human brain, one of the most delicate, complex, and mysterious biological organs. This chapter introduces MRI, PET, and PET-MRI fusion system, and its algorithms are discussed in detail.

  14. Region-based multifocus image fusion for the precise acquisition of Pap smear images.

    Science.gov (United States)

    Tello-Mijares, Santiago; Bescós, Jesús

    2018-05-01

    A multifocus image fusion method to obtain a single focused image from a sequence of microscopic high-magnification Papanicolau source (Pap smear) images is presented. These images, captured each in a different position of the microscope lens, frequently show partially focused cells or parts of cells, which makes them unpractical for the direct application of image analysis techniques. The proposed method obtains a focused image with a high preservation of original pixels information while achieving a negligible visibility of the fusion artifacts. The method starts by identifying the best-focused image of the sequence; then, it performs a mean-shift segmentation over this image; the focus level of the segmented regions is evaluated in all the images of the sequence, and best-focused regions are merged in a single combined image; finally, this image is processed with an adaptive artifact removal process. The combination of a region-oriented approach, instead of block-based approaches, and a minimum modification of the value of focused pixels in the original images achieve a highly contrasted image with no visible artifacts, which makes this method especially convenient for the medical imaging domain. The proposed method is compared with several state-of-the-art alternatives over a representative dataset. The experimental results show that our proposal obtains the best and more stable quality indicators. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  15. A method based on IHS cylindrical transform model for quality assessment of image fusion

    Science.gov (United States)

    Zhu, Xiaokun; Jia, Yonghong

    2005-10-01

    Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

  16. A novel fusion imaging system for endoscopic ultrasound

    DEFF Research Database (Denmark)

    Gruionu, Lucian Gheorghe; Saftoiu, Adrian; Gruionu, Gabriel

    2016-01-01

    BACKGROUND AND OBJECTIVE: Navigation of a flexible endoscopic ultrasound (EUS) probe inside the gastrointestinal (GI) tract is problematic due to the small window size and complex anatomy. The goal of the present study was to test the feasibility of a novel fusion imaging (FI) system which uses...... time was 24.6 ± 6.6 min, while the time to reach the clinical target was 8.7 ± 4.2 min. CONCLUSIONS: The FI system is feasible for clinical use, and can reduce the learning curve for EUS procedures and improve navigation and targeting in difficult anatomic locations....

  17. A Hybrid Dynamic System Assessment Methodology for Multi-Modal Transportation-Electrification

    Directory of Open Access Journals (Sweden)

    Thomas J.T. van der Wardt

    2017-05-01

    Full Text Available In recent years, electrified transportation, be it in the form of buses, trains, or cars have become an emerging form of mobility. Electric vehicles (EVs, especially, are set to expand the amount of electric miles driven and energy consumed. Nevertheless, the question remains as to whether EVs will be technically feasible within infrastructure systems. Fundamentally, EVs interact with three interconnected systems: the (physical transportation system, the electric power grid, and their supporting information systems. Coupling of the two physical systems essentially forms a nexus, the transportation-electricity nexus (TEN. This paper presents a hybrid dynamic system assessment methodology for multi-modal transportation-electrification. At its core, it utilizes a mathematical model which consists of a marked Petri-net model superimposed on the continuous time microscopic traffic dynamics and the electrical state evolution. The methodology consists of four steps: (1 establish the TEN structure; (2 establish the TEN behavior; (3 establish the TEN Intelligent Transportation-Energy System (ITES decision-making; and (4 assess the TEN performance. In the presentation of the methodology, the Symmetrica test case is used throughout as an illustrative example. Consequently, values for several measures of performance are provided. This methodology is presented generically and may be used to assess the effects of transportation-electrification in any city or area; opening up possibilities for many future studies.

  18. A multi-modal treatment approach for the shoulder: A 4 patient case series

    Directory of Open Access Journals (Sweden)

    Pollard Henry

    2005-09-01

    Full Text Available Abstract Background This paper describes the clinical management of four cases of shoulder impingement syndrome using a conservative multimodal treatment approach. Clinical Features Four patients presented to a chiropractic clinic with chronic shoulder pain, tenderness in the shoulder region and a limited range of motion with pain and catching. After physical and orthopaedic examination a clinical diagnosis of shoulder impingement syndrome was reached. The four patients were admitted to a multi-modal treatment protocol including soft tissue therapy (ischaemic pressure and cross-friction massage, 7 minutes of phonophoresis (driving of medication into tissue with ultrasound with 1% cortisone cream, diversified spinal and peripheral joint manipulation and rotator cuff and shoulder girdle muscle exercises. The outcome measures for the study were subjective/objective visual analogue pain scales (VAS, range of motion (goniometer and return to normal daily, work and sporting activities. All four subjects at the end of the treatment protocol were symptom free with all outcome measures being normal. At 1 month follow up all patients continued to be symptom free with full range of motion and complete return to normal daily activities. Conclusion This case series demonstrates the potential benefit of a multimodal chiropractic protocol in resolving symptoms associated with a suspected clinical diagnosis of shoulder impingement syndrome.

  19. A software framework for real-time multi-modal detection of microsleeps.

    Science.gov (United States)

    Knopp, Simon J; Bones, Philip J; Weddell, Stephen J; Jones, Richard D

    2017-09-01

    A software framework is described which was designed to process EEG, video of one eye, and head movement in real time, towards achieving early detection of microsleeps for prevention of fatal accidents, particularly in transport sectors. The framework is based around a pipeline structure with user-replaceable signal processing modules. This structure can encapsulate a wide variety of feature extraction and classification techniques and can be applied to detecting a variety of aspects of cognitive state. Users of the framework can implement signal processing plugins in C++ or Python. The framework also provides a graphical user interface and the ability to save and load data to and from arbitrary file formats. Two small studies are reported which demonstrate the capabilities of the framework in typical applications: monitoring eye closure and detecting simulated microsleeps. While specifically designed for microsleep detection/prediction, the software framework can be just as appropriately applied to (i) other measures of cognitive state and (ii) development of biomedical instruments for multi-modal real-time physiological monitoring and event detection in intensive care, anaesthesiology, cardiology, neurosurgery, etc. The software framework has been made freely available for researchers to use and modify under an open source licence.

  20. Interactive natural language acquisition in a multi-modal recurrent neural architecture

    Science.gov (United States)

    Heinrich, Stefan; Wermter, Stefan

    2018-01-01

    For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

  1. Anticipation by multi-modal association through an artificial mental imagery process

    Science.gov (United States)

    Gaona, Wilmer; Escobar, Esaú; Hermosillo, Jorge; Lara, Bruno

    2015-01-01

    Mental imagery has become a central issue in research laboratories seeking to emulate basic cognitive abilities in artificial agents. In this work, we propose a computational model to produce an anticipatory behaviour by means of a multi-modal off-line hebbian association. Unlike the current state of the art, we propose to apply hebbian learning during an internal sensorimotor simulation, emulating a process of mental imagery. We associate visual and tactile stimuli re-enacted by a long-term predictive simulation chain motivated by covert actions. As a result, we obtain a neural network which provides a robot with a mechanism to produce a visually conditioned obstacle avoidance behaviour. We developed our system in a physical Pioneer 3-DX robot and realised two experiments. In the first experiment we test our model on one individual navigating in two different mazes. In the second experiment we assess the robustness of the model by testing in a single environment five individuals trained under different conditions. We believe that our work offers an underpinning mechanism in cognitive robotics for the study of motor control strategies based on internal simulations. These strategies can be seen analogous to the mental imagery process known in humans, opening thus interesting pathways to the construction of upper-level grounded cognitive abilities.

  2. Performance processes within affect-related performance zones: a multi-modal investigation of golf performance.

    Science.gov (United States)

    van der Lei, Harry; Tenenbaum, Gershon

    2012-12-01

    Individual affect-related performance zones (IAPZs) method utilizing Kamata et al. (J Sport Exerc Psychol 24:189-208, 2002) probabilistic model of determining the individual zone of optimal functioning was utilized as idiosyncratic affective patterns during golf performance. To do so, three male golfers of a varsity golf team were observed during three rounds of golf competition. The investigation implemented a multi-modal assessment approach in which the probabilistic relationship between affective states and both, performance process and performance outcome, measures were determined. More specifically, introspective (i.e., verbal reports) and objective (heart rate and respiration rate) measures of arousal were incorporated to examine the relationships between arousal states and both, process components (i.e., routine consistency, timing), and outcome scores related to golf performance. Results revealed distinguishable and idiosyncratic IAPZs associated with physiological and introspective measures for each golfer. The associations between the IAPZs and decision-making or swing/stroke execution were strong and unique for each golfer. Results are elaborated using cognitive and affect-related concepts, and applications for practitioners are provided.

  3. Tissue identification with micro-magnetic resonance imaging in a caprine spinal fusion model

    NARCIS (Netherlands)

    Uffen, M.; Krijnen, M.; Hoogendoorn, R.; Strijkers, G.; Everts, V.; Wuisman, P.; Smit, T.

    2008-01-01

    Nonunion is a major complication of spinal interbody fusion. Currently X-ray and computed tomography (CT) are used for evaluating the spinal fusion process. However, both imaging modalities have limitations in judgment of the early stages of this fusion process, as they only visualize mineralized

  4. IMPROVING THE QUALITY OF NEAR-INFRARED IMAGING OF IN VIVOBLOOD VESSELS USING IMAGE FUSION METHODS

    DEFF Research Database (Denmark)

    Jensen, Andreas Kryger; Savarimuthu, Thiusius Rajeeth; Sørensen, Anders Stengaard

    2009-01-01

    We investigate methods for improving the visual quality of in vivo images of blood vessels in the human forearm. Using a near-infrared light source and a dual CCD chip camera system capable of capturing images at visual and nearinfrared spectra, we evaluate three fusion methods in terms...... of their capability of enhancing the blood vessels while preserving the spectral signature of the original color image. Furthermore, we investigate a possibility of removing hair in the images using a fusion rule based on the "a trous" stationary wavelet decomposition. The method with the best overall performance...... with both speed and quality in mind is the Intensity Injection method. Using the developed system and the methods presented in this article, it is possible to create images of high visual quality with highly emphasized blood vessels....

  5. Analysis and Evaluation of IKONOS Image Fusion Algorithm Based on Land Cover Classification

    Institute of Scientific and Technical Information of China (English)

    Xia; JING; Yan; BAO

    2015-01-01

    Different fusion algorithm has its own advantages and limitations,so it is very difficult to simply evaluate the good points and bad points of the fusion algorithm. Whether an algorithm was selected to fuse object images was also depended upon the sensor types and special research purposes. Firstly,five fusion methods,i. e. IHS,Brovey,PCA,SFIM and Gram-Schmidt,were briefly described in the paper. And then visual judgment and quantitative statistical parameters were used to assess the five algorithms. Finally,in order to determine which one is the best suitable fusion method for land cover classification of IKONOS image,the maximum likelihood classification( MLC) was applied using the above five fusion images. The results showed that the fusion effect of SFIM transform and Gram-Schmidt transform were better than the other three image fusion methods in spatial details improvement and spectral information fidelity,and Gram-Schmidt technique was superior to SFIM transform in the aspect of expressing image details. The classification accuracy of the fused image using Gram-Schmidt and SFIM algorithms was higher than that of the other three image fusion methods,and the overall accuracy was greater than 98%. The IHS-fused image classification accuracy was the lowest,the overall accuracy and kappa coefficient were 83. 14% and 0. 76,respectively. Thus the IKONOS fusion images obtained by the Gram-Schmidt and SFIM were better for improving the land cover classification accuracy.

  6. Fusion of different modalities of imaging the fist

    International Nuclear Information System (INIS)

    Verdenet, J.; Garbuio, P.; Runge, M.; Cardot, J.C.

    1997-01-01

    The standard radiographical pictures are not able always to bring out the fracture of one of the fist bones. In an early study it was shown that 40% of patients presenting a suspicion of fracture and in which the radio- image was normal, have had a fracture confirmed with quantification by MRI and scintigraphy. The last one does not allow to specify the localization and consequently we developed a code to fusion entirely automatically the radiologic image and the scintigraphic image using no external marker. The code has been installed on a PC and uses the Matlab environment. Starting from the histogram processing the contours are individualized on the interpolated radio- and scinti-images. For matching there are 3 freedom degrees: one of rotation and 2 of translation (in x and y axes). The internal axes of the forearm was chosen to effect the rotation and translation. The forehand thickness, identical for each modality, allows to match properly the images. We have obtained an anatomic image on which the contour and the hyper-fixating zones of the scintigraphy are added. On a set of 100 examinations we observed 38 fractures while the difference between a fracture of the scaphoid and of another fist bone is confirmed in 93% of cases

  7. Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

    Science.gov (United States)

    2016-10-01

    in aqueous hemoglobin solutions. Our current setup is not ideal for accurately calibrating these measurements, but changes in the microscope setup and...in the addition of gaseous oxygen to the physical sample are promising next steps. 15. SUBJECT TERMS Primary blast injury, PBI, hypoxia, ischemia...picosecond optical parametric oscillator (OPO) in order to enhance the parametric amplification and the output power. We worked on the instability

  8. Research and Realization of Medical Image Fusion Based on Three-Dimensional Reconstruction

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new medical image fusion technique is presented. The method is based on three-dimensional reconstruction. After reconstruction, the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure, as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique, three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images, but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter. The research proves this fusion technique is more exact and has no registration, so it is more adapt to arbitrary medical image fusion with different equipments.

  9. Evaluation of multimodality imaging using image fusion with ultrasound tissue elasticity imaging in an experimental animal model.

    Science.gov (United States)

    Paprottka, P M; Zengel, P; Cyran, C C; Ingrisch, M; Nikolaou, K; Reiser, M F; Clevert, D A

    2014-01-01

    To evaluate the ultrasound tissue elasticity imaging by comparison to multimodality imaging using image fusion with Magnetic Resonance Imaging (MRI) and conventional grey scale imaging with additional elasticity-ultrasound in an experimental small-animal-squamous-cell carcinoma-model for the assessment of tissue morphology. Human hypopharynx carcinoma cells were subcutaneously injected into the left flank of 12 female athymic nude rats. After 10 days (SD ± 2) of subcutaneous tumor growth, sonographic grey scale including elasticity imaging and MRI measurements were performed using a high-end ultrasound system and a 3T MR. For image fusion the contrast-enhanced MRI DICOM data set was uploaded in the ultrasonic device which has a magnetic field generator, a linear array transducer (6-15 MHz) and a dedicated software package (GE Logic E9), that can detect transducers by means of a positioning system. Conventional grey scale and elasticity imaging were integrated in the image fusion examination. After successful registration and image fusion the registered MR-images were simultaneously shown with the respective ultrasound sectional plane. Data evaluation was performed using the digitally stored video sequence data sets by two experienced radiologist using a modified Tsukuba Elasticity score. The colors "red and green" are assigned for an area of soft tissue, "blue" indicates hard tissue. In all cases a successful image fusion and plan registration with MRI and ultrasound imaging including grey scale and elasticity imaging was possible. The mean tumor volume based on caliper measurements in 3 dimensions was ~323 mm3. 4/12 rats were evaluated with Score I, 5/12 rates were evaluated with Score II, 3/12 rates were evaluated with Score III. There was a close correlation in the fused MRI with existing small necrosis in the tumor. None of the scored II or III lesions was visible by conventional grey scale. The comparison of ultrasound tissue elasticity imaging enables a

  10. Multi-focus Image Fusion Using Epifluorescence Microscopy for Robust Vascular Segmentation

    OpenAIRE

    Pelapur, Rengarajan; Prasath, Surya; Palaniappan, Kannappan

    2014-01-01

    We are building a computerized image analysis system for Dura Mater vascular network from fluorescence microscopy images. We propose a system that couples a multi-focus image fusion module with a robust adaptive filtering based segmentation. The robust adaptive filtering scheme handles noise without destroying small structures, and the multi focal image fusion considerably improves the overall segmentation quality by integrating information from multiple images. Based on the segmenta...

  11. Fusion

    CERN Document Server

    Mahaffey, James A

    2012-01-01

    As energy problems of the world grow, work toward fusion power continues at a greater pace than ever before. The topic of fusion is one that is often met with the most recognition and interest in the nuclear power arena. Written in clear and jargon-free prose, Fusion explores the big bang of creation to the blackout death of worn-out stars. A brief history of fusion research, beginning with the first tentative theories in the early 20th century, is also discussed, as well as the race for fusion power. This brand-new, full-color resource examines the various programs currently being funded or p

  12. A Geometric Dictionary Learning Based Approach for Fluorescence Spectroscopy Image Fusion

    Directory of Open Access Journals (Sweden)

    Zhiqin Zhu

    2017-02-01

    Full Text Available In recent years, sparse representation approaches have been integrated into multi-focus image fusion methods. The fused images of sparse-representation-based image fusion methods show great performance. Constructing an informative dictionary is a key step for sparsity-based image fusion method. In order to ensure sufficient number of useful bases for sparse representation in the process of informative dictionary construction, image patches from all source images are classified into different groups based on geometric similarities. The key information of each image-patch group is extracted by principle component analysis (PCA to build dictionary. According to the constructed dictionary, image patches are converted to sparse coefficients by simultaneous orthogonal matching pursuit (SOMP algorithm for representing the source multi-focus images. At last the sparse coefficients are fused by Max-L1 fusion rule and inverted to fused image. Due to the limitation of microscope, the fluorescence image cannot be fully focused. The proposed multi-focus image fusion solution is applied to fluorescence imaging area for generating all-in-focus images. The comparison experimentation results confirm the feasibility and effectiveness of the proposed multi-focus image fusion solution.

  13. A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

    Science.gov (United States)

    Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

    2015-11-01

    This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

  14. Seizure Onset Detection based on a Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) System

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2010-01-01

    An automatic Uni- or Multi-modal Inteligent Seizure Acquisition (UISA/MISA) system is highly applicable for onset detection of epileptic seizures based on motion data. The modalities used are surface electromyography (sEMG), acceleration (ACC) and angular velocity (ANG). The new proposed automatic...... algorithm on motion data is extracting features as “log-sum” measures of discrete wavelet components. Classification into the two groups “seizure” versus “nonseizure” is made based on the support vector machine (SVM) algorithm. The algorithm performs with a sensitivity of 91-100%, a median latency of 1...... second and a specificity of 100% on multi-modal data from five healthy subjects simulating seizures. The uni-modal algorithm based on sEMG data from the subjects and patients performs satisfactorily in some cases. As expected, our results clearly show superiority of the multimodal approach, as compared...

  15. Implementation of a multi-modal mobile sensor system for surface and subsurface assessment of roadways

    Science.gov (United States)

    Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

    2015-03-01

    There are more than 4 million miles of roads and 600,000 bridges in the United States alone. On-going investments are required to maintain the physical and operational quality of these assets to ensure public's safety and prosperity of the economy. Planning efficient maintenance and repair (M&R) operations must be armed with a meticulous pavement inspection method that is non-disruptive, is affordable and requires minimum manual effort. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project developed a technology able to cost- effectively monitor the condition of roadway systems to plan for the right repairs, in the right place, at the right time. VOTERS technology consists of an affordable, lightweight package of multi-modal sensor systems including acoustic, optical, electromagnetic, and GPS sensors. Vehicles outfitted with this technology would be capable of collecting information on a variety of pavement-related characteristics at both surface and subsurface levels as they are driven. By correlating the sensors' outputs with the positioning data collected in tight time synchronization, a GIS-based control center attaches a spatial component to all the sensors' measurements and delivers multiple ratings of the pavement every meter. These spatially indexed ratings are then leveraged by VOTERS decision making modules to plan the optimum M&R operations and predict the future budget needs. In 2014, VOTERS inspection results were validated by comparing them to the outputs of recent professionally done condition surveys of a local engineering firm for 300 miles of Massachusetts roads. Success of the VOTERS project portrays rapid, intelligent, and comprehensive evaluation of tomorrow's transportation infrastructure to increase public's safety, vitalize the economy, and deter catastrophic failures.

  16. Use of different exposure metrics for understanding multi-modal travel injury risk

    Directory of Open Access Journals (Sweden)

    S. Ilgin Guler

    2016-08-01

    Full Text Available The objective of this work is to identify characteristics of different metrics of exposure for quantifying multi-modal travel injury risk. First, a discussion on the use of time-based and trip-based metrics for road user exposure to injury risk, considering multiple travel modes, is presented. The main difference between a time-based and trip-based metric is argued to be that a time-based metric reflects the actual duration of time spent on the road exposed to the travel risks. This can be proven to be important when considering multiple modes since different modes typically different speeds and average travel distances. Next, the use of total number of trips, total time traveled, and mode share (time-based or trip-based is considered to compare the injury risk of a given mode at different locations. It is argued that using mode share the safety concept which focuses on absolute numbers can be generalized. Quantitative results are also obtained from combining travel survey data with police collision reports for ten counties in California. The data are aggregated for five modes: (i cars, (ii SUVs, (iii transit riders, (iv bicyclists, and (v pedestrians. These aggregated data are used to compare travel risk of different modes with time-based or trip-based exposure metrics. These quantitative results confirm the initial qualitative discussions. As the penetration of mobile probes for transportation data collection increases, the insights of this study can provide guidance on how to best utilize the added value of such data to better quantify travel injury risk, and improve safety.

  17. Multi-modal distraction. Using technology to combat pain in young children with burn injuries.

    Science.gov (United States)

    Miller, Kate; Rodger, Sylvia; Bucolo, Sam; Greer, Ristan; Kimble, Roy M

    2010-08-01

    The use of non-pharmacological pain management remains adhoc within acute paediatric burns pain management protocols despite ongoing acknowledgement of its role. Advancements in adult based pain services including the integration of virtual reality has been adapted to meet the needs of children in pain, as exemplified by the development of multi-modal distraction (MMD). This easy to use, hand held interactive device uses customized programs designed to inform the child about the procedure he/she is about to experience and to distract the child during dressing changes. (1) To investigate if either MMD procedural preparation (MMD-PP) or distraction (MMD-D) has a greater impact on child pain reduction compared to standard distraction (SD) or hand held video game distraction (VG), (2) to understand the impact of MMD-PP and MMD-D on clinic efficiency by measuring length of treatment across groups, and lastly, (3) to assess the efficacy of distraction techniques over three dressing change procedures. A prospective randomised control trial was completed in a paediatric tertiary hospital Burns Outpatient Clinic. Eighty participants were recruited and studied over their first three dressing changes. Pain was assessed using validated child report, caregiver report, nursing observation and physiological measures. MMD-D and MMD-PP were both shown to significantly relieve reported pain (ppositive effects of both MMD-D and MMD-PP were sustained with subsequent dressing changes. The use of MMD as a preparatory or a distraction tool in an outpatient burns clinic offered superior pain reduction across three dressing changes to children when compared to standard practices or hand held video games. This device has the potential to improve clinic efficiency with reductions in treatment lengths.

  18. Multi-Modal, Multi-Touch Interaction with Maps in Disaster Management Applications

    Directory of Open Access Journals (Sweden)

    V. Paelke

    2012-07-01

    Full Text Available Multi-touch interaction has become popular in recent years and impressive advances in technology have been demonstrated, with the presentation of digital maps as a common presentation scenario. However, most existing systems are really technology demonstrators and have not been designed with real applications in mind. A critical factor in the management of disaster situations is the access to current and reliable data. New sensors and data acquisition platforms (e.g. satellites, UAVs, mobile sensor networks have improved the supply of spatial data tremendously. However, in many cases this data is not well integrated into current crisis management systems and the capabilities to analyze and use it lag behind sensor capabilities. Therefore, it is essential to develop techniques that allow the effective organization, use and management of heterogeneous data from a wide variety of data sources. Standard user interfaces are not well suited to provide this information to crisis managers. Especially in dynamic situations conventional cartographic displays and mouse based interaction techniques fail to address the need to review a situation rapidly and act on it as a team. The development of novel interaction techniques like multi-touch and tangible interaction in combination with large displays provides a promising base technology to provide crisis managers with an adequate overview of the situation and to share relevant information with other stakeholders in a collaborative setting. However, design expertise on the use of such techniques in interfaces for real-world applications is still very sparse. In this paper we report on interdisciplinary research with a user and application centric focus to establish real-world requirements, to design new multi-modal mapping interfaces, and to validate them in disaster management applications. Initial results show that tangible and pen-based interaction are well suited to provide an intuitive and visible way to

  19. Multi-modal neuroimaging of adolescents with non-suicidal self-injury: Amygdala functional connectivity.

    Science.gov (United States)

    Westlund Schreiner, Melinda; Klimes-Dougan, Bonnie; Mueller, Bryon A; Eberly, Lynn E; Reigstad, Kristina M; Carstedt, Patricia A; Thomas, Kathleen M; Hunt, Ruskin H; Lim, Kelvin O; Cullen, Kathryn R

    2017-10-15

    Non-suicidal self-injury (NSSI) is a significant mental health problem among adolescents. Research is needed to clarify the neurobiology of NSSI and identify candidate neurobiological targets for interventions. Based on prior research implicating heightened negative affect and amygdala hyperactivity in NSSI, we pursued a systems approach to characterize amygdala functional connectivity networks during rest (resting-state functional connectivity [RSFC)]) and a task (task functional connectivity [TFC]) in adolescents with NSSI. We examined amygdala networks in female adolescents with NSSI and healthy controls (n = 45) using resting-state fMRI and a negative emotion face-matching fMRI task designed to activate the amygdala. Connectivity analyses included amygdala RSFC, amygdala TFC, and psychophysiological interactions (PPI) between amygdala connectivity and task conditions. Compared to healthy controls, adolescents with NSSI showed atypical amygdala-frontal connectivity during rest and task; greater amygdala RSFC in supplementary motor area (SMA) and dorsal anterior cingulate; and differential amygdala-occipital connectivity between rest and task. After correcting for depression symptoms, amygdala-SMA RSFC abnormalities, among others, remained significant. This study's limitations include its cross-sectional design and its absence of a psychiatric control group. Using a multi-modal approach, we identified widespread amygdala circuitry anomalies in adolescents with NSSI. While deficits in amygdala-frontal connectivity (driven by depression symptoms) replicates prior work in depression, hyperconnectivity between amygdala and SMA (independent of depression symptoms) has not been previously reported. This circuit may represent an important mechanism underlying the link between negative affect and habitual behaviors. These abnormalities may represent intervention targets for adolescents with NSSI. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Design and Implementation of a Multi-Modal Biometric System for Company Access Control

    Directory of Open Access Journals (Sweden)

    Elisabetta Stefani

    2017-05-01

    Full Text Available This paper is about the design, implementation, and deployment of a multi-modal biometric system to grant access to a company structure and to internal zones in the company itself. Face and iris have been chosen as biometric traits. Face is feasible for non-intrusive checking with a minimum cooperation from the subject, while iris supports very accurate recognition procedure at a higher grade of invasivity. The recognition of the face trait is based on the Local Binary Patterns histograms, and the Daughman’s method is implemented for the analysis of the iris data. The recognition process may require either the acquisition of the user’s face only or the serial acquisition of both the user’s face and iris, depending on the confidence level of the decision with respect to the set of security levels and requirements, stated in a formal way in the Service Level Agreement at a negotiation phase. The quality of the decision depends on the setting of proper different thresholds in the decision modules for the two biometric traits. Any time the quality of the decision is not good enough, the system activates proper rules, which ask for new acquisitions (and decisions, possibly with different threshold values, resulting in a system not with a fixed and predefined behaviour, but one which complies with the actual acquisition context. Rules are formalized as deduction rules and grouped together to represent “response behaviors” according to the previous analysis. Therefore, there are different possible working flows, since the actual response of the recognition process depends on the output of the decision making modules that compose the system. Finally, the deployment phase is described, together with the results from the testing, based on the AT&T Face Database and the UBIRIS database.

  1. The effectiveness of multi modal representation text books to improve student's scientific literacy of senior high school students

    Science.gov (United States)

    Zakiya, Hanifah; Sinaga, Parlindungan; Hamidah, Ida

    2017-05-01

    The results of field studies showed the ability of science literacy of students was still low. One root of the problem lies in the books used in learning is not oriented toward science literacy component. This study focused on the effectiveness of the use of textbook-oriented provisioning capability science literacy by using multi modal representation. The text books development method used Design Representational Approach Learning to Write (DRALW). Textbook design which was applied to the topic of "Kinetic Theory of Gases" is implemented in XI grade students of high school learning. Effectiveness is determined by consideration of the effect and the normalized percentage gain value, while the hypothesis was tested using Independent T-test. The results showed that the textbooks which were developed using multi-mode representation science can improve the literacy skills of students. Based on the size of the effect size textbooks developed with representation multi modal was found effective in improving students' science literacy skills. The improvement was occurred in all the competence and knowledge of scientific literacy. The hypothesis testing showed that there was a significant difference on the ability of science literacy between class that uses textbooks with multi modal representation and the class that uses the regular textbook used in schools.

  2. Obstacle traversal and self-righting of bio-inspired robots reveal the physics of multi-modal locomotion

    Science.gov (United States)

    Li, Chen; Fearing, Ronald; Full, Robert

    Most animals move in nature in a variety of locomotor modes. For example, to traverse obstacles like dense vegetation, cockroaches can climb over, push across, reorient their bodies to maneuver through slits, or even transition among these modes forming diverse locomotor pathways; if flipped over, they can also self-right using wings or legs to generate body pitch or roll. By contrast, most locomotion studies have focused on a single mode such as running, walking, or jumping, and robots are still far from capable of life-like, robust, multi-modal locomotion in the real world. Here, we present two recent studies using bio-inspired robots, together with new locomotion energy landscapes derived from locomotor-environment interaction physics, to begin to understand the physics of multi-modal locomotion. (1) Our experiment of a cockroach-inspired legged robot traversing grass-like beam obstacles reveals that, with a terradynamically ``streamlined'' rounded body like that of the insect, robot traversal becomes more probable by accessing locomotor pathways that overcome lower potential energy barriers. (2) Our experiment of a cockroach-inspired self-righting robot further suggests that body vibrations are crucial for exploring locomotion energy landscapes and reaching lower barrier pathways. Finally, we posit that our new framework of locomotion energy landscapes holds promise to better understand and predict multi-modal biological and robotic movement.

  3. Extended depth of field integral imaging using multi-focus fusion

    Science.gov (United States)

    Piao, Yongri; Zhang, Miao; Wang, Xiaohui; Li, Peihua

    2018-03-01

    In this paper, we propose a new method for depth of field extension in integral imaging by realizing the image fusion method on the multi-focus elemental images. In the proposed method, a camera is translated on a 2D grid to take multi-focus elemental images by sweeping the focus plane across the scene. Simply applying an image fusion method on the elemental images holding rich parallax information does not work effectively because registration accuracy of images is the prerequisite for image fusion. To solve this problem an elemental image generalization method is proposed. The aim of this generalization process is to geometrically align the objects in all elemental images so that the correct regions of multi-focus elemental images can be exacted. The all-in focus elemental images are then generated by fusing the generalized elemental images using the block based fusion method. The experimental results demonstrate that the depth of field of synthetic aperture integral imaging system has been extended by realizing the generation method combined with the image fusion on multi-focus elemental images in synthetic aperture integral imaging system.

  4. Effective Multifocus Image Fusion Based on HVS and BP Neural Network

    Directory of Open Access Journals (Sweden)

    Yong Yang

    2014-01-01

    Full Text Available The aim of multifocus image fusion is to fuse the images taken from the same scene with different focuses to obtain a resultant image with all objects in focus. In this paper, a novel multifocus image fusion method based on human visual system (HVS and back propagation (BP neural network is presented. Three features which reflect the clarity of a pixel are firstly extracted and used to train a BP neural network to determine which pixel is clearer. The clearer pixels are then used to construct the initial fused image. Thirdly, the focused regions are detected by measuring the similarity between the source images and the initial fused image followed by morphological opening and closing operations. Finally, the final fused image is obtained by a fusion rule for those focused regions. Experimental results show that the proposed method can provide better performance and outperform several existing popular fusion methods in terms of both objective and subjective evaluations.

  5. Data fusion of Landsat TM and IRS images in forest classification

    Science.gov (United States)

    Guangxing Wang; Markus Holopainen; Eero Lukkarinen

    2000-01-01

    Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...

  6. THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    A. H. Ahrari

    2017-09-01

    Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

  7. Data and image fusion for geometrical cloud characterization

    Energy Technology Data Exchange (ETDEWEB)

    Thorne, L.R.; Buch, K.A.; Sun, Chen-Hui; Diegert, C.

    1997-04-01

    Clouds have a strong influence on the Earth`s climate and therefore on climate change. An important step in improving the accuracy of models that predict global climate change, general circulation models, is improving the parameterization of clouds and cloud-radiation interactions. Improvements in the next generation models will likely include the effect of cloud geometry on the cloud-radiation parameterizations. We have developed and report here methods for characterizing the geometrical features and three-dimensional properties of clouds that could be of significant value in developing these new parameterizations. We developed and report here a means of generating and imaging synthetic clouds which we used to test our characterization algorithms; a method for using Taylor`s hypotheses to infer spatial averages from temporal averages of cloud properties; a computer method for automatically classifying cloud types in an image; and a method for producing numerical three-dimensional renderings of cloud fields based on the fusion of ground-based and satellite images together with meteorological data.

  8. A color fusion method of infrared and low-light-level images based on visual perception

    Science.gov (United States)

    Han, Jing; Yan, Minmin; Zhang, Yi; Bai, Lianfa

    2014-11-01

    The color fusion images can be obtained through the fusion of infrared and low-light-level images, which will contain both the information of the two. The fusion images can help observers to understand the multichannel images comprehensively. However, simple fusion may lose the target information due to inconspicuous targets in long-distance infrared and low-light-level images; and if targets extraction is adopted blindly, the perception of the scene information will be affected seriously. To solve this problem, a new fusion method based on visual perception is proposed in this paper. The extraction of the visual targets ("what" information) and parallel processing mechanism are applied in traditional color fusion methods. The infrared and low-light-level color fusion images are achieved based on efficient typical targets learning. Experimental results show the effectiveness of the proposed method. The fusion images achieved by our algorithm can not only improve the detection rate of targets, but also get rich natural information of the scenes.

  9. An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

    Directory of Open Access Journals (Sweden)

    Guanqiu Qi

    2017-10-01

    Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

  10. Remote Sensing Image Fusion Based on the Combination Grey Absolute Correlation Degree and IHS Transform

    Directory of Open Access Journals (Sweden)

    Hui LIN

    2014-12-01

    Full Text Available An improved fusion algorithm for multi-source remote sensing images with high spatial resolution and multi-spectral capacity is proposed based on traditional IHS fusion and grey correlation analysis. Firstly, grey absolute correlation degree is used to discriminate non-edge pixels and edge pixels in high-spatial resolution images, by which the weight of intensity component is identified in order to combine it with high-spatial resolution image. Therefore, image fusion is achieved using IHS inverse transform. The proposed method is applied to ETM+ multi-spectral images and panchromatic image, and Quickbird’s multi-spectral images and panchromatic image respectively. The experiments prove that the fusion method proposed in the paper can efficiently preserve spectral information of the original multi-spectral images while enhancing spatial resolution greatly. By comparison and analysis, the proposed fusion algorithm is better than traditional IHS fusion and fusion method based on grey correlation analysis and IHS transform.

  11. Semiparametric score level fusion: Gaussian copula approach

    NARCIS (Netherlands)

    Susyanyo, N.; Klaassen, C.A.J.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2015-01-01

    Score level fusion is an appealing method for combining multi-algorithms, multi- representations, and multi-modality biometrics due to its simplicity. Often, scores are assumed to be independent, but even for dependent scores, accord- ing to the Neyman-Pearson lemma, the likelihood ratio is the

  12. Compressed Sensing and Low-Rank Matrix Decomposition in Multisource Images Fusion

    Directory of Open Access Journals (Sweden)

    Kan Ren

    2014-01-01

    Full Text Available We propose a novel super-resolution multisource images fusion scheme via compressive sensing and dictionary learning theory. Under the sparsity prior of images patches and the framework of the compressive sensing theory, the multisource images fusion is reduced to a signal recovery problem from the compressive measurements. Then, a set of multiscale dictionaries are learned from several groups of high-resolution sample image’s patches via a nonlinear optimization algorithm. Moreover, a new linear weights fusion rule is proposed to obtain the high-resolution image. Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to its counterparts.

  13. Clinical assessment of SPECT/CT co-registration image fusion

    International Nuclear Information System (INIS)

    Zhou Wen; Luan Zhaosheng; Peng Yong

    2004-01-01

    Objective: Study the methodology of the SPECT/CT co-registration image fusion, and Assessment the Clinical application value. Method: 172 patients who underwent SPECT/CT image fusion during 2001-2003 were studied, 119 men, 53 women. 51 patients underwent 18FDG image +CT, 26 patients underwent 99m Tc-RBC Liver pool image +CT, 43 patients underwent 99mTc-MDP Bone image +CT, 18 patients underwent 99m Tc-MAA Lung perfusion image +CT. The machine is Millium VG SPECT of GE Company. All patients have been taken three steps image: X-ray survey, X-ray transmission and nuclear emission image (Including planer imaging, SPECT or 18 F-FDG of dual head camera) without changing the position of the patients. We reconstruct the emission image with X-ray map and do reconstruction, 18FDG with COSEM and 99mTc with OSEM. Then combine the transmission image and the reconstructed emission image. We use different process parameters in deferent image methods. The accurate rate of SPECT/CT image fusion were statistics, and compare their accurate with that of single nuclear emission image. Results: The nuclear image which have been reconstructed by X-ray attenuation and OSEM are apparent better than pre-reconstructed. The post-reconstructed emission images have no scatter lines around the organs. The outline between different issues is more clear than before. The validity of All post-reconstructed images is better than pre-reconstructed. SPECT/CT image fusion make localization have worthy bases. 138 patients, the accuracy of SPECT/CT image fusion is 91.3% (126/138), whereas 60(88.2%) were found through SPECT/CT image fusion, There are significant difference between them(P 99m Tc- RBC-SPECT +CT image fusion, but 21 of them were inspected by emission image. In BONE 99m Tc -MDP-SPECT +CT image fusion, 4 patients' removed bone(1-6 months after surgery) and their relay with normal bone had activity, their morphologic and density in CT were different from normal bones. 11 of 20 patients who could

  14. Fusion of remote sensing images based on pyramid decomposition with Baldwinian Clonal Selection Optimization

    Science.gov (United States)

    Jin, Haiyan; Xing, Bei; Wang, Lei; Wang, Yanyan

    2015-11-01

    In this paper, we put forward a novel fusion method for remote sensing images based on the contrast pyramid (CP) using the Baldwinian Clonal Selection Algorithm (BCSA), referred to as CPBCSA. Compared with classical methods based on the transform domain, the method proposed in this paper adopts an improved heuristic evolutionary algorithm, wherein the clonal selection algorithm includes Baldwinian learning. In the process of image fusion, BCSA automatically adjusts the fusion coefficients of different sub-bands decomposed by CP according to the value of the fitness function. BCSA also adaptively controls the optimal search direction of the coefficients and accelerates the convergence rate of the algorithm. Finally, the fusion images are obtained via weighted integration of the optimal fusion coefficients and CP reconstruction. Our experiments show that the proposed method outperforms existing methods in terms of both visual effect and objective evaluation criteria, and the fused images are more suitable for human visual or machine perception.

  15. The establishment of the method of three dimension volumetric fusion of emission and transmission images for PET imaging

    International Nuclear Information System (INIS)

    Zhang Xiangsong; He Zuoxiang

    2004-01-01

    Objective: To establish the method of three dimension volumetric fusion of emission and transmission images for PET imaging. Methods: The volume data of emission and transmission images acquired with Siemens ECAT HR + PET scanner were transferred to PC computer by local area network. The PET volume data were converted into 8 bit byte type, and scaled to the range of 0-255. The data coordinates of emission and transmission images were normalized by three-dimensional coordinate conversion in the same way. The images were fused with the mode of alpha-blending. The accuracy of image fusion was confirmed by its clinical application in 13 cases. Results: The three dimension volumetric fusion of emission and transmission images clearly displayed the silhouette and anatomic configuration in chest, including chest wall, lung, heart, mediastinum, et al. Forty-eight lesions in chest in 13 cases were accurately located by the image fusion. Conclusions: The volume data of emission and transmission images acquired with Siemens ECAT HR + PET scanner have the same data coordinate. The three dimension fusion software can conveniently used for the three dimension volumetric fusion of emission and transmission images, and also can correctly locate the lesions in chest

  16. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  17. Multi-sensor radiation detection, imaging, and fusion

    Energy Technology Data Exchange (ETDEWEB)

    Vetter, Kai [Department of Nuclear Engineering, University of California, Berkeley, CA 94720 (United States); Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

    2016-01-01

    Glenn Knoll was one of the leaders in the field of radiation detection and measurements and shaped this field through his outstanding scientific and technical contributions, as a teacher, his personality, and his textbook. His Radiation Detection and Measurement book guided me in my studies and is now the textbook in my classes in the Department of Nuclear Engineering at UC Berkeley. In the spirit of Glenn, I will provide an overview of our activities at the Berkeley Applied Nuclear Physics program reflecting some of the breadth of radiation detection technologies and their applications ranging from fundamental studies in physics to biomedical imaging and to nuclear security. I will conclude with a discussion of our Berkeley Radwatch and Resilient Communities activities as a result of the events at the Dai-ichi nuclear power plant in Fukushima, Japan more than 4 years ago. - Highlights: • .Electron-tracking based gamma-ray momentum reconstruction. • .3D volumetric and 3D scene fusion gamma-ray imaging. • .Nuclear Street View integrates and associates nuclear radiation features with specific objects in the environment. • Institute for Resilient Communities combines science, education, and communities to minimize impact of disastrous events.

  18. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    International Nuclear Information System (INIS)

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-01-01

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  19. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    Energy Technology Data Exchange (ETDEWEB)

    Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja [Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India); Bao, Le Nguyen [Duytan University, Danang 550000 (Viet Nam); Lay-Ekuakille, Aimé [Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy); Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn [Duytan University, Danang 550000 (Viet Nam); Haiphong University, Haiphong 180000 (Viet Nam)

    2016-07-15

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  20. Ultrasound and PET-CT image fusion for prostate brachytherapy image guidance

    International Nuclear Information System (INIS)

    Hasford, F.

    2015-01-01

    Fusion of medical images between different cross-sectional modalities is widely used, mostly where functional images are fused with anatomical data. Ultrasound has for some time now been the standard imaging technique used for treatment planning of prostate cancer cases. While this approach is laudable and has yielded some positive results, latest developments have been the integration of images from ultrasound and other modalities such as PET-CT to compliment missing properties of ultrasound images. This study has sought to enhance diagnosis and treatment of prostate cancers by developing MATLAB algorithms to fuse ultrasound and PET-CT images. The fused ultrasound-PET-CT image has shown to contain improved quality of information than the individual input images. The fused image has the property of reduced uncertainty, increased reliability, robust system performance, and compact representation of information. The objective of co-registering the ultrasound and PET-CT images was achieved by conducting performance evaluation of the ultrasound and PET-CT imaging systems, developing image contrast enhancement algorithm, developing MATLAB image fusion algorithm, and assessing accuracy of the fusion algorithm. Performance evaluation of the ultrasound brachytherapy system produced satisfactory results in accordance with set tolerances as recommended by AAPM TG 128. Using an ultrasound brachytherapy quality assurance phantom, average axial distance measurement of 10.11 ± 0.11 mm was estimated. Average lateral distance measurements of 10.08 ± 0.07 mm, 20.01 ± 0.06 mm, 29.89 ± 0.03 mm and 39.84 ± 0.37 mm were estimated for the inter-target distances corresponding to 10 mm, 20 mm, 30 mm and 40 mm respectively. Volume accuracy assessment produced measurements of 3.97 cm 3 , 8.86 cm 3 and 20.11 cm 3 for known standard volumes of 4 cm 3 , 9 cm 3 and 20 cm 3 respectively. Depth of penetration assessment of the ultrasound system produced an estimate of 5.37 ± 0.02 cm

  1. Two-dimensional fusion imaging of planar bone scintigraphy and radiographs in patients with clinical scaphoid fracture: an imaging study

    DEFF Research Database (Denmark)

    Henriksen, Otto Mølby; Lonsdale, Markus Georg; Jensen, T D

    2009-01-01

    . Bone scintigraphy is highly sensitive for the detection of fractures, but exact localization of scintigraphic lesions may be difficult and can negatively affect diagnostic accuracy. PURPOSE: To investigate the influence of image fusion of planar bone scintigraphy and radiographs on image interpretation......BACKGROUND: Although magnetic resonance imaging (MRI) is now considered the gold standard in second-line imaging of patients with suspected scaphoid fracture and negative radiographs, bone scintigraphy can be used in patients with pacemakers, metallic implants, or other contraindications to MRI....... CONCLUSION: Image fusion of planar bone scintigrams and radiographs has a significant influence on image interpretation and increases both diagnostic confidence and interobserver agreement....

  2. Pulmonary function-morphologic relationships assessed by SPECT-CT fusion images

    International Nuclear Information System (INIS)

    Suga, Kazuyoshi

    2012-01-01

    Pulmonary single photon emission computed tomography-computed tomography (SPECT-CT) fusion images provide objective and comprehensive assessment of pulmonary function and morphology relationships at cross-sectional lungs. This article reviewed the noteworthy findings of lung pathophysiology in wide-spectral lung disorders, which have been revealed on SPECT-CT fusion images in 8 years of experience. The fusion images confirmed the fundamental pathophysiologic appearance of lung low CT attenuation caused by airway obstruction-induced hypoxic vasoconstriction and that caused by direct pulmonary arterial obstruction as in acute pulmonary thromboembolism (PTE). The fusion images showed better correlation of lung perfusion distribution with lung CT attenuation changes at lung mosaic CT attenuation (MCA) compared with regional ventilation in the wide-spectral lung disorders, indicating that lung heterogeneous perfusion distribution may be a dominant mechanism of MCA on CT. SPECT-CT angiography fusion images revealed occasional dissociation between lung perfusion defects and intravascular clots in acute PTE, indicating the importance of assessment of actual effect of intravascular colts on peripheral lung perfusion. Perfusion SPECT-CT fusion images revealed the characteristic and preferential location of pulmonary infarction in acute PTE. The fusion images showed occasional unexpected perfusion defects in normal lung areas on CT in chronic obstructive pulmonary diseases and interstitial lung diseases, indicating the ability of perfusion SPECT superior to CT for detection of mild lesions in these disorders. The fusion images showed frequent ''steal phenomenon''-induced perfusion defects extending to the surrounding normal lung of arteriovenous fistulas and those at normal lungs on CT in hepatopulmonary syndrome. Comprehensive assessment of lung function-CT morphology on fusion images will lead to more profound understanding of lung pathophysiology in wide-spectral lung

  3. Percutaneous Thermal Ablation with Ultrasound Guidance. Fusion Imaging Guidance to Improve Conspicuity of Liver Metastasis

    Energy Technology Data Exchange (ETDEWEB)

    Hakime, Antoine, E-mail: thakime@yahoo.com; Yevich, Steven; Tselikas, Lambros; Deschamps, Frederic [Gustave Roussy - Cancer Campus, Interventional Radiology Department (France); Petrover, David [Imagerie Médicale Paris Centre, IMPC (France); Baere, Thierry De [Gustave Roussy - Cancer Campus, Interventional Radiology Department (France)

    2017-05-15

    PurposeTo assess whether fusion imaging-guided percutaneous microwave ablation (MWA) can improve visibility and targeting of liver metastasis that were deemed inconspicuous on ultrasound (US).Materials and MethodsMWA of liver metastasis not judged conspicuous enough on US was performed under CT/US fusion imaging guidance. The conspicuity before and after the fusion imaging was graded on a five-point scale, and significance was assessed by Wilcoxon test. Technical success, procedure time, and procedure-related complications were evaluated.ResultsA total of 35 patients with 40 liver metastases (mean size 1.3 ± 0.4 cm) were enrolled. Image fusion improved conspicuity sufficiently to allow fusion-targeted MWA in 33 patients. The time required for image fusion processing and tumors’ identification averaged 10 ± 2.1 min (range 5–14). Initial conspicuity on US by inclusion criteria was 1.2 ± 0.4 (range 0–2), while conspicuity after localization on fusion imaging was 3.5 ± 1 (range 1–5, p < 0.001). Technical success rate was 83% (33/40) in intention-to-treat analysis and 100% in analysis of treated tumors. There were no major procedure-related complications.ConclusionsFusion imaging broadens the scope of US-guided MWA to metastasis lacking adequate conspicuity on conventional US. Fusion imaging is an effective tool to increase the conspicuity of liver metastases that were initially deemed non visualizable on conventional US imaging.

  4. Functional and morphological imaging of thyroid associated eye disease. Data evaluation by means of image fusion

    International Nuclear Information System (INIS)

    Kainz, H.

    2002-08-01

    Aim: to recognize the structures that show an uptake of a 99mTc-labeled octreotide tracer within the orbit and head in patients with thyroid associated eye disease relying on image fusion. Methods: A series of 18 patients presenting the signs and symptoms of thyroid associated eye disease were studied. Functional imaging was done with 99mTc-HYNIC-TOC, a newly in-house developed tracer. Both whole body as well as single photon emission tomographies (SPECT) of the head were obtained in each patient. Parallel to nuclear medicine imaging, morphological imaging was done using either computed tomography or magnetic resonance. Results: By means of image fusion farther more information on the functional status of the patients was obtained. All areas showing an uptake could be anatomically identified, revealing a series of organs that had not yet been consideren in this disease. The organs presenting tracer uptake showed characteristic forms as described below: - eye glass sign: lacrimal gland and lacrimal ducts - scissors sign: eye muscles, rectus sup. and inf. - arch on CT: muscle displacement - Omega sign: tonsils and salivary glands - W- sign: tonsils and salivary glands Conclusions: By means of image fusion it was possible to recognize that a series of organs of the neck and head express somatostatin receptors. We interpret these results as a sign of inflammation of the lacrimal glands, the lacrimal ducts, the cervical lymphatics, the anterior portions of the extra ocular eye muscles and muscles of the posterior cervical region. Somatostatin uptake in these sturctures reflects the prescence of specific receptors which reflect the immuno regulating function of the peptide. (author)

  5. Image fusion using MIM software via picture archiving and communication system

    International Nuclear Information System (INIS)

    Gu Zhaoxiang; Jiang Maosong

    2001-01-01

    The preliminary studies of the multimodality image registration and fusion were performed using an image fusion software and a picture archiving and communication system (PACS) to explore the methodology. Original image voluminal data were acquired with a CT scanner, MR and dual-head coincidence SPECT, respectively. The data sets from all imaging devices were queried, retrieved, transferred and accessed via DICOM PACS. The image fusion was performed at the SPECT ICON work-station, where the MIM (Medical Image Merge) fusion software was installed. The images were created by re-slicing original volume on the fly. The image volumes were aligned by translation and rotation of these view ports with respect to the original volume orientation. The transparency factor and contrast were adjusted in order that both volumes can be visualized in the merged images. The image volume data of CT, MR and nuclear medicine were transferred, accessed and loaded via PACS successfully. The perfect fused images of chest CT/ 18 F-FDG and brain MR/SPECT were obtained. These results showed that image fusion technique using PACS was feasible and practical. Further experimentation and larger validation studies were needed to explore the full potential of the clinical use

  6. Development of a novel fusion imaging technique in the diagnosis of hepatobiliary-pancreatic lesions

    International Nuclear Information System (INIS)

    Soga, Koichi; Ochiai, Jun; Miyajima, Takashi; Kassai, Kyoichi; Itani, Kenji; Yagi, Nobuaki; Naito, Yuji

    2013-01-01

    Multi-row detector computed tomography (MDCT) and magnetic resonance cholangiopancreatography (MRCP) play an important role in the imaging diagnosis of hepatobiliary-pancreatic lesions. Here we investigated whether unifying the MDCT and MRCP images onto the same screen using fusion imaging could overcome the limitations of each technique, while still maintaining their benefits. Moreover, because reports of fusion imaging using MDCT and MRCP are rare, we assessed the benefits and limitations of this method for its potential application in a clinical setting. The patient group included 9 men and 11 women. Among the 20 patients, the final diagnoses were as follows: 10 intraductal papillary mucinous neoplasms, 5 biliary system carcinomas, 1 pancreatic adenocarcinoma and 5 non-neoplastic lesions. After transmitting the Digital Imaging and Communication in Medicine data of the MDCT and MRCP images to a workstation, we performed a 3-D organisation of both sets of images using volume rendering for the image fusion. Fusion imaging enabled clear identification of the spatial relationship between a hepatobiliary-pancreatic lesion and the solid viscera and/or vessels. Further, this method facilitated the determination of the relationship between the anatomical position of the lesion and its surroundings more easily than either MDCT or MRCP alone. Fusion imaging is an easy technique to perform and may be a useful tool for planning treatment strategies and for examining pathological changes in hepatobiliary-pancreatic lesions. Additionally, the ease of obtaining the 3-D images suggests the possibility of using these images to plan intervention strategies.

  7. Adaptive polarization image fusion based on regional energy dynamic weighted average

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yong-qiang; PAN Quan; ZHANG Hong-cai

    2005-01-01

    According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations,most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

  8. Fusion method of SAR and optical images for urban object extraction

    Science.gov (United States)

    Jia, Yonghong; Blum, Rick S.; Li, Fangfang

    2007-11-01

    A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

  9. Fusion of SPECT/TC images: Usefulness and benefits in degenerative spinal cord pathology

    International Nuclear Information System (INIS)

    Ocampo, Monica; Ucros, Gonzalo; Bermudez, Sonia; Morillo, Anibal; Rodriguez, Andres

    2005-01-01

    The objectives are to compare CT and SPECT bone scintigraphy evaluated independently with SPECT-CT fusion images in patients with known degenerative spinal pathology. To demonstrate the clinical usefulness of CT and SPECT fusion images. Materials and methods: Thirty-one patients with suspected degenerative spinal disease were evaluated with thin-slice, non-angled helical CT and bone scintigrams with single photon emission computed tomography (SPECT), both with multiplanar reconstructions within a 24-hour period After independent evaluation by a nuclear medicine specialist and a radiologist, multimodality image fusion software was used to merge the CT and SPECT studies and a final consensus interpretation of the combined images was obtained. Results: Thirty-two SPECT bone scintigraphy images, helical CT studies and SPECT-CT fusion images were obtained for 31 patients with degenerative spinal disease. The results of the bone scintigraphy and CT scans were in agreement in 17 pairs of studies (53.12%). In these studies image fusion did not provide additional information on the location or extension of the lesions. In 11 of the study pairs (34.2%), the information obtained was not in agreement between scintigraphy and CT studies: CT images demonstrated several abnormalities, whereas the SPECT images showed only one dominant lesion, or the SPECT images did not provide enough information for anatomical localization. In these cases image fusion helped establish the precise localization of the most clinically significant lesion, which matched the lesion with the greatest uptake. In 4 studies (12.5%) the CT and SPECT images were not in agreement: CT and SPECT images showed different information (normal scintigraphy, abnormal CT), thus leading to inconclusive fusion images. Conclusion: The use of CT-SPECT fusion images in degenerative spinal disease allows for the integration of anatomic detail with physiologic and functional information. CT-SPECT fusion improves the

  10. Fusion of infrared and visible images based on BEMD and NSDFB

    Science.gov (United States)

    Zhu, Pan; Huang, Zhanhua; Lei, Hai

    2016-07-01

    This paper presents a new fusion method based on the adaptive multi-scale decomposition of bidimensional empirical mode decomposition (BEMD) and the flexible directional expansion of nonsubsampled directional filter banks (NSDFB) for visible-infrared images. Compared with conventional multi-scale fusion methods, BEMD is non-parametric and completely data-driven, which is relatively more suitable for non-linear signals decomposition and fusion. NSDFB can provide direction filtering on the decomposition levels to capture more geometrical structure of the source images effectively. In our fusion framework, the entropies of the two patterns of source images are firstly calculated and the residue of the image whose entropy is larger is extracted to make it highly relevant with the other source image. Then, the residue and the other source image are decomposed into low-frequency sub-bands and a sequence of high-frequency directional sub-bands in different scales by using BEMD and NSDFB. In this fusion scheme, two relevant fusion rules are used in low-frequency sub-bands and high-frequency directional sub-bands, respectively. Finally, the fused image is obtained by applying corresponding inverse transform. Experimental results indicate that the proposed fusion algorithm can obtain state-of-the-art performance for visible-infrared images fusion in both aspects of objective assessment and subjective visual quality even for the source images obtained in different conditions. Furthermore, the fused results have high contrast, remarkable target information and rich details information that are more suitable for human visual characteristics or machine perception.

  11. Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

    Directory of Open Access Journals (Sweden)

    Yong Yang

    2014-01-01

    Full Text Available Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT, the fast discrete curvelet transform (FDCT, and the dual tree complex wavelet transform (DTCWT based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

  12. Quality Assurance of Serial 3D Image Registration, Fusion, and Segmentation

    International Nuclear Information System (INIS)

    Sharpe, Michael; Brock, Kristy K.

    2008-01-01

    Radiotherapy relies on images to plan, guide, and assess treatment. Image registration, fusion, and segmentation are integral to these processes; specifically for aiding anatomic delineation, assessing organ motion, and aligning targets with treatment beams in image-guided radiation therapy (IGRT). Future developments in image registration will also improve estimations of the actual dose delivered and quantitative assessment in patient follow-up exams. This article summarizes common and emerging technologies and reviews the role of image registration, fusion, and segmentation in radiotherapy processes. The current quality assurance practices are summarized, and implications for clinical procedures are discussed

  13. Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

    Science.gov (United States)

    Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

    2016-01-01

    Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.

  14. A multi-modal training programme to improve physical activity, physical fitness and perceived physical ability in obese children.

    Science.gov (United States)

    Morano, Milena; Colella, Dario; Rutigliano, Irene; Fiore, Pietro; Pettoello-Mantovani, Massimo; Campanozzi, Angelo

    2014-01-01

    Actual and perceived physical abilities are important correlates of physical activity (PA) and fitness, but little research has explored these relationships over time in obese children. This study was designed: (a) to assess the feasibility of a multi-modal training programme promoting changes in PA, fundamental motor skills and real and perceived physical abilities of obese children; and (b) to explore cross-sectional and longitudinal relationships between real and perceived physical competence in boys and girls. Forty-one participants (9.2 ± 1.2 years) were assessed before and after an 8-month intervention with respect to body composition, physical fitness, self-reported PA and perceived physical ability. After treatment, obese children reported improvements in the body mass index, PA levels, gross motor performance and actual and perceived physical abilities. Real and perceived physical competence was correlated in boys, but not in girls. Results indicate that a multi-modal programme focused on actual and perceived physical competence as associated with the gradual increase in the volume of activity might be an effective strategy to improve adherence of the participants and to increase the lifelong exercise skills of obese children.

  15. Medical images fusion for application in treatment planning systems in radiotherapy

    International Nuclear Information System (INIS)

    Ros, Renato Assenci

    2006-01-01

    Software for medical images fusion was developed for utilization in CAT3D radiotherapy and MNPS radiosurgery treatment planning systems. A mutual information maximization methodology was used to make the image registration of different modalities by measure of the statistical dependence between the voxels pairs. The alignment by references points makes an initial approximation to the non linear optimization process by downhill simplex method for estimation of the joint histogram. The coordinates transformation function use a trilinear interpolation and search for the global maximum value in a 6 dimensional space, with 3 degree of freedom for translation and 3 degree of freedom for rotation, by making use of the rigid body model. This method was evaluated with CT, MR and PET images from Vanderbilt University database to verify its accuracy by comparison of transformation coordinates of each images fusion with gold-standard values. The median of images alignment error values was 1.6 mm for CT-MR fusion and 3.5 mm for PET-MR fusion, with gold-standard accuracy estimated as 0.4 mm for CT-MR fusion and 1.7 mm for PET-MR fusion. The maximum error values were 5.3 mm for CT-MR fusion and 7.4 mm for PET-MR fusion, and 99.1% of alignment errors were images subvoxels values. The mean computing time was 24 s. The software was successfully finished and implemented in 59 radiotherapy routine services, of which 42 are in Brazil and 17 are in Latin America. This method does not have limitation about different resolutions from images, pixels sizes and slice thickness. Besides, the alignment may be accomplished by axial, coronal or sagittal images. (author)

  16. Gamma-Ray imaging for nuclear security and safety: Towards 3-D gamma-ray vision

    Science.gov (United States)

    Vetter, Kai; Barnowksi, Ross; Haefner, Andrew; Joshi, Tenzing H. Y.; Pavlovsky, Ryan; Quiter, Brian J.

    2018-01-01

    The development of portable gamma-ray imaging instruments in combination with the recent advances in sensor and related computer vision technologies enable unprecedented capabilities in the detection, localization, and mapping of radiological and nuclear materials in complex environments relevant for nuclear security and safety. Though multi-modal imaging has been established in medicine and biomedical imaging for some time, the potential of multi-modal data fusion for radiological localization and mapping problems in complex indoor and outdoor environments remains to be explored in detail. In contrast to the well-defined settings in medical or biological imaging associated with small field-of-view and well-constrained extension of the radiation field, in many radiological search and mapping scenarios, the radiation fields are not constrained and objects and sources are not necessarily known prior to the measurement. The ability to fuse radiological with contextual or scene data in three dimensions, in analog to radiological and functional imaging with anatomical fusion in medicine, provides new capabilities enhancing image clarity, context, quantitative estimates, and visualization of the data products. We have developed new means to register and fuse gamma-ray imaging with contextual data from portable or moving platforms. These developments enhance detection and mapping capabilities as well as provide unprecedented visualization of complex radiation fields, moving us one step closer to the realization of gamma-ray vision in three dimensions.

  17. Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

    Science.gov (United States)

    Reena Benjamin, J; Jayasree, T

    2018-02-01

    In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

  18. Improved detection probability of low level light and infrared image fusion system

    Science.gov (United States)

    Luo, Yuxiang; Fu, Rongguo; Zhang, Junju; Wang, Wencong; Chang, Benkang

    2018-02-01

    Low level light(LLL) image contains rich information on environment details, but is easily affected by the weather. In the case of smoke, rain, cloud or fog, much target information will lose. Infrared image, which is from the radiation produced by the object itself, can be "active" to obtain the target information in the scene. However, the image contrast and resolution is bad, the ability of the acquisition of target details is very poor, and the imaging mode does not conform to the human visual habit. The fusion of LLL and infrared image can make up for the deficiency of each sensor and give play to the advantages of single sensor. At first, we show the hardware design of fusion circuit. Then, through the recognition probability calculation of the target(one person) and the background image(trees), we find that the trees detection probability of LLL image is higher than that of the infrared image, and the person detection probability of the infrared image is obviously higher than that of LLL image. The detection probability of fusion image for one person and trees is higher than that of single detector. Therefore, image fusion can significantly enlarge recognition probability and improve detection efficiency.

  19. The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna

    NARCIS (Netherlands)

    Weimar Acerbi, F.; Clevers, J.G.P.W.; Schaepman, M.E.

    2006-01-01

    Multi-sensor image fusion using the wavelet approach provides a conceptual framework for the improvement of the spatial resolution with minimal distortion of the spectral content of the source image. This paper assesses whether images with a large ratio of spatial resolution can be fused, and

  20. Image Fusion of CT and MR with Sparse Representation in NSST Domain

    Directory of Open Access Journals (Sweden)

    Chenhui Qiu

    2017-01-01

    Full Text Available Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR- based approach. And the dynamic group sparsity recovery (DGSR algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

  1. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Directory of Open Access Journals (Sweden)

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  2. An object-oriented framework for medical image registration, fusion, and visualization.

    Science.gov (United States)

    Zhu, Yang-Ming; Cochoff, Steven M

    2006-06-01

    An object-oriented framework for image registration, fusion, and visualization was developed based on the classic model-view-controller paradigm. The framework employs many design patterns to facilitate legacy code reuse, manage software complexity, and enhance the maintainability and portability of the framework. Three sample applications built a-top of this framework are illustrated to show the effectiveness of this framework: the first one is for volume image grouping and re-sampling, the second one is for 2D registration and fusion, and the last one is for visualization of single images as well as registered volume images.

  3. Multi Modality Brain Mapping System (MBMS) Using Artificial Intelligence and Pattern Recognition

    Science.gov (United States)

    Kateb, Babak (Inventor); Nikzad, Shouleh (Inventor)

    2017-01-01

    A Multimodality Brain Mapping System (MBMS), comprising one or more scopes (e.g., microscopes or endoscopes) coupled to one or more processors, wherein the one or more processors obtain training data from one or more first images and/or first data, wherein one or more abnormal regions and one or more normal regions are identified; receive a second image captured by one or more of the scopes at a later time than the one or more first images and/or first data and/or captured using a different imaging technique; and generate, using machine learning trained using the training data, one or more viewable indicators identifying one or abnormalities in the second image, wherein the one or more viewable indicators are generated in real time as the second image is formed. One or more of the scopes display the one or more viewable indicators on the second image.

  4. Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Naveed ur Rehman

    2015-05-01

    Full Text Available A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA, discrete wavelet transform (DWT and non-subsampled contourlet transform (NCT. A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

  5. Multi-focus image fusion with the all convolutional neural network

    Science.gov (United States)

    Du, Chao-ben; Gao, She-sheng

    2018-01-01

    A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network (CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN (ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.

  6. Dual Channel Pulse Coupled Neural Network Algorithm for Fusion of Multimodality Brain Images with Quality Analysis

    Directory of Open Access Journals (Sweden)

    Kavitha SRINIVASAN

    2014-09-01

    Full Text Available Background: In the review of medical imaging techniques, an important fact that emerged is that radiologists and physicians still are in a need of high-resolution medical images with complementary information from different modalities to ensure efficient analysis. This requirement should have been sorted out using fusion techniques with the fused image being used in image-guided surgery, image-guided radiotherapy and non-invasive diagnosis. Aim: This paper focuses on Dual Channel Pulse Coupled Neural Network (PCNN Algorithm for fusion of multimodality brain images and the fused image is further analyzed using subjective (human perception and objective (statistical measures for the quality analysis. Material and Methods: The modalities used in fusion are CT, MRI with subtypes T1/T2/PD/GAD, PET and SPECT, since the information from each modality is complementary to one another. The objective measures selected for evaluation of fused image were: Information Entropy (IE - image quality, Mutual Information (MI – deviation in fused to the source images and Signal to Noise Ratio (SNR – noise level, for analysis. Eight sets of brain images with different modalities (T2 with T1, T2 with CT, PD with T2, PD with GAD, T2 with GAD, T2 with SPECT-Tc, T2 with SPECT-Ti, T2 with PET are chosen for experimental purpose and the proposed technique is compared with existing fusion methods such as the Average method, the Contrast pyramid, the Shift Invariant Discrete Wavelet Transform (SIDWT with Harr and the Morphological pyramid, using the selected measures to ascertain relative performance. Results: The IE value and SNR value of the fused image derived from dual channel PCNN is higher than other fusion methods, shows that the quality is better with less noise. Conclusion: The fused image resulting from the proposed method retains the contrast, shape and texture as in source images without false information or information loss.

  7. Data Fusion and Fuzzy Clustering on Ratio Images for Change Detection in Synthetic Aperture Radar Images

    Directory of Open Access Journals (Sweden)

    Wenping Ma

    2014-01-01

    Full Text Available The unsupervised approach to change detection via synthetic aperture radar (SAR images becomes more and more popular. The three-step procedure is the most widely used procedure, but it does not work well with the Yellow River Estuary dataset obtained by two synthetic aperture radars. The difference of the two radars in imaging techniques causes severe noise, which seriously affects the difference images generated by a single change detector in step two, producing the difference image. To deal with problem, we propose a change detector to fuse the log-ratio (LR and the mean-ratio (MR images by a context independent variable behavior (CIVB operator and can utilize the complement information in two ratio images. In order to validate the effectiveness of the proposed change detector, the change detector will be compared with three other change detectors, namely, the log-ratio (LR, mean-ratio (MR, and the wavelet-fusion (WR operator, to deal with three datasets with different characteristics. The four operators are applied not only in a widely used three-step procedure but also in a new approach. The experiments show that the false alarms and overall errors of change detection are greatly reduced, and the kappa and KCC are improved a lot. And its superiority can also be observed visually.

  8. Analyzer-based imaging of spinal fusion in an animal model

    International Nuclear Information System (INIS)

    Kelly, M E; Beavis, R C; Allen, L A; Fiorella, David; Schueltke, E; Juurlink, B H; Chapman, L D; Zhong, Z

    2008-01-01

    Analyzer-based imaging (ABI) utilizes synchrotron radiation sources to create collimated monochromatic x-rays. In addition to x-ray absorption, this technique uses refraction and scatter rejection to create images. ABI provides dramatically improved contrast over standard imaging techniques. Twenty-one adult male Wistar rats were divided into four experimental groups to undergo the following interventions: (1) non-injured control, (2) decortication alone, (3) decortication with iliac crest bone grafting and (4) decortication with iliac crest bone grafting and interspinous wiring. Surgical procedures were performed at the L5-6 level. Animals were killed at 2, 4 and 6 weeks after the intervention and the spine muscle blocks were excised. Specimens were assessed for the presence of fusion by (1) manual testing, (2) conventional absorption radiography and (3) ABI. ABI showed no evidence of bone fusion in groups 1 and 2 and showed solid or possibly solid fusion in subjects from groups 3 and 4 at 6 weeks. Metal artifacts were not present in any of the ABI images. Conventional absorption radiographs did not provide diagnostic quality imaging of either the graft material or fusion masses in any of the specimens in any of the groups. Synchrotron-based ABI represents a novel imaging technique which can be used to assess spinal fusion in a small animal model. ABI produces superior image quality when compared to conventional radiographs

  9. Analyzer-based imaging of spinal fusion in an animal model

    Science.gov (United States)

    Kelly, M. E.; Beavis, R. C.; Fiorella, David; Schültke, E.; Allen, L. A.; Juurlink, B. H.; Zhong, Z.; Chapman, L. D.

    2008-05-01

    Analyzer-based imaging (ABI) utilizes synchrotron radiation sources to create collimated monochromatic x-rays. In addition to x-ray absorption, this technique uses refraction and scatter rejection to create images. ABI provides dramatically improved contrast over standard imaging techniques. Twenty-one adult male Wistar rats were divided into four experimental groups to undergo the following interventions: (1) non-injured control, (2) decortication alone, (3) decortication with iliac crest bone grafting and (4) decortication with iliac crest bone grafting and interspinous wiring. Surgical procedures were performed at the L5-6 level. Animals were killed at 2, 4 and 6 weeks after the intervention and the spine muscle blocks were excised. Specimens were assessed for the presence of fusion by (1) manual testing, (2) conventional absorption radiography and (3) ABI. ABI showed no evidence of bone fusion in groups 1 and 2 and showed solid or possibly solid fusion in subjects from groups 3 and 4 at 6 weeks. Metal artifacts were not present in any of the ABI images. Conventional absorption radiographs did not provide diagnostic quality imaging of either the graft material or fusion masses in any of the specimens in any of the groups. Synchrotron-based ABI represents a novel imaging technique which can be used to assess spinal fusion in a small animal model. ABI produces superior image quality when compared to conventional radiographs.

  10. A Remote Sensing Image Fusion Method based on adaptive dictionary learning

    Science.gov (United States)

    He, Tongdi; Che, Zongxi

    2018-01-01

    This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

  11. Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain Segmentation

    OpenAIRE

    Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H.; Shen, Dinggang

    2013-01-01

    Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6–8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significan...

  12. Evaluation of multi-modality CT-MRI-SPECT registration tools for radiotherapy treatment planning purposes

    International Nuclear Information System (INIS)

    Bianchini, S.; Alfonso, R.; Castillo, J.; Coca, M.; Torres, L.

    2013-01-01

    A qualitative and quantitative comparison of registration CT-CT, CT-MR and CT-SPECT performed by the different software and algorithms studies is presented. Only two studied software were full DICOM RT compatible while accepting DICOM images in any layout. Quantitative results of fiducial displacement errors were calculated for all software and available registration methods. The presented methodology demonstrated being effective for assessing the quality of studied image registration tools in the radiotherapy planning context, provided the images are free of significant geometric deformation. When implementing this methodology in real patients, the use of immobilization devices, such as thermoplastic masks, is recommended for enhanced quality of image registration. (Author)

  13. Solving the problem of imaging resolution: stochastic multi-scale image fusion

    Science.gov (United States)

    Karsanina, Marina; Mallants, Dirk; Gilyazetdinova, Dina; Gerke, Kiril

    2016-04-01

    rocks) and RFBR grant 15-34-20989 (data fusion). References: 1. Karsanina, M.V., Gerke, K.M., Skvortsova, E.B., Mallants, D. Universal spatial correlation functions for describing and reconstructing soil microstructure. PLoS ONE 10(5): e0126515 (2015). 2. Gerke, K.M., Karsanina, M.V., Mallants, D. Universal stochastic multiscale image fusion: an example application for shale rock. Scientific Reports 5: 15880 (2015). 3. Gerke, K.M., Karsanina, M.V., Vasilyev, R.V., Mallants, D. Improving pattern reconstruction using correlation functions computed in directions. Europhys. Lett. 106(6), 66002 (2014). 4. Gerke, K.M., Karsanina, M.V. Improving stochastic reconstructions by weighting correlation functions in an objective function. Europhys. Lett. 111, 56002 (2015).

  14. Modeling most likely pathways for smuggling radioactive and special nuclear materials on a worldwide multi-modal transportation network

    Energy Technology Data Exchange (ETDEWEB)

    Saeger, Kevin J [Los Alamos National Laboratory; Cuellar, Leticia [Los Alamos National Laboratory

    2010-10-28

    Nuclear weapons proliferation is an existing and growing worldwide problem. To help with devising strategies and supporting decisions to interdict the transport of nuclear material, we developed the Pathway Analysis, Threat Response and Interdiction Options Tool (PATRIOT) that provides an analytical approach for evaluating the probability that an adversary smuggling radioactive or special nuclear material will be detected during transit. We incorporate a global, multi-modal transportation network, explicit representation of designed and serendipitous detection opportunities, and multiple threat devices, material types, and shielding levels. This paper presents the general structure of PATRIOT, all focuses on the theoretical framework used to model the reliabilities of all network components that are used to predict the most likely pathways to the target.

  15. LapTrain: multi-modality training curriculum for laparoscopic cholecystectomy-results of a randomized controlled trial.

    Science.gov (United States)

    Kowalewski, K F; Garrow, C R; Proctor, T; Preukschas, A A; Friedrich, M; Müller, P C; Kenngott, H G; Fischer, L; Müller-Stich, B P; Nickel, F

    2018-02-12

    Multiple training modalities for laparoscopy have different advantages, but little research has been conducted on the benefit of a training program that includes multiple different training methods compared to one method only. This study aimed to evaluate benefits of a combined multi-modality training program for surgical residents. Laparoscopic cholecystectomy (LC) was performed on a porcine liver as the pre-test. Randomization was stratified for experience to the multi-modality Training group (12 h of training on Virtual Reality (VR) and box trainer) or Control group (no training). The post-test consisted of a VR LC and porcine LC. Performance was rated with the Global Operative Assessment of Laparoscopic Skills (GOALS) score by blinded experts. Training (n = 33) and Control (n = 31) were similar in the pre-test (GOALS: 13.7 ± 3.4 vs. 14.7 ± 2.6; p = 0.198; operation time 57.0 ± 18.1 vs. 63.4 ± 17.5 min; p = 0.191). In the post-test porcine LC, Training had improved GOALS scores (+ 2.84 ± 2.85 points, p < 0.001), while Control did not (+ 0.55 ± 2.34 points, p = 0.154). Operation time in the post-test was shorter for Training vs. Control (40.0 ± 17.0 vs. 55.0 ± 22.2 min; p = 0.012). Junior residents improved GOALS scores to the level of senior residents (pre-test: 13.7 ± 2.7 vs. 18.3 ± 2.9; p = 0.010; post-test: 15.5 ± 3.4 vs. 18.8 ± 3.8; p = 0.120) but senior residents remained faster (50.1 ± 20.6 vs. 25.0 ± 1.9 min; p < 0.001). No differences were found between groups on the post-test VR trainer. Structured multi-modality training is beneficial for novices to improve basics and overcome the initial learning curve in laparoscopy as well as to decrease operation time for LCs in different stages of experience. Future studies should evaluate multi-modality training in comparison with single modalities. German Clinical Trials Register DRKS00011040.

  16. A multi-modality tracking, navigation and calibration for a flexible robotic drill system for total hip arthroplasty.

    Science.gov (United States)

    Ahmad Fuad, Ahmad Nazmi Bin; Deep, Kamal; Yao, Wei

    2018-02-01

    This paper presents a novel multi-modality tracking and navigation system that provides a unique capability to guild a flexible drill tip inside the bone with accurate curved tunnelling. As the flexible drill tip cannot be tracked optically inside the bone, this research focuses on developing a hybrid tracking and navigation system for tracking a flexible drill tip by using both optical and kinematic tracking. The tracking information is used to guide the THA (total hip arthroplasty) procedure, providing a real-time virtual model of the flexible drill. The flexible and steerable drill tip system is then tested on total hip arthroplasty followed by evaluation of the positioning and orientation of femoral stem placement by femoral milling. Based on this study, we conclude that the tracking and navigation system is able to guide the flexible drill to mill inside femoral canal. Copyright © 2017 John Wiley & Sons, Ltd.

  17. Multi-modal TiO2-LaFeO3 composite films with high photocatalytic activity and hydrophilicity

    International Nuclear Information System (INIS)

    Gao Kun; Li Shudan

    2012-01-01

    In this paper, a series of multi-modal TiO 2 -LaFeO 3 composite films have been successfully synthesized through a two-step method. The resultant films were characterized in detail by several testing techniques, such as X-ray diffraction (XRD), ultraviolet-visible diffuse reflection spectrum (UV-vis DRS), photoluminescence spectrum (PL), surface photovoltage spectroscopy (SPS) and water contact angle measurements. The photocatalytic activity of different films was evaluated for degrading Methylene Blue (MB) aqueous solution. Hydrophilicity of the obtained TiO 2 -LaFeO 3 composite films was also investigated. The results show that TL film and LT film exhibited superior photocatalytic activity and hydrophilicity.

  18. Multi-modal Intelligent Seizure Acquisition (MISA) system - A new approach towards seizure detection based on full body motion measures

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2009-01-01

    Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid...... hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three...... test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG...

  19. APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies.

    Science.gov (United States)

    Kanbar, Lara J; Shalish, Wissam; Precup, Doina; Brown, Karen; Sant'Anna, Guilherme M; Kearney, Robert E

    2017-07-01

    In multi-disciplinary studies, different forms of data are often collected for analysis. For example, APEX, a study on the automated prediction of extubation readiness in extremely preterm infants, collects clinical parameters and cardiorespiratory signals. A variety of cardiorespiratory metrics are computed from these signals and used to assign a cardiorespiratory pattern at each time. In such a situation, exploratory analysis requires a visualization tool capable of displaying these different types of acquired and computed signals in an integrated environment. Thus, we developed APEX_SCOPE, a graphical tool for the visualization of multi-modal data comprising cardiorespiratory signals, automated cardiorespiratory metrics, automated respiratory patterns, manually classified respiratory patterns, and manual annotations by clinicians during data acquisition. This MATLAB-based application provides a means for collaborators to view combinations of signals to promote discussion, generate hypotheses and develop features.

  20. CT and MR image fusion using two different methods after prostate brachytherapy: impact on post-implant dosimetric assessment

    International Nuclear Information System (INIS)

    Servois, V.; El Khoury, C.; Lantoine, A.; Ollivier, L.; Neuenschwander, S.; Chauveinc, L.; Cosset, J.M.; Flam, T.; Rosenwald, J.C.

    2003-01-01

    To study different methods of CT and MR images fusion in patient treated by brachytherapy for localized prostate cancer. To compare the results of the dosimetric study realized on CT slices and images fusion. Fourteen cases of patients treated by 1125 were retrospectively studied. The CT examinations were realized with continuous section of 5 mm thickness, and MR images were obtained with a surface coil with contiguous section of 3 mm thickness. For the images fusion process, only the T2 weighted MR sequence was used. Two processes of images fusion were realized for each patient, using as reference marks the bones of the pelvis and the implanted seeds. A quantitative and qualitative appreciation was made by the operators, for each patient and both methods of images fusion. The dosimetric study obtained by a dedicated software was realized on CT images and all types of images fusion. The usual dosimetric indexes (D90, V 100 and V 150) were compared for each type of image. The quantitative results given by the software of images fusion showed a superior accuracy to the one obtained by the pelvic bony reference marks. Conversely, qualitative and quantitative results obtained by the operators showed a better accuracy of the images fusion based on iodine seeds. For two patients out of three presenting a D90 inferior to 145 Gy on CT examination, the D90 was superior to this norm when the dosimetry was based on images fusion, whatever the method used. The images fusion method based on implanted seed matching seems to be more precise than the one using bony reference marks. The dosimetric study realized on images fusion could allow to rectify possible errors, mainly due to difficulties in surrounding prostate contour delimitation on CT images. (authors)

  1. Automatic multi-modal MR tissue classification for the assessment of response to bevacizumab in patients with glioblastoma

    International Nuclear Information System (INIS)

    Liberman, Gilad; Louzoun, Yoram; Aizenstein, Orna; Blumenthal, Deborah T.; Bokstein, Felix; Palmon, Mika; Corn, Benjamin W.; Ben Bashat, Dafna

    2013-01-01

    Background: Current methods for evaluation of treatment response in glioblastoma are inaccurate, limited and time-consuming. This study aimed to develop a multi-modal MRI automatic classification method to improve accuracy and efficiency of treatment response assessment in patients with recurrent glioblastoma (GB). Materials and methods: A modification of the k-Nearest-Neighbors (kNN) classification method was developed and applied to 59 longitudinal MR data sets of 13 patients with recurrent GB undergoing bevacizumab (anti-angiogenic) therapy. Changes in the enhancing tumor volume were assessed using the proposed method and compared with Macdonald's criteria and with manual volumetric measurements. The edema-like area was further subclassified into peri- and non-peri-tumoral edema, using both the kNN method and an unsupervised method, to monitor longitudinal changes. Results: Automatic classification using the modified kNN method was applicable in all scans, even when the tumors were infiltrative with unclear borders. The enhancing tumor volume obtained using the automatic method was highly correlated with manual measurements (N = 33, r = 0.96, p < 0.0001), while standard radiographic assessment based on Macdonald's criteria matched manual delineation and automatic results in only 68% of cases. A graded pattern of tumor infiltration within the edema-like area was revealed by both automatic methods, showing high agreement. All classification results were confirmed by a senior neuro-radiologist and validated using MR spectroscopy. Conclusion: This study emphasizes the important role of automatic tools based on a multi-modal view of the tissue in monitoring therapy response in patients with high grade gliomas specifically under anti-angiogenic therapy

  2. Distributed flow estimation and closed-loop control of an underwater vehicle with a multi-modal artificial lateral line.

    Science.gov (United States)

    DeVries, Levi; Lagor, Francis D; Lei, Hong; Tan, Xiaobo; Paley, Derek A

    2015-03-25

    Bio-inspired sensing modalities enhance the ability of autonomous vehicles to characterize and respond to their environment. This paper concerns the lateral line of cartilaginous and bony fish, which is sensitive to fluid motion and allows fish to sense oncoming flow and the presence of walls or obstacles. The lateral line consists of two types of sensing modalities: canal neuromasts measure approximate pressure gradients, whereas superficial neuromasts measure local flow velocities. By employing an artificial lateral line, the performance of underwater sensing and navigation strategies is improved in dark, cluttered, or murky environments where traditional sensing modalities may be hindered. This paper presents estimation and control strategies enabling an airfoil-shaped unmanned underwater vehicle to assimilate measurements from a bio-inspired, multi-modal artificial lateral line and estimate flow properties for feedback control. We utilize potential flow theory to model the fluid flow past a foil in a uniform flow and in the presence of an upstream obstacle. We derive theoretically justified nonlinear estimation strategies to estimate the free stream flowspeed, angle of attack, and the relative position of an upstream obstacle. The feedback control strategy uses the estimated flow properties to execute bio-inspired behaviors including rheotaxis (the tendency of fish to orient upstream) and station-holding (the tendency of fish to position behind an upstream obstacle). A robotic prototype outfitted with a multi-modal artificial lateral line composed of ionic polymer metal composite and embedded pressure sensors experimentally demonstrates the distributed flow sensing and closed-loop control strategies.

  3. Live-cell imaging of conidial anastomosis tube fusion during colony initiation in Fusarium oxysporum.

    Directory of Open Access Journals (Sweden)

    Smija M Kurian

    Full Text Available Fusarium oxysporum exhibits conidial anastomosis tube (CAT fusion during colony initiation to form networks of conidial germlings. Here we determined the optimal culture conditions for this fungus to undergo CAT fusion between microconidia in liquid medium. Extensive high resolution, confocal live-cell imaging was performed to characterise the different stages of CAT fusion, using genetically encoded fluorescent labelling and vital fluorescent organelle stains. CAT homing and fusion were found to be dependent on adhesion to the surface, in contrast to germ tube development which occurs in the absence of adhesion. Staining with fluorescently labelled concanavalin A indicated that the cell wall composition of CATs differs from that of microconidia and germ tubes. The movement of nuclei, mitochondria, vacuoles and lipid droplets through fused germlings was observed by live-cell imaging.

  4. Image fusion between whole body FDG PET images and whole body MRI images using a full-automatic mutual information-based multimodality image registration software

    International Nuclear Information System (INIS)

    Uchida, Yoshitaka; Nakano, Yoshitada; Fujibuchi, Toshiou; Isobe, Tomoko; Kazama, Toshiki; Ito, Hisao

    2006-01-01

    We attempted image fusion between whole body PET and whole body MRI of thirty patients using a full-automatic mutual information (MI) -based multimodality image registration software and evaluated accuracy of this method and impact of the coregistrated imaging on diagnostic accuracy. For 25 of 30 fused images in body area, translating gaps were within 6 mm in all axes and rotating gaps were within 2 degrees around all axes. In head and neck area, considerably much gaps caused by difference of head inclination at imaging occurred in 16 patients, however these gaps were able to decrease by fused separately. In 6 patients, diagnostic accuracy using PET/MRI fused images was superior compared by PET image alone. This work shows that whole body FDG PET images and whole body MRI images can be automatically fused using MI-based multimodality image registration software accurately and this technique can add useful information when evaluating FDG PET images. (author)

  5. Usefulness of CT based SPECT Fusion Image in the lung Disease : Preliminary Study

    International Nuclear Information System (INIS)

    Park, Hoon Hee; Lyu, Kwang Yeul; Kim, Tae Hyung; Shin, Ji Yun

    2012-01-01

    Recently, SPECT/CT system has been applied to many diseases, however, the application is not extensively applied at pulmonary disease. Especially, in case that, the pulmonary embolisms suspect at the CT images, SPECT is performed. For the accurate diagnosis, SPECT/CT tests are subsequently undergoing. However, without SPECT/CT, there are some limitations to apply these procedures. With SPECT/CT, although, most of the examination performed after CT. Moreover, such a test procedures generate unnecessary dual irradiation problem to the patient. In this study, we evaluated the amount of unnecessary irradiation, and the usefulness of fusion images of pulmonary disease, which independently acquired from SPECT and CT. Using NEMA PhantomTM (NU2-2001), SPECT and CT scan were performed for fusion images. From June 2011 to September 2010, 10 patients who didn't have other personal history, except lung disease were selected (male: 7, female: 3, mean age: 65.3±12.7). In both clinical patient and phantom data, the fusion images scored higher than SPECT and CT images. The fusion images, which is combined with pulmonary vessel images from CT and functional images from SPECT, can increase the detection possibility in detecting pulmonary embolism in the resin of lung parenchyma. It is sure that performing SPECT and CT in integral SPECT/CT system were better. However, we believe this protocol can give more informative data to have more accurate diagnosis in the hospital without integral SPECT/CT system.

  6. A multi-modal stereo microscope based on a spatial light modulator.

    Science.gov (United States)

    Lee, M P; Gibson, G M; Bowman, R; Bernet, S; Ritsch-Marte, M; Phillips, D B; Padgett, M J

    2013-07-15

    Spatial Light Modulators (SLMs) can emulate the classic microscopy techniques, including differential interference (DIC) contrast and (spiral) phase contrast. Their programmability entails the benefit of flexibility or the option to multiplex images, for single-shot quantitative imaging or for simultaneous multi-plane imaging (depth-of-field multiplexing). We report the development of a microscope sharing many of the previously demonstrated capabilities, within a holographic implementation of a stereo microscope. Furthermore, we use the SLM to combine stereo microscopy with a refocusing filter and with a darkfield filter. The instrument is built around a custom inverted microscope and equipped with an SLM which gives various imaging modes laterally displaced on the same camera chip. In addition, there is a wide angle camera for visualisation of a larger region of the sample.

  7. Mosaicing of single plane illumination microscopy images using groupwise registration and fast content-based image fusion

    Science.gov (United States)

    Preibisch, Stephan; Rohlfing, Torsten; Hasak, Michael P.; Tomancak, Pavel

    2008-03-01

    Single Plane Illumination Microscopy (SPIM; Huisken et al., Nature 305(5686):1007-1009, 2004) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the living biological sample from multiple angles SPIM has the potential to achieve isotropic resolution throughout even relatively large biological specimens. For every angle, however, only a relatively shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. In order to produce a single, uniformly high resolution image, we propose here an image mosaicing algorithm that combines state of the art groupwise image registration for alignment with content-based image fusion to prevent degrading of the fused image due to regional blurring of the input images. For the registration stage, we introduce an application-specific groupwise transformation model that incorporates per-image as well as groupwise transformation parameters. We also propose a new fusion algorithm based on Gaussian filters, which is substantially faster than fusion based on local image entropy. We demonstrate the performance of our mosaicing method on data acquired from living embryos of the fruit fly, Drosophila, using four and eight angle acquisitions.

  8. Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

    Science.gov (United States)

    Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

    2017-12-01

    In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

  9. Research on multi-source image fusion technology in haze environment

    Science.gov (United States)

    Ma, GuoDong; Piao, Yan; Li, Bing

    2017-11-01

    In the haze environment, the visible image collected by a single sensor can express the details of the shape, color and texture of the target very well, but because of the haze, the sharpness is low and some of the target subjects are lost; Because of the expression of thermal radiation and strong penetration ability, infrared image collected by a single sensor can clearly express the target subject, but it will lose detail information. Therefore, the multi-source image fusion method is proposed to exploit their respective advantages. Firstly, the improved Dark Channel Prior algorithm is used to preprocess the visible haze image. Secondly, the improved SURF algorithm is used to register the infrared image and the haze-free visible image. Finally, the weighted fusion algorithm based on information complementary is used to fuse the image. Experiments show that the proposed method can improve the clarity of the visible target and highlight the occluded infrared target for target recognition.

  10. Visualization of intracranial vessel anatomy using high resolution MRI and a simple image fusion technique

    International Nuclear Information System (INIS)

    Nasel, C.

    2005-01-01

    A new technique for fusion and 3D viewing of high resolution magnetic resonance (MR) angiography and morphological MR sequences is reported. Scanning and image fusion was possible within 20 min on a standard 1.5 T MR-scanner. The procedure was successfully performed in 10 consecutive cases with excellent visualization of wall and luminal aspects of the intracranial segments of the internal carotid artery, the vertebrobasilar system and the anterior, middle and posterior cerebral artery

  11. Visualization of intracranial vessel anatomy using high resolution MRI and a simple image fusion technique

    Energy Technology Data Exchange (ETDEWEB)

    Nasel, C. [Division of Neuroradiology, Department of Radiology, Medical University of Vienna, Waehringerguertel 18-20, A-1090 Vienna (Austria)]. E-mail: christian.nasel@perfusion.at

    2005-04-01

    A new technique for fusion and 3D viewing of high resolution magnetic resonance (MR) angiography and morphological MR sequences is reported. Scanning and image fusion was possible within 20 min on a standard 1.5 T MR-scanner. The procedure was successfully performed in 10 consecutive cases with excellent visualization of wall and luminal aspects of the intracranial segments of the internal carotid artery, the vertebrobasilar system and the anterior, middle and posterior cerebral artery.

  12. Information fusion in signal and image processing major probabilistic and non-probabilistic numerical approaches

    CERN Document Server

    Bloch, Isabelle

    2010-01-01

    The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

  13. An investigation of face and fingerprint feature-fusion guidelines

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-05-01

    Full Text Available There are a lack of multi-modal biometric fusion guidelines at the feature-level. This paper investigates face and fingerprint features in the form of their strengths and weaknesses. This serves as a set of guidelines to authors that are planning...

  14. Adaptive structured dictionary learning for image fusion based on group-sparse-representation

    Science.gov (United States)

    Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

    2018-04-01

    Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

  15. Detail-enhanced multimodality medical image fusion based on gradient minimization smoothing filter and shearing filter.

    Science.gov (United States)

    Liu, Xingbin; Mei, Wenbo; Du, Huiqian

    2018-02-13

    In this paper, a detail-enhanced multimodality medical image fusion algorithm is proposed by using proposed multi-scale joint decomposition framework (MJDF) and shearing filter (SF). The MJDF constructed with gradient minimization smoothing filter (GMSF) and Gaussian low-pass filter (GLF) is used to decompose source images into low-pass layers, edge layers, and detail layers at multiple scales. In order to highlight the detail information in the fused image, the edge layer and the detail layer in each scale are weighted combined into a detail-enhanced layer. As directional filter is effective in capturing salient information, so SF is applied to the detail-enhanced layer to extract geometrical features and obtain directional coefficients. Visual saliency map-based fusion rule is designed for fusing low-pass layers, and the sum of standard deviation is used as activity level measurement for directional coefficients fusion. The final fusion result is obtained by synthesizing the fused low-pass layers and directional coefficients. Experimental results show that the proposed method with shift-invariance, directional selectivity, and detail-enhanced property is efficient in preserving and enhancing detail information of multimodality medical images. Graphical abstract The detailed implementation of the proposed medical image fusion algorithm.

  16. Label fusion based brain MR image segmentation via a latent selective model

    Science.gov (United States)

    Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

    2018-04-01

    Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

  17. Application of Multimodality Imaging Fusion Technology in Diagnosis and Treatment of Malignant Tumors under the Precision Medicine Plan.

    Science.gov (United States)

    Wang, Shun-Yi; Chen, Xian-Xia; Li, Yi; Zhang, Yu-Ying

    2016-12-20

    The arrival of precision medicine plan brings new opportunities and challenges for patients undergoing precision diagnosis and treatment of malignant tumors. With the development of medical imaging, information on different modality imaging can be integrated and comprehensively analyzed by imaging fusion system. This review aimed to update the application of multimodality imaging fusion technology in the precise diagnosis and treatment of malignant tumors under the precision medicine plan. We introduced several multimodality imaging fusion technologies and their application to the diagnosis and treatment of malignant tumors in clinical practice. The data cited in this review were obtained mainly from the PubMed database from 1996 to 2016, using the keywords of "precision medicine", "fusion imaging", "multimodality", and "tumor diagnosis and treatment". Original articles, clinical practice, reviews, and other relevant literatures published in English were reviewed. Papers focusing on precision medicine, fusion imaging, multimodality, and tumor diagnosis and treatment were selected. Duplicated papers were excluded. Multimodality imaging fusion technology plays an important role in tumor diagnosis and treatment under the precision medicine plan, such as accurate location, qualitative diagnosis, tumor staging, treatment plan design, and real-time intraoperative monitoring. Multimodality imaging fusion systems could provide more imaging information of tumors from different dimensions and angles, thereby offing strong technical support for the implementation of precision oncology. Under the precision medicine plan, personalized treatment of tumors is a distinct possibility. We believe that multimodality imaging fusion technology will find an increasingly wide application in clinical practice.

  18. [Accuracy of morphological simulation for orthognatic surgery. Assessment of a 3D image fusion software.

    Science.gov (United States)

    Terzic, A; Schouman, T; Scolozzi, P

    2013-08-06

    The CT/CBCT data allows for 3D reconstruction of skeletal and untextured soft tissue volume. 3D stereophotogrammetry technology has strongly improved the quality of facial soft tissue surface texture. The combination of these two technologies allows for an accurate and complete reconstruction. The 3D virtual head may be used for orthognatic surgical planning, virtual surgery, and morphological simulation obtained with a software dedicated to the fusion of 3D photogrammetric and radiological images. The imaging material include: a multi-slice CT scan or broad field CBCT scan, a 3D photogrammetric camera. The operative image processing protocol includes the following steps: 1) pre- and postoperative CT/CBCT scan and 3D photogrammetric image acquisition; 2) 3D image segmentation and fusion of untextured CT/CBCT skin with the preoperative textured facial soft tissue surface of the 3D photogrammetric scan; 3) image fusion of the pre- and postoperative CT/CBCT data set virtual osteotomies, and 3D photogrammetric soft tissue virtual simulation; 4) fusion of virtual simulated 3D photogrammetric and real postoperative images, and assessment of accuracy using a color-coded scale to measure the differences between the two surfaces. Copyright © 2013. Published by Elsevier Masson SAS.

  19. Two-Dimensional Image Fusion of Planar Bone Scintigraphy and Radiographs in Patients with Clinical Scaphoid Fracture: An Imaging Study

    DEFF Research Database (Denmark)

    Henriksen, O.M.; Lonsdale, M.N.; Jensen, T.D.

    2008-01-01

    . Bone scintigraphy is highly sensitive for the detection of fractures, but exact localization of scintigraphic lesions may be difficult and can negatively affect diagnostic accuracy. Purpose: To investigate the influence of image fusion of planar bone scintigraphy and radiographs on image interpretation......Background: Although magnetic resonance imaging (MRI) is now considered the gold standard in second-line imaging of patients with suspected scaphoid fracture and negative radiographs, bone scintigraphy can be used in patients with pacemakers, metallic implants, or other contraindications to MRI....... Conclusion: Image fusion of planar bone scintigrams and radiographs has a significant influence on image interpretation and increases both diagnostic confidence and interobserver agreement Udgivelsesdato: 2008/12/3...

  20. Image fusion in craniofacial virtual reality modeling based on CT and 3dMD photogrammetry.

    Science.gov (United States)

    Xin, Pengfei; Yu, Hongbo; Cheng, Huanchong; Shen, Shunyao; Shen, Steve G F

    2013-09-01

    The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface. A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed. Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm. The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.

  1. Disguised face identification using multi-modal features in a quaternionic form

    DEFF Research Database (Denmark)

    Apostolopoulos, George; Tzitzilonis, Vasileios; Kappatos, Vassilios

    2017-01-01

    Disguised face recognition is considered as very challenging and important problem in the face recognition field. A disguised face recognition algorithm is proposed using quaternionic representation. The feature extraction module is accomplished with a new method, decomposing each face image...... that the proposed algorithm can achieve high recognition results under disguised conditions....

  2. Infrared and visible image fusion using discrete cosine transform and swarm intelligence for surveillance applications

    Science.gov (United States)

    Paramanandham, Nirmala; Rajendiran, Kishore

    2018-01-01

    A novel image fusion technique is presented for integrating infrared and visible images. Integration of images from the same or various sensing modalities can deliver the required information that cannot be delivered by viewing the sensor outputs individually and consecutively. In this paper, a swarm intelligence based image fusion technique using discrete cosine transform (DCT) domain is proposed for surveillance application which integrates the infrared image with the visible image for generating a single informative fused image. Particle swarm optimization (PSO) is used in the fusion process for obtaining the optimized weighting factor. These optimized weighting factors are used for fusing the DCT coefficients of visible and infrared images. Inverse DCT is applied for obtaining the initial fused image. An enhanced fused image is obtained through adaptive histogram equalization for a better visual understanding and target detection. The proposed framework is evaluated using quantitative metrics such as standard deviation, spatial frequency, entropy and mean gradient. The experimental results demonstrate the outperformance of the proposed algorithm over many other state- of- the- art techniques reported in literature.

  3. Three-dimensional registration methods for multi-modal magnetic resonance neuroimages

    International Nuclear Information System (INIS)

    Triantafyllou, C.

    2001-08-01

    In this thesis, image alignment techniques are developed and evaluated for applications in neuroimaging. In particular, the problem of combining cross-sequence MRI (Magnetic Resonance Imaging) intra-subject scans is considered. The challenge in this case is to find topographically uniform mappings in order to register (find a mapping between) low resolution echo-planar images and their high resolution structural counterparts. Such an approach enables us to effectually fuse, in a clinically useful way, information across scans. This dissertation devises a new framework by which this may be achieved, involving appropriate optimisation of the required mapping functions, which turn out to be non-linear and high-dimensional in nature. Novel ways to constrain and regularise these functions to enhance the computational speed of the process and the accuracy of the solution are also studied. The algorithms, whose characteristics are demonstrated for this specific application should be fully generalisable to other medical imaging modalities and potentially, other areas of image processing. To begin with, some existing registration methods are reviewed, followed by the introduction of an automated global 3-D registration method. Its performance is investigated on extracted cortical and ventricular surfaces by utilising the principles of the chamfer matching approach. Evaluations on synthetic and real data-sets, are performed to show that removal of global image differences is possible in principle, although the true accuracy of the method depends on the type of geometrical distortions present. These results also reveal that this class of algorithm is unable to solve more localised variations and higher order magnetic field distortions between the images. These facts motivate the development of a high-dimensional 3-D registration method capable of effecting a one-to-one correspondence by capturing the localised differences. This method was seen to account not only for

  4. Art care: A multi-modality coronary 3D reconstruction and hemodynamic status assessment software.

    Science.gov (United States)

    Siogkas, Panagiotis K; Stefanou, Kostas A; Athanasiou, Lambros S; Papafaklis, Michail I; Michalis, Lampros K; Fotiadis, Dimitrios I

    2018-01-01

    Due to the incremental increase of clinical interest in the development of software that allows the 3-dimensional (3D) reconstruction and the functional assessment of the coronary vasculature, several software packages have been developed and are available today. Taking this into consideration, we have developed an innovative suite of software modules that perform 3D reconstruction of coronary arterial segments using different coronary imaging modalities such as IntraVascular UltraSound (IVUS) and invasive coronary angiography images (ICA), Optical Coherence Tomography (OCT) and ICA images, or plain ICA images and can safely and accurately assess the hemodynamic status of the artery of interest. The user can perform automated or manual segmentation of the IVUS or OCT images, visualize in 3D the reconstructed vessel and export it to formats, which are compatible with other Computer Aided Design (CAD) software systems. We employ finite elements to provide the capability to assess the hemodynamic functionality of the reconstructed vessels by calculating the virtual functional assessment index (vFAI), an index that corresponds and has been shown to correlate well to the actual fractional flow reserve (FFR) value. All the modules of the proposed system have been thoroughly validated. In brief, the 3D-QCA module, compared to a successful commercial software of the same genre, presented very good correlation using several validation metrics, with a Pearson's correlation coefficient (R) for the calculated volumes, vFAI, length and minimum lumen diameter of 0.99, 0.99, 0.99 and 0.88, respectively. Moreover, the automatic lumen detection modules for IVUS and OCT presented very high accuracy compared to the annotations by medical experts with the Pearson's correlation coefficient reaching the values of 0.94 and 0.99, respectively. In this study, we have presented a user-friendly software for the 3D reconstruction of coronary arterial segments and the accurate hemodynamic

  5. Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

    Science.gov (United States)

    Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

    1994-09-01

    A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

  6. Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

    Directory of Open Access Journals (Sweden)

    Jing-Yu Yang

    2012-04-01

    Full Text Available When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person’s overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA. Specifically, one person’s different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

  7. Palmprint and face multi-modal biometric recognition based on SDA-GSVD and its kernelization.

    Science.gov (United States)

    Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

    2012-01-01

    When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

  8. Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

    Science.gov (United States)

    Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

    2012-01-01

    When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance. PMID:22778600

  9. Infrared and visible image fusion based on robust principal component analysis and compressed sensing

    Science.gov (United States)

    Li, Jun; Song, Minghui; Peng, Yuanxi

    2018-03-01

    Current infrared and visible image fusion methods do not achieve adequate information extraction, i.e., they cannot extract the target information from infrared images while retaining the background information from visible images. Moreover, most of them have high complexity and are time-consuming. This paper proposes an efficient image fusion framework for infrared and visible images on the basis of robust principal component analysis (RPCA) and compressed sensing (CS). The novel framework consists of three phases. First, RPCA decomposition is applied to the infrared and visible images to obtain their sparse and low-rank components, which represent the salient features and background information of the images, respectively. Second, the sparse and low-rank coefficients are fused by different strategies. On the one hand, the measurements of the sparse coefficients are obtained by the random Gaussian matrix, and they are then fused by the standard deviation (SD) based fusion rule. Next, the fused sparse component is obtained by reconstructing the result of the fused measurement using the fast continuous linearized augmented Lagrangian algorithm (FCLALM). On the other hand, the low-rank coefficients are fused using the max-absolute rule. Subsequently, the fused image is superposed by the fused sparse and low-rank components. For comparison, several popular fusion algorithms are tested experimentally. By comparing the fused results subjectively and objectively, we find that the proposed framework can extract the infrared targets while retaining the background information in the visible images. Thus, it exhibits state-of-the-art performance in terms of both fusion effects and timeliness.

  10. Ultrasound/Magnetic Resonance Image Fusion Guided Lumbosacral Plexus Block – A Clinical Study

    DEFF Research Database (Denmark)

    Strid, JM; Pedersen, Erik Morre; Søballe, Kjeld

    2014-01-01

    in a double-blinded randomized controlled trial with crossover design. MR datasets will be acquired and uploaded in an advanced US system (Epiq7, Phillips, Amsterdam, Netherlands). All volunteers will receive SSPS blocks with lidocaine added gadolinium contrast guided by US/MR image fusion and by US one week......Background and aims Ultrasound (US) guided lumbosacral plexus block (Supra Sacral Parallel Shift [SSPS]) offers an alternative to general anaesthesia and perioperative analgesia for hip surgery.1 The complex anatomy of the lumbosacral region hampers the accuracy of the block, but it may be improved...... by guidance of US and magnetic resonance (MR) image fusion and real-time 3D electronic needle tip tracking.2 We aim to estimate the effect and the distribution of lidocaine after SSPS guided by US/MR image fusion compared to SSPS guided by ultrasound. Methods Twenty-four healthy volunteers will be included...

  11. First downscattered neutron images from Inertial Confinement Fusion experiments at the National Ignition Facility

    Directory of Open Access Journals (Sweden)

    Guler Nevzat

    2013-11-01

    Full Text Available Inertial Confinement Fusion experiments at the National Ignition Facility (NIF are designed to understand and test the basic principles of self-sustaining fusion reactions by laser driven compression of deuterium-tritium (DT filled cryogenic plastic (CH capsules. The experimental campaign is ongoing to tune the implosions and characterize the burning plasma conditions. Nuclear diagnostics play an important role in measuring the characteristics of these burning plasmas, providing feedback to improve the implosion dynamics. The Neutron Imaging (NI diagnostic provides information on the distribution of the central fusion reaction region and the surrounding DT fuel by collecting images at two different energy bands for primary (13–15 MeV and downscattered (10–12 MeV neutrons. From these distributions, the final shape and size of the compressed capsule can be estimated and the symmetry of the compression can be inferred. The first downscattered neutron images from imploding ICF capsules are shown in this paper.

  12. First downscattered neutron images from Inertial Confinement Fusion experiments at the National Ignition Facility

    Science.gov (United States)

    Guler, Nevzat; Aragonez, Robert J.; Archuleta, Thomas N.; Batha, Steven H.; Clark, David D.; Clark, Deborah J.; Danly, Chris R.; Day, Robert D.; Fatherley, Valerie E.; Finch, Joshua P.; Gallegos, Robert A.; Garcia, Felix P.; Grim, Gary; Hsu, Albert H.; Jaramillo, Steven A.; Loomis, Eric N.; Mares, Danielle; Martinson, Drew D.; Merrill, Frank E.; Morgan, George L.; Munson, Carter; Murphy, Thomas J.; Oertel, John A.; Polk, Paul J.; Schmidt, Derek W.; Tregillis, Ian L.; Valdez, Adelaida C.; Volegov, Petr L.; Wang, Tai-Sen F.; Wilde, Carl H.; Wilke, Mark D.; Wilson, Douglas C.; Atkinson, Dennis P.; Bower, Dan E.; Drury, Owen B.; Dzenitis, John M.; Felker, Brian; Fittinghoff, David N.; Frank, Matthias; Liddick, Sean N.; Moran, Michael J.; Roberson, George P.; Weiss, Paul; Buckles, Robert A.; Cradick, Jerry R.; Kaufman, Morris I.; Lutz, Steve S.; Malone, Robert M.; Traille, Albert

    2013-11-01

    Inertial Confinement Fusion experiments at the National Ignition Facility (NIF) are designed to understand and test the basic principles of self-sustaining fusion reactions by laser driven compression of deuterium-tritium (DT) filled cryogenic plastic (CH) capsules. The experimental campaign is ongoing to tune the implosions and characterize the burning plasma conditions. Nuclear diagnostics play an important role in measuring the characteristics of these burning plasmas, providing feedback to improve the implosion dynamics. The Neutron Imaging (NI) diagnostic provides information on the distribution of the central fusion reaction region and the surrounding DT fuel by collecting images at two different energy bands for primary (13-15 MeV) and downscattered (10-12 MeV) neutrons. From these distributions, the final shape and size of the compressed capsule can be estimated and the symmetry of the compression can be inferred. The first downscattered neutron images from imploding ICF capsules are shown in this paper.

  13. Evaluating the efficacy of an integrated motivational interviewing and multi-modal exercise intervention for youth with major depression: Healthy Body, Healthy Mind randomised controlled trial protocol

    Directory of Open Access Journals (Sweden)

    Yasmina Nasstasia

    2018-03-01

    Conclusion: This trial will increase our understanding of the efficacy of multi-modal exercise interventions for depression and the specific effects of exercise on depressive symptom profiles. It also offers a novel contribution by addressing treatment engagement in exercise efficacy trials in youth with MDD.

  14. A multi-modal intervention for Activating Patients at Risk for Osteoporosis (APROPOS: Rationale, design, and uptake of online study intervention material

    Directory of Open Access Journals (Sweden)

    Maria I. Danila

    2016-12-01

    Conclusion: We developed and implemented a novel tailored multi-modal intervention to improve initiation of osteoporosis therapy. An email address provided on the survey was the most important factor independently associated with accessing the intervention online. The design and uptake of this intervention may have implications for future studies in osteoporosis or other chronic diseases.

  15. A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

    Science.gov (United States)

    van den Bergh, J.; Schutz, J.; Chirayath, V.; Li, A.

    2017-12-01

    NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Net's convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign.Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users' input against pre-classified coral imagery to gauge their accuracy and utilizes in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

  16. A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

    Science.gov (United States)

    van den Bergh, Jarrett; Schutz, Joey; Li, Alan; Chirayath, Ved

    2017-01-01

    NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

  17. An acceleration system for Laplacian image fusion based on SoC

    Science.gov (United States)

    Gao, Liwen; Zhao, Hongtu; Qu, Xiujie; Wei, Tianbo; Du, Peng

    2018-04-01

    Based on the analysis of Laplacian image fusion algorithm, this paper proposes a partial pipelining and modular processing architecture, and a SoC based acceleration system is implemented accordingly. Full pipelining method is used for the design of each module, and modules in series form the partial pipelining with unified data formation, which is easy for management and reuse. Integrated with ARM processor, DMA and embedded bare-mental program, this system achieves 4 layers of Laplacian pyramid on the Zynq-7000 board. Experiments show that, with small resources consumption, a couple of 256×256 images can be fused within 1ms, maintaining a fine fusion effect at the same time.

  18. Ontology-aided feature correlation for multi-modal urban sensing

    Science.gov (United States)

    Misra, Archan; Lantra, Zaman; Jayarajah, Kasthuri

    2016-05-01

    The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

  19. APPLICATION OF FUSION WITH SAR AND OPTICAL IMAGES IN LAND USE CLASSIFICATION BASED ON SVM

    Directory of Open Access Journals (Sweden)

    C. Bao

    2012-07-01

    Full Text Available As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture Radar (SAR and optical camera are two most common sensors presently. The multi-spectral optical images express spectral features of ground objects, while SAR images express backscatter information. Accuracy of the image classification could be effectively improved fusing the two kinds of images. In this paper, Terra SAR-X images and ALOS multi-spectral images were fused for land use classification. After preprocess such as geometric rectification, radiometric rectification noise suppression and so on, the two kind images were fused, and then SVM model identification method was used for land use classification. Two different fusion methods were used, one is joining SAR image into multi-spectral images as one band, and the other is direct fusing the two kind images. The former one can raise the resolution and reserve the texture information, and the latter can reserve spectral feature information and improve capability of identifying different features. The experiment results showed that accuracy of classification using fused images is better than only using multi-spectral images. Accuracy of classification about roads, habitation and water bodies was significantly improved. Compared to traditional classification method, the method of this paper for fused images with SVM classifier could achieve better results in identifying complicated land use classes, especially for small pieces ground features.

  20. A Multi-Modality Deep Network for Cold-Start Recommendation

    Directory of Open Access Journals (Sweden)

    Mingxuan Sun

    2018-03-01

    Full Text Available Collaborative filtering (CF approaches, which provide recommendations based on ratings or purchase history, perform well for users and items with sufficient interactions. However, CF approaches suffer from the cold-start problem for users and items with few ratings. Hybrid recommender systems that combine collaborative filtering and content-based approaches have been proved as an effective way to alleviate the cold-start issue. Integrating contents from multiple heterogeneous data sources such as reviews and product images is challenging for two reasons. Firstly, mapping contents in different modalities from the original feature space to a joint lower-dimensional space is difficult since they have intrinsically different characteristics and statistical properties, such as sparse texts and dense images. Secondly, most algorithms only use content features as the prior knowledge to improve the estimation of user and item profiles but the ratings do not directly provide feedback to guide feature extraction. To tackle these challenges, we propose a tightly-coupled deep network model for fusing heterogeneous modalities, to avoid tedious feature extraction in specific domains, and to enable two-way information propagation from both content and rating information. Experiments on large-scale Amazon product data in book and movie domains demonstrate the effectiveness of the proposed model for cold-start recommendation.

  1. Episodic aphasia associated with tumor active multiple sclerosis: a correlative SPECT study utilising image fusion

    International Nuclear Information System (INIS)

    Roff, G.; Campbell, A.; Lawn, N.; Henderson, A.; McCarthy, M.; Lenzo, N.

    2003-01-01

    Full text: Cerebral perfusion imaging is a common technique to assess cerebral perfusion and metabolism. It can complement anatomical imaging in assessing a number of neurological conditions. At times it can better define the clinical manifestations of a disease process than anatomical imaging alone. We present a clinical case whereby cerebral SPECT imaging helped define the physiological reason for intermittent aphasia in a patient with tumor active multiple sclerotic white matter plaques. Cerebral SPECT studies were performed during a period of aphasia and when the patient had recovered. We utilised subtraction analyses and image fusion techniques to better define the changes seen on SPECT. We discuss the neuroanatomical relationship of aphasia and the automatic fusion technique that allows accurate co-registration of the MRI and SPECT data. Copyright (2003) The Australian and New Zealand Society of Nuclear Medicine Inc

  2. Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

    Science.gov (United States)

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

    2018-04-01

    In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

  3. Evaluation of Effective Parameters on Quality of Magnetic Resonance Imaging-computed Tomography Image Fusion in Head and Neck Tumors for Application in Treatment Planning

    Directory of Open Access Journals (Sweden)

    Atefeh Shirvani

    2017-01-01

    Full Text Available Background: In radiation therapy, computed tomography (CT simulation is used for treatment planning to define the location of tumor. Magnetic resonance imaging (MRI-CT image fusion leads to more efficient tumor contouring. This work tried to identify the practical issues for the combination of CT and MRI images in real clinical cases. The effect of various factors is evaluated on image fusion quality. Materials and Methods: In this study, the data of thirty patients with brain tumors were used for image fusion. The effect of several parameters on possibility and quality of image fusion was evaluated. These parameters include angles of the patient's head on the bed, slices thickness, slice gap, and height of the patient's head. Results: According to the results, the first dominating factor on quality of image fusion was the difference slice gap between CT and MRI images (cor = 0.86, P 4 cm and image fusion quality was <25%. Conclusion: The most important problem in image fusion is that MRI images are taken without regard to their use in treatment planning. In general, parameters related to the patient position during MRI imaging should be chosen to be consistent with CT images of the patient in terms of location and angle.

  4. An analysis of fusion algorithms for LWIR and visual images

    CSIR Research Space (South Africa)

    De Villiers, J

    2013-12-01

    Full Text Available This paper presents a comparison of methods to fuse pre-registered colour visual and long wave infra-red images to create a new image containing both visual and thermal cues. Three methods of creating the artificially coloured fused images...

  5. Assessment of spatiotemporal fusion algorithms for Planet and Worldview images

    Science.gov (United States)

    Although Worldview (WV) images (non-pansharpened) have 2-meter resolution, the re-visit times for the same areas may be 7 days or more. In contrast, Planet images using small satellites can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It will be ideal to f...

  6. System for automatic x-ray-image analysis, measurement, and sorting of laser fusion targets

    International Nuclear Information System (INIS)

    Singleton, R.M.; Perkins, D.E.; Willenborg, D.L.

    1980-01-01

    This paper describes the Automatic X-Ray Image Analysis and Sorting (AXIAS) system which is designed to analyze and measure x-ray images of opaque hollow microspheres used as laser fusion targets. The x-ray images are first recorded on a high resolution film plate. The AXIAS system then digitizes and processes the images to accurately measure the target parameters and defects. The primary goals of the AXIAS system are: to provide extremely accurate and rapid measurements, to engineer a practical system for a routine production environment and to furnish the capability of automatically measuring an array of images for sorting and selection

  7. Echocardiographic and Fluoroscopic Fusion Imaging for Procedural Guidance: An Overview and Early Clinical Experience.

    Science.gov (United States)

    Thaden, Jeremy J; Sanon, Saurabh; Geske, Jeffrey B; Eleid, Mackram F; Nijhof, Niels; Malouf, Joseph F; Rihal, Charanjit S; Bruce, Charles J

    2016-06-01

    There has been significant growth in the volume and complexity of percutaneous structural heart procedures in the past decade. Increasing procedural complexity and accompanying reliance on multimodality imaging have fueled the development of fusion imaging to facilitate procedural guidance. The first clinically available system capable of echocardiographic and fluoroscopic fusion for real-time guidance of structural heart procedures was approved by the US Food and Drug Administration in 2012. Echocardiographic-fluoroscopic fusion imaging combines the precise catheter and device visualization of fluoroscopy with the soft tissue anatomy and color flow Doppler information afforded by echocardiography in a single image. This allows the interventionalist to perform precise catheter manipulations under fluoroscopy guidance while visualizing critical tissue anatomy provided by echocardiography. However, there are few data available addressing this technology's strengths and limitations in routine clinical practice. The authors provide a critical review of currently available echocardiographic-fluoroscopic fusion imaging for guidance of structural heart interventions to highlight its strengths, limitations, and potential clinical applications and to guide further research into value of this emerging technology. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

  8. Millimeter-wave imaging of magnetic fusion plasmas: technology innovations advancing physics understanding

    Science.gov (United States)

    Wang, Y.; Tobias, B.; Chang, Y.-T.; Yu, J.-H.; Li, M.; Hu, F.; Chen, M.; Mamidanna, M.; Phan, T.; Pham, A.-V.; Gu, J.; Liu, X.; Zhu, Y.; Domier, C. W.; Shi, L.; Valeo, E.; Kramer, G. J.; Kuwahara, D.; Nagayama, Y.; Mase, A.; Luhmann, N. C., Jr.

    2017-07-01

    Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. Microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These have the potential to greatly advance microwave fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfvén eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today’s most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.

  9. Infrared and visible image fusion based on total variation and augmented Lagrangian.

    Science.gov (United States)

    Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi

    2017-11-01

    This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.

  10. Clinical value of CT/MR-US fusion imaging for radiofrequency ablation of hepatic nodules

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Young, E-mail: leejy4u@snu.ac.kr [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Hospital, Seoul (Korea, Republic of); Choi, Byung Ihn [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Hospital, Seoul (Korea, Republic of); Chung, Yong Eun [Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Kim, Min Wook; Kim, Se Hyung; Han, Joon Koo [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Hospital, Seoul (Korea, Republic of)

    2012-09-15

    Objective: The aim of this study was to determine the registration error of an ultrasound (US) fusion imaging system during an ex vivo study and its clinical value for percutaneous radiofrequency ablation (pRFA) during an in vivo study. Materials and methods: An ex vivo study was performed using 4 bovine livers and 66 sonographically invisible lead pellets. Real-time CT-US fusion imaging was applied to assist the targeting of pellets with needles in each liver; the 4 sessions were performed by either an experienced radiologist (R1, 3 sessions) or an inexperienced resident (R2, 1 session). The distance between the pellet target and needle was measured. An in vivo study was retrospectively performed with 51 nodules (42 HCCs and 9 metastases; mean diameter, 16 mm) of 37 patients. Fusion imaging was used to create a sufficient safety margin (>5 mm) during pRFA in 24 nodules (group 1), accurately target 21 nodules obscured in the US images (group 2) and precisely identify 6 nodules surrounded by similar looking nodules (group 3). Image fusion was achieved using MR and CT images in 16 and 21 patients, respectively. The reablation rate, 1-year local recurrence rate and complications were assessed. Results: In the ex vivo study, the mean target–needle distances were 2.7 mm ± 1.9 mm (R1) and 3.1 ± 3.3 mm (R2) (p > 0.05). In the in vivo study, the reablation rates in groups 1–3 were 13%, 19% and 0%, respectively. At 1 year, the local recurrence rate was 11.8% (6/51). In our assessment of complications, one bile duct injury was observed. Conclusion: US fusion imaging system has an acceptable registration error and can be an efficacious tool for overcoming the major limitations of US-guided pRFA.

  11. Multi-modality photoacoustic tomography, ultrasound, and light sheet microscopy for volumetric tumor margin detection

    Science.gov (United States)

    Sangha, Gurneet S.; Hu, Bihe; Bolus, Daniel; Wang, Mei; Skidmore, Shelby J.; Sholl, Andrew B.; Brown, J. Quincy; Goergen, Craig J.

    2018-02-01

    Current methods for breast tumor margin detection are invasive, time consuming, and typically result in a reoperative rate of over 25%. This marks a clear clinical need to develop improved tools to intraoperatively differentiate negative versus positive tumor margins. Here, we utilize photoacoustic tomography (PAT), ultrasound (US), and inverted Selective Plane Illumination Microscopy (iSPIM) to assess breast tumor margins in eight human breast biopsies. Our PAT/US system consists of a tunable Nd:YAG laser (NT 300, EKSPLA) coupled with a 40MHz central frequency US probe (Vevo2100, FUJIFILM Visual Sonics). This system allows for the delivery of 10Hz, 5ns pulses with fluence of 40mJ/cm2 to the tissue with PAT and US axial resolutions of 125μm and 40μm, respectively. For this study, we used a linear stepper motor to acquire volumetric PAT/US images of the breast biopsies using 1100nm light to identify bloodrich "tumor" regions and 1210nm light to identify lipid-rich "healthy" regions. iSPIM (Applied Scientific Instrumentation) is an advanced microscopy technique with lateral resolution of 1.5μm and axial resolution of 7μm. We used 488nm laser excitation and acridine orange as a general comprehensive histology stain. Our results show that PAT/US can be used to identify lipid-rich regions, dense areas of arterioles and arteries, and other internal structures such as ducts. iSPIM images correlate well with histopathology slides and can verify nuclear features, cell type and density, stromal features, and microcalcifications. Together, this multimodality approach has the potential to improve tumor margin detection with a high degree of sensitivity and specificity.

  12. Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

    Science.gov (United States)

    Feyen, Luc; Caers, Jef

    2006-06-01

    In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport

  13. Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection.

    Science.gov (United States)

    Wei, Pan; Ball, John E; Anderson, Derek T

    2018-03-17

    A significant challenge in object detection is accurate identification of an object's position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS) applications.

  14. Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection

    Directory of Open Access Journals (Sweden)

    Pan Wei

    2018-03-01

    Full Text Available A significant challenge in object detection is accurate identification of an object’s position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS applications.

  15. Smart Images Search based on Visual Features Fusion

    International Nuclear Information System (INIS)

    Saad, M.H.

    2013-01-01

    Image search engines attempt to give fast and accurate access to the wide range of the huge amount images available on the Internet. There have been a number of efforts to build search engines based on the image content to enhance search results. Content-Based Image Retrieval (CBIR) systems have achieved a great interest since multimedia files, such as images and videos, have dramatically entered our lives throughout the last decade. CBIR allows automatically extracting target images according to objective visual contents of the image itself, for example its shapes, colors and textures to provide more accurate ranking of the results. The recent approaches of CBIR differ in terms of which image features are extracted to be used as image descriptors for matching process. This thesis proposes improvements of the efficiency and accuracy of CBIR systems by integrating different types of image features. This framework addresses efficient retrieval of images in large image collections. A comparative study between recent CBIR techniques is provided. According to this study; image features need to be integrated to provide more accurate description of image content and better image retrieval accuracy. In this context, this thesis presents new image retrieval approaches that provide more accurate retrieval accuracy than previous approaches. The first proposed image retrieval system uses color, texture and shape descriptors to form the global features vector. This approach integrates the yc b c r color histogram as a color descriptor, the modified Fourier descriptor as a shape descriptor and modified Edge Histogram as a texture descriptor in order to enhance the retrieval results. The second proposed approach integrates the global features vector, which is used in the first approach, with the SURF salient point technique as local feature. The nearest neighbor matching algorithm with a proposed similarity measure is applied to determine the final image rank. The second approach

  16. Multimodal Registration and Fusion for 3D Thermal Imaging

    Directory of Open Access Journals (Sweden)

    Moulay A. Akhloufi

    2015-01-01

    Full Text Available 3D vision is an area of computer vision that has attracted a lot of research interest and has been widely studied. In recent years we witness an increasing interest from the industrial community. This interest is driven by the recent advances in 3D technologies, which enable high precision measurements at an affordable cost. With 3D vision techniques we can conduct advanced manufactured parts inspections and metrology analysis. However, we are not able to detect subsurface defects. This kind of detection is achieved by other techniques, like infrared thermography. In this work, we present a new registration framework for 3D and thermal infrared multimodal fusion. The resulting fused data can be used for advanced 3D inspection in Nondestructive Testing and Evaluation (NDT&E applications. The fusion permits the simultaneous visible surface and subsurface inspections to be conducted in the same process. Experimental tests were conducted with different materials. The obtained results are promising and show how these new techniques can be used efficiently in a combined NDT&E-Metrology analysis of manufactured parts, in areas such as aerospace and automotive.

  17. SPECT/CT image fusion with 99mTc-HYNIC-TOC in the oncological diagnostic

    International Nuclear Information System (INIS)

    Haeusler, F.

    2006-07-01

    Neuroendocrine tumours displaying somatostatin receptors have been successfully visualized with somatostatin receptor imaging. The aim of this retrospective study was to evaluate the value of anatomical-functional image fusion. Image fusion means the combined transmission and emission tomography (computed tomography (CT)) and single-photon emission computed tomography (SPECT) ) and was analyzed in comparison with SPECT and CT alone. Fifty-three patients (30 men and 23 women; mean age 55,9 years; range: 20-82 years) with suspected or known endocrine tumours were studied. The patients were referred to image fusion because of staging of newly diagnosed tumours (14) or biochemically/clinically suspected neuroendocrine tumour (20) or follow-up studies after therapy (19). The patients were studied with SPECT at 2 and 4 hours after injection of 400 MBq of 99mTc-EDDA-HYNIC-Tyr3-octreotide using a dual-detector scintillation camera. The CT was performed on one of the following two days. For both investigations the patients were fixed in an individualized vacuum mattress to guarantee exactly the same position. SPECT and SPECT/CT showed an equivalent scan result in 35 patients (66 %), discrepancies were found in 18 cases (34 %). After image fusion the scan result was true-positive in 27 patients ( 50.9 %) and true-negative in 25 patients (47.2 %). One patient with multiple small liver metastases escaped SPECT as well as image fusion and was so false-negative. The frequency of equivocal and probable lesion characterization was reduced by 11.6% (12 to 0) with PET/CT in comparison with PET or CT alone. The frequency of definite lesion characterization was increased by 11.6% (91 to 103). SPECT/CT affected the clinical management in 21 patients (40 %). The results of this study indicate that SPECT/CT is a valuable tool for the assessment of neuroendocrine tumours. SPECT/CT is better than SPECT or CT alone and it allows a more precise staging and determination of prognosis and

  18. Structural hippocampal network alterations during healthy aging: A multi-modal MRI study

    Directory of Open Access Journals (Sweden)

    Amandine ePelletier

    2013-12-01

    Full Text Available While hippocampal atrophy has been described during healthy aging, few studies have examined its relationship with the integrity of White Matter (WM connecting tracts of the limbic system. This investigation examined WM structural damage specifically related to hippocampal atrophy in healthy aging subjects (n=129, using morphological MRI to assess hippocampal volume and Diffusion Tensor Imaging (DTI to assess WM integrity. Subjects with Mild Cognitive Impairment (MCI or dementia were excluded from the analysis. In our sample, increasing age was significantly associated with reduced hippocampal volume and reduced Fractional Anisotropy (FA at the level of the fornix and the cingulum bundle. The findings also demonstrate that hippocampal atrophy was specifically associated with reduced FA of the fornix bundle, but it was not related to alteration of the cingulum bundle. Our results indicate that the relationship between hippocampal atrophy and fornix FA values is not due to an independent effect of age on both structures. A recursive regression procedure was applied to evaluate sequential relationships between the alterations of these two brain structures. When both hippocampal atrophy and fornix FA values were included in the same model to predict age, fornix FA values remained significant whereas hippocampal atrophy was no longer significantly associated with age. According to this latter finding, hippocampal atrophy in healthy aging could be mediated by a loss of fornix connections. Structural alterations of this part of the limbic system, which have been associated with neurodegeneration in Alzheimer’s disease, result at least in part from the aging process.

  19. Fusion of magnetic resonance angiography and magnetic resonance imaging for surgical planning for meningioma. Technical note

    International Nuclear Information System (INIS)

    Kashimura, Hiroshi; Ogasawara, Kuniaki; Arai, Hiroshi

    2008-01-01

    A fusion technique for magnetic resonance (MR) angiography and MR imaging was developed to help assess the peritumoral angioarchitecture during surgical planning for meningioma. Three-dimensional time-of-flight (3D-TOF) and 3D-spoiled gradient recalled (SPGR) datasets were obtained from 10 patients with intracranial meningioma, and fused using newly developed volume registration and visualization software. Maximum intensity projection (MIP) images from 3D-TOF MR angiography and axial SPGR MR imaging were displayed at the same time on the monitor. Selecting a vessel on the real-time MIP image indicated the corresponding points on the axial image automatically. Fusion images showed displacement of the anterior cerebral or middle cerebral artery in 7 patients and encasement of the anterior cerebral arteries in I patient, with no relationship between the main arterial trunk and tumor in 2 patients. Fusion of MR angiography and MR imaging can clarify relationships between the intracranial vasculature and meningioma, and may be helpful for surgical planning for meningioma. (author)

  20. Multichannel far-infrared phase imaging for fusion plasmas

    International Nuclear Information System (INIS)

    Young, P.E.; Neikirk, D.P.; Tong, P.P.; Rutledge, D.B.; Luhmann, N.C. Jr.

    1985-01-01

    A 20-channel far-infrared imaging interferometer system has been used to obtain single-shot density profiles in the UCLA Microtor tokamak. This system differs from conventional multichannel interferometers in that the phase distribution produced by the plasma is imaged onto a single, monolithic, integrated microbolometer linear detector array and provides significantly more channels than previous far-infrared interferometers. The system has been demonstrated to provide diffraction-limited phase images of dielectric targets

  1. Fusion

    International Nuclear Information System (INIS)

    Bolwell, J. J.

    2009-01-01

    Full text:A 5-year-old female with a history of right sided hypertonia and frequent seizures presented to our department for investigation. She had previously undergone two MRI scans, one in 2004 which demonstrated significant loss of volume of the left hemisphere, a loss of deep and subcortical white matter, markedly dilated left lateral ventricle. This MRI gave a diagnosis of cerebral palsy. In 2007 she underwent an additional brain MRI at the Royal Children's Hospital which demonstrated no significant change from 2004 images and the report was suggestive of an old antenatal/perinatal ischaemic event as the cause of her brain condition. In September of 2008 she was investigated in our department looking for a focus of epilepsy. She underwent a 99mTc-ECD Ictal SPECT/CT study and an 18F-FDG Inter-ictal PET brain study which were later both fused with an additional MRI performed in September of 2008 at the RCH. The PET and SPECT datasets were both corrected for attenuation using their own low dose CT acquisitions and then they were fused with the T2 MRI images. The fused images demonstrated multiple epileptic foci in both sides of the brain with the left side being the more severe of the two. Based on the result of findings of the PET/CT and SPECT/CT fused with the MRI and the failure of medication and dietary strategies, the treating team has decided to perform a partial hemispherectomy of the left side of the brain to alleviate the seizures.

  2. Composite multi-modal vibration control for a stiffened plate using non-collocated acceleration sensor and piezoelectric actuator

    International Nuclear Information System (INIS)

    Li, Shengquan; Li, Juan; Mo, Yueping; Zhao, Rong

    2014-01-01

    A novel active method for multi-mode vibration control of an all-clamped stiffened plate (ACSP) is proposed in this paper, using the extended-state-observer (ESO) approach based on non-collocated acceleration sensors and piezoelectric actuators. Considering the estimated capacity of ESO for system state variables, output superposition and control coupling of other modes, external excitation, and model uncertainties simultaneously, a composite control method, i.e., the ESO based vibration control scheme, is employed to ensure the lumped disturbances and uncertainty rejection of the closed-loop system. The phenomenon of phase hysteresis and time delay, caused by non-collocated sensor/actuator pairs, degrades the performance of the control system, even inducing instability. To solve this problem, a simple proportional differential (PD) controller and acceleration feed-forward with an output predictor design produce the control law for each vibration mode. The modal frequencies, phase hysteresis loops and phase lag values due to non-collocated placement of the acceleration sensor and piezoelectric patch actuator are experimentally obtained, and the phase lag is compensated by using the Smith Predictor technology. In order to improve the vibration control performance, the chaos optimization method based on logistic mapping is employed to auto-tune the parameters of the feedback channel. The experimental control system for the ACSP is tested using the dSPACE real-time simulation platform. Experimental results demonstrate that the proposed composite active control algorithm is an effective approach for suppressing multi-modal vibrations. (paper)

  3. Large area imaging of hydrogenous materials using fast neutrons from a DD fusion generator

    Energy Technology Data Exchange (ETDEWEB)

    Cremer, J.T., E-mail: ted@adelphitech.com [Adelphi Technology Inc., 2003 East Bayshore Road, Redwood City, California 94063 (United States); Williams, D.L.; Gary, C.K.; Piestrup, M.A.; Faber, D.R.; Fuller, M.J.; Vainionpaa, J.H.; Apodaca, M. [Adelphi Technology Inc., 2003 East Bayshore Road, Redwood City, California 94063 (United States); Pantell, R.H.; Feinstein, J. [Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States)

    2012-05-21

    A small-laboratory fast-neutron generator and a large area detector were used to image hydrogen-bearing materials. The overall image resolution of 2.5 mm was determined by a knife-edge measurement. Contact images of objects were obtained in 5-50 min exposures by placing them close to a plastic scintillator at distances of 1.5 to 3.2 m from the neutron source. The generator produces 10{sup 9} n/s from the DD fusion reaction at a small target. The combination of the DD-fusion generator and electronic camera permits both small laboratory and field-portable imaging of hydrogen-rich materials embedded in high density materials.

  4. Real-time image registration and fusion in a FPGA architecture (Ad-FIRE)

    Science.gov (United States)

    Waters, T.; Swan, L.; Rickman, R.

    2011-06-01

    Real-time Image Registration is a key processing requirement of Waterfall Solutions' image fusion system, Ad-FIRE, which combines the attributes of high resolution visible imagery with the spectral response of low resolution thermal sensors in a single composite image. Implementing image fusion at video frame rates typically requires a high bandwidth video processing capability which, within a standard CPU-type processing architecture, necessitates bulky, high power components. Field Programmable Gate Arrays (FPGAs) offer the prospect of low power/heat dissipation combined with highly efficient processing architectures for use in portable, battery-powered, passively cooled applications, such as Waterfall Solutions' hand-held or helmet-mounted Ad-FIRE system.

  5. Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems.

    Science.gov (United States)

    Lai, J; Domier, C W; Luhmann, N C

    2014-03-01

    Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas [B. Tobias et al., Plasma Fusion Res. 6, 2106042 (2011)]. Of particular importance have been microwave electron cyclotron emission imaging and microwave imaging reflectometry systems for imaging T(e) and n(e) fluctuations. These instruments have employed heterodyne receiver arrays with Schottky diode mixer elements directly connected to individual antennas. Consequently, the noise temperature has been strongly determined by the conversion loss with typical noise temperatures of ~60,000 K. However, this can be significantly improved by making use of recent advances in Monolithic Microwave Integrated Circuit chip low noise amplifiers to insert a pre-amplifier in front of the Schottky diode mixer element. In a proof-of-principle design at V-Band (50-75 GHz), significant improvement of noise temperature from the current 60,000 K to measured 4000 K has been obtained.

  6. Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems

    International Nuclear Information System (INIS)

    Lai, J.; Domier, C. W.; Luhmann, N. C.

    2014-01-01

    Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas [B. Tobias et al., Plasma Fusion Res. 6, 2106042 (2011)]. Of particular importance have been microwave electron cyclotron emission imaging and microwave imaging reflectometry systems for imaging T e and n e fluctuations. These instruments have employed heterodyne receiver arrays with Schottky diode mixer elements directly connected to individual antennas. Consequently, the noise temperature has been strongly determined by the conversion loss with typical noise temperatures of ∼60 000 K. However, this can be significantly improved by making use of recent advances in Monolithic Microwave Integrated Circuit chip low noise amplifiers to insert a pre-amplifier in front of the Schottky diode mixer element. In a proof-of-principle design at V-Band (50–75 GHz), significant improvement of noise temperature from the current 60 000 K to measured 4000 K has been obtained

  7. A label field fusion bayesian model and its penalized maximum rand estimator for image segmentation.

    Science.gov (United States)

    Mignotte, Max

    2010-06-01

    This paper presents a novel segmentation approach based on a Markov random field (MRF) fusion model which aims at combining several segmentation results associated with simpler clustering models in order to achieve a more reliable and accurate segmentation result. The proposed fusion model is derived from the recently introduced probabilistic Rand measure for comparing one segmentation result to one or more manual segmentations of the same image. This non-parametric measure allows us to easily derive an appealing fusion model of label fields, easily expressed as a Gibbs distribution, or as a nonstationary MRF model defined on a complete graph. Concretely, this Gibbs energy model encodes the set of binary constraints, in terms of pairs of pixel labels, provided by each segmentation results to be fused. Combined with a prior distribution, this energy-based Gibbs model also allows for definition of an interesting penalized maximum probabilistic rand estimator with which the fusion of simple, quickly estimated, segmentation results appears as an interesting alternative to complex segmentation models existing in the literature. This fusion framework has been successfully applied on the Berkeley image database. The experiments reported in this paper demonstrate that the proposed method is efficient in terms of visual evaluation and quantitative performance measures and performs well compared to the best existing state-of-the-art segmentation methods recently proposed in the literature.

  8. Color-coded Live Imaging of Heterokaryon Formation and Nuclear Fusion of Hybridizing Cancer Cells.

    Science.gov (United States)

    Suetsugu, Atsushi; Matsumoto, Takuro; Hasegawa, Kosuke; Nakamura, Miki; Kunisada, Takahiro; Shimizu, Masahito; Saji, Shigetoyo; Moriwaki, Hisataka; Bouvet, Michael; Hoffman, Robert M

    2016-08-01

    Fusion of cancer cells has been studied for over half a century. However, the steps involved after initial fusion between cells, such as heterokaryon formation and nuclear fusion, have been difficult to observe in real time. In order to be able to visualize these steps, we have established cancer-cell sublines from the human HT-1080 fibrosarcoma, one expressing green fluorescent protein (GFP) linked to histone H2B in the nucleus and a red fluorescent protein (RFP) in the cytoplasm and the other subline expressing RFP in the nucleus (mCherry) linked to histone H2B and GFP in the cytoplasm. The two reciprocal color-coded sublines of HT-1080 cells were fused using the Sendai virus. The fused cells were cultured on plastic and observed using an Olympus FV1000 confocal microscope. Multi-nucleate (heterokaryotic) cancer cells, in addition to hybrid cancer cells with single-or multiple-fused nuclei, including fused mitotic nuclei, were observed among the fused cells. Heterokaryons with red, green, orange and yellow nuclei were observed by confocal imaging, even in single hybrid cells. The orange and yellow nuclei indicate nuclear fusion. Red and green nuclei remained unfused. Cell fusion with heterokaryon formation and subsequent nuclear fusion resulting in hybridization may be an important natural phenomenon between cancer cells that may make them more malignant. The ability to image the complex processes following cell fusion using reciprocal color-coded cancer cells will allow greater understanding of the genetic basis of malignancy. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  9. A hybrid image fusion system for endovascular interventions of peripheral artery disease.

    Science.gov (United States)

    Lalys, Florent; Favre, Ketty; Villena, Alexandre; Durrmann, Vincent; Colleaux, Mathieu; Lucas, Antoine; Kaladji, Adrien

    2018-03-16

    Interventional endovascular treatment has become the first line of management in the treatment of peripheral artery disease (PAD). However, contrast and radiation exposure continue to limit the feasibility of these procedures. This paper presents a novel hybrid image fusion system for endovascular intervention of PAD. We present two different roadmapping methods from intra- and pre-interventional imaging that can be used either simultaneously or independently, constituting the navigation system. The navigation system is decomposed into several steps that can be entirely integrated within the procedure workflow without modifying it to benefit from the roadmapping. First, a 2D panorama of the entire peripheral artery system is automatically created based on a sequence of stepping fluoroscopic images acquired during the intra-interventional diagnosis phase. During the interventional phase, the live image can be synchronized on the panorama to form the basis of the image fusion system. Two types of augmented information are then integrated. First, an angiography panorama is proposed to avoid contrast media re-injection. Information exploiting the pre-interventional computed tomography angiography (CTA) is also brought to the surgeon by means of semiautomatic 3D/2D registration on the 2D panorama. Each step of the workflow was independently validated. Experiments for both the 2D panorama creation and the synchronization processes showed very accurate results (errors of 1.24 and [Formula: see text] mm, respectively), similarly to the registration on the 3D CTA (errors of [Formula: see text] mm), with minimal user interaction and very low computation time. First results of an on-going clinical study highlighted its major clinical added value on intraoperative parameters. No image fusion system has been proposed yet for endovascular procedures of PAD in lower extremities. More globally, such a navigation system, combining image fusion from different 2D and 3D image

  10. Geophysical data fusion for subsurface imaging. Final report

    International Nuclear Information System (INIS)

    1995-10-01

    This report contains the results of a three year, three-phase project whose long-range goal has been to create a means for the more detailed and accurate definition of the near-surface (0--300 ft) geology beneath a site that had been subjected to environmental pollution. The two major areas of research and development have been: improved geophysical field data acquisition techniques; and analytical tools for providing the total integration (fusion) of all site data. The long-range goal of this project has been to mathematically, integrate the geophysical data that could be derived from multiple sensors with site geologic information and any other type of available site data, to provide a detailed characterization of thin clay layers and geological discontinuities at hazardous waste sites

  11. Geophysical data fusion for subsurface imaging. Final report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-10-01

    This report contains the results of a three year, three-phase project whose long-range goal has been to create a means for the more detailed and accurate definition of the near-surface (0--300 ft) geology beneath a site that had been subjected to environmental pollution. The two major areas of research and development have been: improved geophysical field data acquisition techniques; and analytical tools for providing the total integration (fusion) of all site data. The long-range goal of this project has been to mathematically, integrate the geophysical data that could be derived from multiple sensors with site geologic information and any other type of available site data, to provide a detailed characterization of thin clay layers and geological discontinuities at hazardous waste sites.

  12. CT-MR image data fusion for computer assisted navigated neurosurgery of temporal bone tumors

    International Nuclear Information System (INIS)

    Nemec, Stefan Franz; Donat, Markus Alexander; Mehrain, Sheida; Friedrich, Klaus; Krestan, Christian; Matula, Christian; Imhof, Herwig; Czerny, Christian

    2007-01-01

    Purpose: To demonstrate the value of multi detector computed tomography (MDCT) and magnetic resonance imaging (MRI) in the preoperative work up of temporal bone tumors and to present, especially, CT and MR image fusion for surgical planning and performance in computer assisted navigated neurosurgery of temporal bone tumors. Materials and methods: Fifteen patients with temporal bone tumors underwent MDCT and MRI. MDCT was performed in high-resolution bone window level setting in axial plane. The reconstructed MDCT slice thickness was 0.8 mm. MRI was performed in axial and coronal plane with T2-weighted fast spin-echo (FSE) sequences, un-enhanced and contrast-enhanced T1-weighted spin-echo (SE) sequences, and coronal T1-weighted SE sequences with fat suppression and with 3D T1-weighted gradient-echo (GE) contrast-enhanced sequences in axial plane. The 3D T1-weighted GE sequence had a slice thickness of 1 mm. Image data sets of CT and 3D T1-weighted GE sequences were merged utilizing a workstation to create CT-MR fusion images. MDCT and MR images were separately used to depict and characterize lesions. The fusion images were utilized for interventional planning and intraoperative image guidance. The intraoperative accuracy of the navigation unit was measured, defined as the deviation between the same landmark in the navigation image and the patient. Results: Tumorous lesions of bone and soft tissue were well delineated and characterized by CT and MR images. The images played a crucial role in the differentiation of benign and malignant pathologies, which consisted of 13 benign and 2 malignant tumors. The CT-MR fusion images supported the surgeon in preoperative planning and improved surgical performance. The mean intraoperative accuracy of the navigation system was 1.25 mm. Conclusion: CT and MRI are essential in the preoperative work up of temporal bone tumors. CT-MR image data fusion presents an accurate tool for planning the correct surgical procedure and is a

  13. Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

    Science.gov (United States)

    Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

    2014-04-01

    In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

  14. A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Arvind Selwal

    2016-09-01

    Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.

  15. Volume navigation with contrast enhanced ultrasound and image fusion for percutaneous interventions: first results.

    Directory of Open Access Journals (Sweden)

    Ernst Michael Jung

    Full Text Available OBJECTIVE: Assessing the feasibility and efficiency of interventions using ultrasound (US volume navigation (V Nav with real time needle tracking and image fusion with contrast enhanced (ce CT, MRI or US. METHODS: First an in vitro study on a liver phantom with CT data image fusion was performed, involving the puncture of a 10 mm lesion in a depth of 5 cm performed by 15 examiners with US guided freehand technique vs. V Nav for the purpose of time optimization. Then 23 patients underwent ultrasound-navigated biopsies or interventions using V Nav image fusion of live ultrasound with ceCT, ceMRI or CEUS, which were acquired before the intervention. A CEUS data set was acquired in all patients. Image fusion was established for CEUS and CT or CEUS and MRI using anatomical landmarks in the area of the targeted lesion. The definition of a virtual biopsy line with navigational axes targeting the lesion was achieved by the usage of sterile trocar with a magnetic sensor embedded in its distal tip employing a dedicated navigation software for real time needle tracking. RESULTS: The in vitro study showed significantly less time needed for the simulated interventions in all examiners when V Nav was used (p<0.05. In the study involving patients, in all 10 biopsies of suspect lesions of the liver a histological confirmation was achieved. We also used V Nav for a breast biopsy (intraductal carcinoma, for a biopsy of the abdominal wall (metastasis of ovarial carcinoma and for radiofrequency ablations (4 ablations. In 8 cases of inflammatory abdominal lesions 9 percutaneous drainages were successfully inserted. CONCLUSION: Percutaneous biopsies and drainages, even of small lesions involving complex access pathways, can be accomplished with a high success rate by using 3D real time image fusion together with real time needle tracking.

  16. Development and reliability of a multi-modality scoring system for evaluation of disease progression in pre-clinical models of osteoarthritis: celecoxib may possess disease-modifying properties.

    Science.gov (United States)

    Panahifar, A; Jaremko, J L; Tessier, A G; Lambert, R G; Maksymowych, W P; Fallone, B G; Doschak, M R

    2014-10-01

    We sought to develop a comprehensive scoring system for evaluation of pre-clinical models of osteoarthritis (OA) progression, and use this to evaluate two different classes of drugs for management of OA. Post-traumatic OA (PTOA) was surgically induced in skeletally mature rats. Rats were randomly divided in three groups receiving either glucosamine (high dose of 192 mg/kg) or celecoxib (clinical dose) or no treatment. Disease progression was monitored utilizing micro-magnetic resonance imaging (MRI), micro-computed tomography (CT) and histology. Pertinent features such as osteophytes, subchondral sclerosis, joint effusion, bone marrow lesion (BML), cysts, loose bodies and cartilage abnormalities were included in designing a sensitive multi-modality based scoring system, termed the rat arthritis knee scoring system (RAKSS). Overall, an inter-observer correlation coefficient (ICC) of greater than 0.750 was achieved for each scored feature. None of the treatments prevented cartilage loss, synovitis, joint effusion, or sclerosis. However, celecoxib significantly reduced osteophyte development compared to placebo. Although signs of inflammation such as synovitis and joint effusion were readily identified at 4 weeks post-operation, we did not detect any BML. We report the development of a sensitive and reliable multi-modality scoring system, the RAKSS, for evaluation of OA severity in pre-clinical animal models. Using this scoring system, we found that celecoxib prevented enlargement of osteophytes in this animal model of PTOA, and thus it may be useful in preventing OA progression. However, it did not show any chondroprotective effect using the recommended dose. In contrast, high dose glucosamine had no measurable effects. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

  17. Clinical use of digital retrospective image fusion of CT, MRI, FDG-PET and SPECT - fields of indications and results

    International Nuclear Information System (INIS)

    Lemke, A.J.; Niehues, S.M.; Amthauer, H.; Felix, R.; Rohlfing, T.; Hosten, N.

    2004-01-01

    Purpose: To evaluate the feasibility and the clinical benefits of retrospective digital image fusion (PET, SPECT, CT and MRI). Materials and methods: In a prospective study, a total of 273 image fusions were performed and evaluated. The underlying image acquisitions (CT, MRI, SPECT and PET) were performed in a way appropriate for the respective clinical question and anatomical region. Image fusion was executed with a software program developed during this study. The results of the image fusion procedure were evaluated in terms of technical feasibility, clinical objective, and therapeutic impact. Results: The most frequent combinations of modalities were CT/PET (n = 156) and MRI/PET (n = 59), followed by MRI/SPECT (n = 28), CT/SPECT (n = 22) and CT/MRI (n = 8). The clinical questions included following regions (more than one region per case possible): neurocranium (n = 42), neck (n = 13), lung and mediastinum (n = 24), abdomen (n = 181), and pelvis (n = 65). In 92.6% of all cases (n = 253), image fusion was technically successful. Image fusion was able to improve sensitivity and specificity of the single modality, or to add important diagnostic information. Image fusion was problematic in cases of different body positions between the two imaging modalities or different positions of mobile organs. In 37.9% of the cases, image fusion added clinically relevant information compared to the single modality. Conclusion: For clinical questions concerning liver, pancreas, rectum, neck, or neurocranium, image fusion is a reliable method suitable for routine clinical application. Organ motion still limits its feasibility and routine use in other areas (e.g., thorax). (orig.)

  18. The Effect of Multispectral Image Fusion Enhancement on Human Efficiency

    Science.gov (United States)

    2017-03-20

    and discrete wavelet transformation (DWT). A seventh function was added after we noticed a number of cases where PCA produced uninterpretable...component analysis and adjusted PCA Principal component analysis (PCA) is a general math - ematical technique that transforms a set of potentially correlated...equivalent to sampling the image with Laplacian operators of many scales, which tends to enhance salient image features. Discrete wavelet transform The

  19. The fusion of large scale classified side-scan sonar image mosaics.

    Science.gov (United States)

    Reed, Scott; Tena, Ruiz Ioseba; Capus, Chris; Petillot, Yvan

    2006-07-01

    This paper presents a unified framework for the creation of classified maps of the seafloor from sonar imagery. Significant challenges in photometric correction, classification, navigation and registration, and image fusion are addressed. The techniques described are directly applicable to a range of remote sensing problems. Recent advances in side-scan data correction are incorporated to compensate for the sonar beam pattern and motion of the acquisition platform. The corrected images are segmented using pixel-based textural features and standard classifiers. In parallel, the navigation of the sonar device is processed using Kalman filtering techniques. A simultaneous localization and mapping framework is adopted to improve the navigation accuracy and produce georeferenced mosaics of the segmented side-scan data. These are fused within a Markovian framework and two fusion models are presented. The first uses a voting scheme regularized by an isotropic Markov random field and is applicable when the reliability of each information source is unknown. The Markov model is also used to inpaint regions where no final classification decision can be reached using pixel level fusion. The second model formally introduces the reliability of each information source into a probabilistic model. Evaluation of the two models using both synthetic images and real data from a large scale survey shows significant quantitative and qualitative improvement using the fusion approach.

  20. Research on Remote Sensing Image Classification Based on Feature Level Fusion

    Science.gov (United States)

    Yuan, L.; Zhu, G.

    2018-04-01

    Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

  1. Patient repositioning in prostate conformal radiotherapy by image fusion

    International Nuclear Information System (INIS)

    Betrouni, Nacim

    2004-01-01

    This research thesis first proposes an overview of imaging modalities which are generally used in radiotherapy, and briefly presents operation principles for ultrasound scans, scanners and MRI. The issue of patient repositioning in radiotherapy is then introduced, and already proposed solutions are presented. In the next part, the author addresses space location and ultrasound-based location, with a brief overview of methods used to track the displacements of a mobile object, in this case an ultrasound probe, and calibration. Then, after a presentation of the adopted method, and a discussion of published works related to contour extraction and to filtering and noise reduction methods in ultrasound imagery, the author addresses the issue of prostate segmentation based on ultrasound images. The next part deals with image registration with an overview of available methods and tools. A method of registration of pre-operation images obtained by MRI or scanner, and of intra-operation ultrasound images is proposed for a real-time registration. This method is aimed at supporting patient repositioning during prostate conformal radiotherapy

  2. Image Fusion Based on the Self-Organizing Feature Map Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhaoli; SUN Shenghe

    2001-01-01

    This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).

  3. Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods.

    Science.gov (United States)

    Cha, Dong Ik; Lee, Min Woo; Kim, Ah Yeong; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

    2017-11-01

    Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3-16 s] vs. 32 s [range, 21-38 s]; P auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0-84.6 mm] vs. 18.2 mm [6.7-73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7-9.9 mm] vs. 5.8 mm [range, 2.0-13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2-3] vs. 1 [range, 1-2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.

  4. Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

    Science.gov (United States)

    Restaino, Rocco; Vivone, Gemine; Dalla Mura, Mauro; Chanussot, Jocelyn

    2016-04-20

    Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor.

  5. Spatiotemporal Fusion of Remote Sensing Images with Structural Sparsity and Semi-Coupled Dictionary Learning

    Directory of Open Access Journals (Sweden)

    Jingbo Wei

    2016-12-01

    Full Text Available Fusion of remote sensing images with different spatial and temporal resolutions is highly needed by diverse earth observation applications. A small number of spatiotemporal fusion methods using sparse representation appear to be more promising than traditional linear mixture methods in reflecting abruptly changing terrestrial content. However, one of the main difficulties is that the results of sparse representation have reduced expressional accuracy; this is due in part to insufficient prior knowledge. For remote sensing images, the cluster and joint structural sparsity of the sparse coefficients could be employed as a priori knowledge. In this paper, a new optimization model is constructed with the semi-coupled dictionary learning and structural sparsity to predict the unknown high-resolution image from known images. Specifically, the intra-block correlation and cluster-structured sparsity are considered for single-channel reconstruction, and the inter-band similarity of joint-structured sparsity is considered for multichannel reconstruction, and both are implemented with block sparse Bayesian learning. The detailed optimization steps are given iteratively. In the experimental procedure, the red, green, and near-infrared bands of Landsat-7 and Moderate Resolution Imaging Spectrometer (MODIS satellites are put to fusion with root mean square errors to check the prediction accuracy. It can be concluded from the experiment that the proposed methods can produce higher quality than state-of-the-art methods.

  6. Group-sparse representation with dictionary learning for medical image denoising and fusion.

    Science.gov (United States)

    Li, Shutao; Yin, Haitao; Fang, Leyuan

    2012-12-01

    Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

  7. Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Angel D. Sappa

    2016-06-01

    Full Text Available This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR and Long Wave InfraRed (LWIR.

  8. Multispectral image feature fusion for detecting land mines

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Fields, D.J.; Sherwood, R.J. [Lawrence Livermore National Lab., CA (United States)] [and others

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  9. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Directory of Open Access Journals (Sweden)

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  10. Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

    Directory of Open Access Journals (Sweden)

    Peter Kampmann

    2014-04-01

    Full Text Available With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach.

  11. Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

    Directory of Open Access Journals (Sweden)

    Qi Chen

    2013-12-01

    Full Text Available Automatic image registration (AIR has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system.

  12. Experimental verification of a novel MEMS multi-modal vibration energy harvester for ultra-low power remote sensing nodes

    Science.gov (United States)

    Iannacci, J.; Sordo, G.; Serra, E.; Kucera, M.; Schmid, U.

    2015-05-01

    In this work, we discuss the verification and preliminary experimental characterization of a MEMS-based vibration Energy Harvester (EH) design. The device, named Four-Leaf Clover (FLC), is based on a circular-shaped mechanical resonator with four petal-like mass-spring cascaded systems. This solution introduces several mechanical Degrees of Freedom (DOFs), and therefore enables multiple resonant modes and deformation shapes in the vibrations frequency range of interest. The target is to realize a wideband multi-modal EH-MEMS device, that overcomes the typical narrowband working characteristics of standard cantilevered EHs, by ensuring flexible and adaptable power source to ultra-low power electronics for integrated remote sensing nodes (e.g. Wireless Sensor Networks - WSNs) in the Internet of Things (IoT) scenario, aiming to self-powered and energy autonomous smart systems. Finite Element Method simulations of the FLC EH-MEMS show the presence of several resonant modes for vibrations up to 4-5 kHz, and level of converted power up to a few μW at resonance and in closed-loop conditions (i.e. with resistive load). On the other hand, the first experimental tests of FLC fabricated samples, conducted with a Laser Doppler Vibrometer (LDV), proved the presence of several resonant modes, and allowed to validate the accuracy of the FEM modeling method. Such a good accordance holds validity for what concerns the coupled field behavior of the FLC EH-MEMS, as well. Both measurements and simulations performed at 190 Hz (i.e. out of resonance) showed the generation of power in the range of nW (Root Mean Square - RMS values). Further steps of this work will include the experimental characterization in a full range of vibrations, aiming to prove the whole functionality of the FLC EH-MEMS proposed design concept.

  13. Effective Beginning Handwriting Instruction: Multi-modal, Consistent Format for 2 Years, and Linked to Spelling and Composing.

    Science.gov (United States)

    Wolf, Beverly; Abbott, Robert D; Berninger, Virginia W

    2017-02-01

    In Study 1, the treatment group ( N = 33 first graders, M = 6 years 10 months, 16 girls) received Slingerland multi-modal (auditory, visual, tactile, motor through hand, and motor through mouth) manuscript (unjoined) handwriting instruction embedded in systematic spelling, reading, and composing lessons; and the control group ( N =16 first graders, M = 7 years 1 month, 7 girls) received manuscript handwriting instruction not systematically related to the other literacy activities. ANOVA showed both groups improved on automatic alphabet writing from memory; but ANCOVA with the automatic alphabet writing task as covariate showed that the treatment group improved significantly more than control group from the second to ninth month of first grade on dictated spelling and recognition of word-specific spellings among phonological foils. In Study 2 new groups received either a second year of manuscript ( N = 29, M = 7 years 8 months, 16 girls) or introduction to cursive (joined) instruction in second grade ( N = 24, M = 8 years 0 months, 11 girls) embedded in the Slingerland literacy program. ANCOVA with automatic alphabet writing as covariate showed that those who received a second year of manuscript handwriting instruction improved more on sustained handwriting over 30, 60, and 90 seconds than those who had had only one year of manuscript instruction; both groups improved in spelling and composing from the second to ninth month of second grade. Results are discussed in reference to mastering one handwriting format before introducing another format at a higher grade level and always embedding handwriting instruction in writing and reading instruction aimed at all levels of language.

  14. Multi-modal homing in sea turtles: modeling dual use of geomagnetic and chemical cues in island-finding

    Directory of Open Access Journals (Sweden)

    Courtney S Endres

    2016-02-01

    Full Text Available Sea turtles are capable of navigating across large expanses of ocean to arrive at remote islands for nesting, but how they do so has remained enigmatic. An interesting example involves green turtles (Chelonia mydas that nest on Ascension Island, a tiny land mass located approximately 2000 km from the turtles' foraging grounds along the coast of Brazil. Sensory cues that turtles are known to detect, and which might hypothetically be used to help locate Ascension Island, include the geomagnetic field, airborne odorants, and waterborne odorants. One possibility is that turtles use magnetic cues to arrive in the vicinity of the island, then use chemical cues to pinpoint its location. As a first step toward investigating this hypothesis, we used oceanic, atmospheric, and geomagnetic models to assess whether magnetic and chemical cues might plausibly be used by turtles to locate Ascension Island. Results suggest that waterborne and airborne odorants alone are insufficient to guide turtles from Brazil to Ascension, but might permit localization of the island once turtles arrive in its vicinity. By contrast, magnetic cues might lead turtles into the vicinity of the island, but would not typically permit its localization because the field shifts gradually over time. Simulations reveal, however, that the sequential use of magnetic and chemical cues can potentially provide a robust navigational strategy for locating Ascension Island. Specifically, one strategy that appears viable is following a magnetic isoline into the vicinity of Ascension Island until an odor plume emanating from the island is encountered, after which turtles might either: (1 initiate a search strategy; or (2 follow the plume to its island source. These findings are consistent with the hypothesis that sea turtles, and perhaps other marine animals, use a multi-modal navigational strategy for locating remote islands.

  15. Multi-Modal Homing in Sea Turtles: Modeling Dual Use of Geomagnetic and Chemical Cues in Island-Finding.

    Science.gov (United States)

    Endres, Courtney S; Putman, Nathan F; Ernst, David A; Kurth, Jessica A; Lohmann, Catherine M F; Lohmann, Kenneth J

    2016-01-01

    Sea turtles are capable of navigating across large expanses of ocean to arrive at remote islands for nesting, but how they do so has remained enigmatic. An interesting example involves green turtles (Chelonia mydas) that nest on Ascension Island, a tiny land mass located approximately 2000 km from the turtles' foraging grounds along the coast of Brazil. Sensory cues that turtles are known to detect, and which might hypothetically be used to help locate Ascension Island, include the geomagnetic field, airborne odorants, and waterborne odorants. One possibility is that turtles use magnetic cues to arrive in the vicinity of the island, then use chemical cues to pinpoint its location. As a first step toward investigating this hypothesis, we used oceanic, atmospheric, and geomagnetic models to assess whether magnetic and chemical cues might plausibly be used by turtles to locate Ascension Island. Results suggest that waterborne and airborne odorants alone are insufficient to guide turtles from Brazil to Ascension, but might permit localization of the island once turtles arrive in its vicinity. By contrast, magnetic cues might lead turtles into the vicinity of the island, but would not typically permit its localization because the field shifts gradually over time. Simulations reveal, however, that the sequential use of magnetic and chemical cues can potentially provide a robust navigational strategy for locating Ascension Island. Specifically, one strategy that appears viable is following a magnetic isoline into the vicinity of Ascension Island until an odor plume emanating from the island is encountered, after which turtles might either: (1) initiate a search strategy; or (2) follow the plume to its island source. These findings are consistent with the hypothesis that sea turtles, and perhaps other marine animals, use a multi-modal navigational strategy for locating remote islands.

  16. Effective Beginning Handwriting Instruction: Multi-modal, Consistent Format for 2 Years, and Linked to Spelling and Composing

    Science.gov (United States)

    Wolf, Beverly; Abbott, Robert D.; Berninger, Virginia W.

    2016-01-01

    In Study 1, the treatment group (N = 33 first graders, M = 6 years 10 months, 16 girls) received Slingerland multi-modal (auditory, visual, tactile, motor through hand, and motor through mouth) manuscript (unjoined) handwriting instruction embedded in systematic spelling, reading, and composing lessons; and the control group (N =16 first graders, M = 7 years 1 month, 7 girls) received manuscript handwriting instruction not systematically related to the other literacy activities. ANOVA showed both groups improved on automatic alphabet writing from memory; but ANCOVA with the automatic alphabet writing task as covariate showed that the treatment group improved significantly more than control group from the second to ninth month of first grade on dictated spelling and recognition of word-specific spellings among phonological foils. In Study 2 new groups received either a second year of manuscript (N = 29, M = 7 years 8 months, 16 girls) or introduction to cursive (joined) instruction in second grade (N = 24, M = 8 years 0 months, 11 girls) embedded in the Slingerland literacy program. ANCOVA with automatic alphabet writing as covariate showed that those who received a second year of manuscript handwriting instruction improved more on sustained handwriting over 30, 60, and 90 seconds than those who had had only one year of manuscript instruction; both groups improved in spelling and composing from the second to ninth month of second grade. Results are discussed in reference to mastering one handwriting format before introducing another format at a higher grade level and always embedding handwriting instruction in writing and reading instruction aimed at all levels of language. PMID:28190930

  17. Collimator design for neutron imaging of laser-fusion targets

    International Nuclear Information System (INIS)

    Sommargren, G.E.; Lerche, R.A.

    1981-01-01

    Several pinhole collimator geometries for use in neutron imaging experiments have been modeled and compared. Point spread functions are shown for a cylinder, hyperbola, intersecting cones, and a five-zone approximation to the intersecting cones. Of the geometries studied, the intersecting cones appear the most promising with respect to neutron efficiency, field of view, and isoplanatism

  18. Fusion of MODIS Images Using Kriging With External Drift

    NARCIS (Netherlands)

    Ribeiro Sales, M.H.; Souza, C.M.; Kyriakidis, P.C.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) has been used in several remote sensing studies, including land, ocean, and atmospheric applications. The advantages of this sensor are its high spectral resolution, with 36 spectral bands; its high revisiting frequency; and its public domain

  19. Polarimetric and Indoor Imaging Fusion Based on Compressive Sensing

    Science.gov (United States)

    2013-04-01

    34 in Proc. IEEE Radar Conf, Rome, Italy , May 2008. [17] M. G. Amin, F. Ahmad, W. Zhang, "A compressive sensing approach to moving target... Ferrara , J. Jackson, and M. Stuff, "Three-dimensional sparse-aperture moving-target imaging," in Proc. SPIE, vol. 6970, 2008. [43] M. Skolnik (Ed

  20. A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

    Directory of Open Access Journals (Sweden)

    Lu Guo