WorldWideScience

Sample records for fusion imaging ensemble

  1. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Sun Xun

    2016-12-01

    Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

  2. 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.

  3. 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.

  4. An Ensemble of Classifiers based Approach for Prediction of Alzheimer's Disease using fMRI Images based on Fusion of Volumetric, Textural and Hemodynamic Features

    Directory of Open Access Journals (Sweden)

    MALIK, F.

    2018-02-01

    Full Text Available Alzheimer's is a neurodegenerative disease caused by the destruction and death of brain neurons resulting in memory loss, impaired thinking ability, and in certain behavioral changes. Alzheimer disease is a major cause of dementia and eventually death all around the world. Early diagnosis of the disease is crucial which can help the victims to maintain their level of independence for comparatively longer time and live a best life possible. For early detection of Alzheimer's disease, we are proposing a novel approach based on fusion of multiple types of features including hemodynamic, volumetric and textural features of the brain. Our approach uses non-invasive fMRI with ensemble of classifiers, for the classification of the normal controls and the Alzheimer patients. For performance evaluation, ten-fold cross validation is used. Individual feature sets and fusion of features have been investigated with ensemble classifiers for successful classification of Alzheimer's patients from normal controls. It is observed that fusion of features resulted in improved results for accuracy, specificity and sensitivity.

  5. 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

  6. 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

  7. [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.

  8. 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)

  9. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  10. 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.

  11. New approach to information fusion for Lipschitz classifiers ensembles: Application in multi-channel C-OTDR-monitoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Timofeev, Andrey V.; Egorov, Dmitry V. [LPP “EqualiZoom”, Astana, 010000 (Kazakhstan)

    2016-06-08

    This paper presents new results concerning selection of an optimal information fusion formula for an ensemble of Lipschitz classifiers. The goal of information fusion is to create an integral classificatory which could provide better generalization ability of the ensemble while achieving a practically acceptable level of effectiveness. The problem of information fusion is very relevant for data processing in multi-channel C-OTDR-monitoring systems. In this case we have to effectively classify targeted events which appear in the vicinity of the monitored object. Solution of this problem is based on usage of an ensemble of Lipschitz classifiers each of which corresponds to a respective channel. We suggest a brand new method for information fusion in case of ensemble of Lipschitz classifiers. This method is called “The Weighing of Inversely as Lipschitz Constants” (WILC). Results of WILC-method practical usage in multichannel C-OTDR monitoring systems are presented.

  12. ANALYSIS OF SST IMAGES BY WEIGHTED ENSEMBLE TRANSFORM KALMAN FILTER

    OpenAIRE

    Sai , Gorthi; Beyou , Sébastien; Memin , Etienne

    2011-01-01

    International audience; This paper presents a novel, efficient scheme for the analysis of Sea Surface Temperature (SST) ocean images. We consider the estimation of the velocity fields and vorticity values from a sequence of oceanic images. The contribution of this paper lies in proposing a novel, robust and simple approach based onWeighted Ensemble Transform Kalman filter (WETKF) data assimilation technique for the analysis of real SST images, that may contain coast regions or large areas of ...

  13. Wind power application research on the fusion of the determination and ensemble prediction

    Science.gov (United States)

    Lan, Shi; Lina, Xu; Yuzhu, Hao

    2017-07-01

    The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

  14. 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.

  15. Weighted ensemble transform Kalman filter for image assimilation

    Directory of Open Access Journals (Sweden)

    Sebastien Beyou

    2013-01-01

    Full Text Available This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF proposed by Papadakis et al. (2010 for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF, incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.

  16. 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

  17. 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...

  18. 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...

  19. 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.

  20. 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

  1. Asymmetric similarity-weighted ensembles for image segmentation

    DEFF Research Database (Denmark)

    Cheplygina, V.; Van Opbroek, A.; Ikram, M. A.

    2016-01-01

    Supervised classification is widely used for image segmentation. To work effectively, these techniques need large amounts of labeled training data, that is representative of the test data. Different patient groups, different scanners or different scanning protocols can lead to differences between...... the images, thus representative data might not be available. Transfer learning techniques can be used to account for these differences, thus taking advantage of all the available data acquired with different protocols. We investigate the use of classifier ensembles, where each classifier is weighted...... and the direction of measurement needs to be chosen carefully. We also show that a point set similarity measure is robust across different studies, and outperforms state-of-the-art results on a multi-center brain tissue segmentation task....

  2. Detection of microaneurysms in retinal images using an ensemble classifier

    Directory of Open Access Journals (Sweden)

    M.M. Habib

    2017-01-01

    Full Text Available This paper introduces, and reports on the performance of, a novel combination of algorithms for automated microaneurysm (MA detection in retinal images. The presence of MAs in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR which is one of the leading causes of blindness amongst the working age population. An extensive survey of the literature is presented and current techniques in the field are summarised. The proposed technique first detects an initial set of candidates using a Gaussian Matched Filter and then classifies this set to reduce the number of false positives. A Tree Ensemble classifier is used with a set of 70 features (the most commons features in the literature. A new set of 32 MA groundtruth images (with a total of 256 labelled MAs based on images from the MESSIDOR dataset is introduced as a public dataset for benchmarking MA detection algorithms. We evaluate our algorithm on this dataset as well as another public dataset (DIARETDB1 v2.1 and compare it against the best available alternative. Results show that the proposed classifier is superior in terms of eliminating false positive MA detection from the initial set of candidates. The proposed method achieves an ROC score of 0.415 compared to 0.2636 achieved by the best available technique. Furthermore, results show that the classifier model maintains consistent performance across datasets, illustrating the generalisability of the classifier and that overfitting does not occur.

  3. Semantic Segmentation of Aerial Images with AN Ensemble of Cnns

    Science.gov (United States)

    Marmanis, D.; Wegner, J. D.; Galliani, S.; Schindler, K.; Datcu, M.; Stilla, U.

    2016-06-01

    This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recent years deep convolutional neural networks (CNNs) have emerged as the method of choice for a range of image interpretation tasks like visual recognition and object detection. Still, standard CNNs do not lend themselves to per-pixel semantic segmentation, mainly because one of their fundamental principles is to gradually aggregate information over larger and larger image regions, making it hard to disentangle contributions from different pixels. Very recently two extensions of the CNN framework have made it possible to trace the semantic information back to a precise pixel position: deconvolutional network layers undo the spatial downsampling, and Fully Convolution Networks (FCNs) modify the fully connected classification layers of the network in such a way that the location of individual activations remains explicit. We design a FCN which takes as input intensity and range data and, with the help of aggressive deconvolution and recycling of early network layers, converts them into a pixelwise classification at full resolution. We discuss design choices and intricacies of such a network, and demonstrate that an ensemble of several networks achieves excellent results on challenging data such as the ISPRS semantic labeling benchmark, using only the raw data as input.

  4. 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

  5. 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)

  6. 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....

  7. 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

  8. 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....

  9. 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.

  10. 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.

  11. Time-of-flight PET image reconstruction using origin ensembles

    Science.gov (United States)

    Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

    2015-03-01

    The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

  12. Historic photos and TLS data fusion for the 3D reconstruction of a monastery altar ensemble

    Directory of Open Access Journals (Sweden)

    K. Hanke

    2015-08-01

    Full Text Available The basis of the photogrammetric reconstruction of the altar at the monastery / church are 2 historic photos from around 1920’s as well as a 3D documentation of the church from terrestrial laser scanning. The point cloud from the laser scan was the starting point for an approximate computation of the interior and exterior orientation of that image that also contains parts of the altar area that still do exist. Using a projection of the recent geometry into the image allowed the analysis of changes of the altar ensemble since the time of image acquisition. Those parts that are still in situ are the origin for further action. Whether fragments and parts should be used further or newly positioned was decided in the next phase of reconstruction process. The focus of the first step of the workflow was at the outlines of the parts in the center of the altar. Using a monoplotting approach and assuming that the profiles are vertical and parallel to each other these object could be definitely compiled. Theses outlines also allowed an approximate determination of the interior and exterior orientation of the second historic photograph in which otherwise the complete connection to the recent altar area was missing. The side parts of the altar showed to be more complicated for reconstruction. The difference in depth of the varying edges could not be distinguished any more in the images. Such, the sequence and form of the different edges was adopted, scaled and transferred from the central part of the altar to the peripheral ones. Using this geometric information it was possible to define the necessary projection planes for the monoplotting restitution of the visible outlines. A concluding rigorous control was accomplished by back projection of the geometry into both historical images.

  13. 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.

  14. 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)

  15. 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)

  16. 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.

  17. 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

  18. A variational ensemble scheme for noisy image data assimilation

    Science.gov (United States)

    Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne

    2014-05-01

    Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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,

  5. 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

  6. 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.

  7. Contributions to Ensemble Classifiers with Image Analysis Applications

    OpenAIRE

    Ayerdi Vilches, Borja

    2015-01-01

    134 p. Ésta tesis tiene dos aspectos fundamentales, por un lado, la propuesta denuevas arquitecturas de clasificadores y, por otro, su aplicación a el análisis deimagen.Desde el punto de vista de proponer nuevas arquitecturas de clasificaciónla tesis tiene dos contribucciones principales. En primer lugar la propuestade un innovador ensemble de clasificadores basado en arquitecturas aleatorias,como pueden ser las Extreme Learning Machines (ELM), Random Forest (RF) yRotation Forest, llamado ...

  8. 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

  9. 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

  10. An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis.

    Science.gov (United States)

    Li, Shaobo; Liu, Guokai; Tang, Xianghong; Lu, Jianguang; Hu, Jianjun

    2017-07-28

    Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster-Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions.

  11. Ensembles of Novel Visual Keywords Descriptors for Image Categorization

    NARCIS (Netherlands)

    Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco

    2010-01-01

    Object recognition systems need effective image descriptors to obtain good performance levels. Currently, the most widely used image descriptor is the SIFT descriptor that computes histograms of orientation gradients around points in an image. A possible problem of this approach is that the number

  12. 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.

  13. 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)

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Ensemble modelling of nitrogen fluxes: data fusion for a Swedish meso-scale catchment

    Directory of Open Access Journals (Sweden)

    J.-F. Exbrayat

    2010-12-01

    Full Text Available Model predictions of biogeochemical fluxes at the landscape scale are highly uncertain, both with respect to stochastic (parameter and structural uncertainty. In this study 5 different models (LASCAM, LASCAM-S, a self-developed tool, SWAT and HBV-N-D designed to simulate hydrological fluxes as well as mobilisation and transport of one or several nitrogen species were applied to the mesoscale River Fyris catchment in mid-eastern Sweden.

    Hydrological calibration against 5 years of recorded daily discharge at two stations gave highly variable results with Nash-Sutcliffe Efficiency (NSE ranging between 0.48 and 0.83. Using the calibrated hydrological parameter sets, the parameter uncertainty linked to the nitrogen parameters was explored in order to cover the range of possible predictions of exported loads for 3 nitrogen species: nitrate (NO3, ammonium (NH4 and total nitrogen (Tot-N. For each model and each nitrogen species, predictions were ranked in two different ways according to the performance indicated by two different goodness-of-fit measures: the coefficient of determination R2 and the root mean square error RMSE. A total of 2160 deterministic Single Model Ensembles (SME was generated using an increasing number of members (from the 2 best to the 10 best single predictions. Finally the best SME for each model, nitrogen species and discharge station were selected and merged into 330 different Multi-Model Ensembles (MME. The evolution of changes in R2 and RMSE was used as a performance descriptor of the ensemble procedure.

    In each studied case, numerous ensemble merging schemes were identified which outperformed any of their members. Improvement rates were generally higher when worse members were introduced. The highest improvements were achieved for the nitrogen SMEs compiled with multiple linear regression models with R2 selected members, which

  19. R-FCN Object Detection Ensemble based on Object Resolution and Image Quality

    DEFF Research Database (Denmark)

    Rasmussen, Christoffer Bøgelund; Nasrollahi, Kamal; Moeslund, Thomas B.

    2017-01-01

    Object detection can be difficult due to challenges such as variations in objects both inter- and intra-class. Additionally, variations can also be present between images. Based on this, research was conducted into creating an ensemble of Region-based Fully Convolutional Networks (R-FCN) object d...

  20. 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

  1. 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...

  2. 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.

  3. 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

  4. [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.

  5. 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.

  6. Ensemble Methods

    Science.gov (United States)

    Re, Matteo; Valentini, Giorgio

    2012-03-01

    Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been

  7. 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).

  8. 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

  9. 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.

  10. 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.

  11. An Ensemble of Deep Support Vector Machines for Image Categorization

    NARCIS (Netherlands)

    Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco

    2009-01-01

    This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for training another SVM at the next

  12. 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.

  13. 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.

  14. 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

  15. Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

    Science.gov (United States)

    Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

    2018-03-01

    An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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)

  1. 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....

  2. Discrimination of Breast Tumors in Ultrasonic Images by Classifier Ensemble Trained with AdaBoost

    Science.gov (United States)

    Takemura, Atsushi; Shimizu, Akinobu; Hamamoto, Kazuhiko

    In this paper, we propose a novel method for acurate automated discrimination of breast tumors (carcinoma, fibroadenoma, and cyst). We defined 199 features related to diagnositic observations noticed when a doctor judges breast tumors, such as internal echo, shape, and boundary echo. These features included novel features based on a parameter of log-compressed K distribution, which reflect physical characteristics of ultrasonic B-mode imaging. Furthermore, we propose a discrimination method of breast tumors by using an ensemble classifier based on the multi-class AdaBoost algorithm with effective features selection. Verification by analyzing 200 carcinomas, 30 fibroadenomas and 30 cycts showed the usefulness of the newly defined features and the effectiveness of the discrimination by using an ensemble classifier trained by AdaBoost.

  3. 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.

  4. 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).

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images

    International Nuclear Information System (INIS)

    Linares-Rodriguez, Alvaro; Ruiz-Arias, José Antonio; Pozo-Vazquez, David; Tovar-Pescador, Joaquin

    2013-01-01

    An optimized artificial neural network ensemble model is built to estimate daily global solar radiation over large areas. The model uses clear-sky estimates and satellite images as input variables. Unlike most studies using satellite imagery based on visible channels, our model also exploits all information within infrared channels of the Meteosat 9 satellite. A genetic algorithm is used to optimize selection of model inputs, for which twelve are selected – eleven 3-km Meteosat 9 channels and one clear-sky term. The model is validated in Andalusia (Spain) from January 2008 through December 2008. Measured data from 83 stations across the region are used, 65 for training and 18 independent ones for testing the model. At the latter stations, the ensemble model yields an overall root mean square error of 6.74% and correlation coefficient of 99%; the generated estimates are relatively accurate and errors spatially uniform. The model yields reliable results even on cloudy days, improving on current models based on satellite imagery. - Highlights: • Daily solar radiation data are generated using an artificial neural network ensemble. • Eleven Meteosat channels observations and a clear sky term are used as model inputs. • Model exploits all information within infrared Meteosat channels. • Measured data for a year from 83 ground stations are used. • The proposed approach has better performance than existing models on daily basis

  11. 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.

  12. 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...

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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...

  19. 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

  20. Fast image reconstruction for Compton camera using stochastic origin ensemble approach.

    Science.gov (United States)

    Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna

    2011-01-01

    Compton camera has been proposed as a potential imaging tool in astronomy, industry, homeland security, and medical diagnostics. Due to the inherent geometrical complexity of Compton camera data, image reconstruction of distributed sources can be ineffective and/or time-consuming when using standard techniques such as filtered backprojection or maximum likelihood-expectation maximization (ML-EM). In this article, the authors demonstrate a fast reconstruction of Compton camera data using a novel stochastic origin ensembles (SOE) approach based on Markov chains. During image reconstruction, the origins of the measured events are randomly assigned to locations on conical surfaces, which are the Compton camera analogs of lines-of-responses in PET. Therefore, the image is defined as an ensemble of origin locations of all possible event origins. During the course of reconstruction, the origins of events are stochastically moved and the acceptance of the new event origin is determined by the predefined acceptance probability, which is proportional to the change in event density. For example, if the event density at the new location is higher than in the previous location, the new position is always accepted. After several iterations, the reconstructed distribution of origins converges to a quasistationary state which can be voxelized and displayed. Comparison with the list-mode ML-EM reveals that the postfiltered SOE algorithm has similar performance in terms of image quality while clearly outperforming ML-EM in relation to reconstruction time. In this study, the authors have implemented and tested a new image reconstruction algorithm for the Compton camera based on the stochastic origin ensembles with Markov chains. The algorithm uses list-mode data, is parallelizable, and can be used for any Compton camera geometry. SOE algorithm clearly outperforms list-mode ML-EM for simple Compton camera geometry in terms of reconstruction time. The difference in computational time

  1. 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.

  2. 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 ...

  3. 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

  4. Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

    Science.gov (United States)

    Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

    2017-10-01

    High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

  5. 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

  6. The role of ensemble-based statistics in variational assimilation of cloud-affected observations from infrared imagers

    Science.gov (United States)

    Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris

    2017-04-01

    Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the

  7. 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

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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)

  14. 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

  15. 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.

  16. 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.

  17. 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)

  18. 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.

  19. 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

  20. 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)

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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)

  8. 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.

  9. 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

  10. [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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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).

  16. 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.

  17. 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....

  18. 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

  19. 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....

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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...

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. AN ENSEMBLE TEMPLATE MATCHING AND CONTENT-BASED IMAGE RETRIEVAL SCHEME TOWARDS EARLY STAGE DETECTION OF MELANOMA

    Directory of Open Access Journals (Sweden)

    Spiros Kostopoulos

    2016-12-01

    Full Text Available Malignant melanoma represents the most dangerous type of skin cancer. In this study we present an ensemble classification scheme, employing the mutual information, the cross-correlation and the clustering based on proximity of image features methods, for early stage assessment of melanomas on plain photography images. The proposed scheme performs two main operations. First, it retrieves the most similar, to the unknown case, image samples from an available image database with verified benign moles and malignant melanoma cases. Second, it provides an automated estimation regarding the nature of the unknown image sample based on the majority of the most similar images retrieved from the available database. Clinical material comprised 75 melanoma and 75 benign plain photography images collected from publicly available dermatological atlases. Results showed that the ensemble scheme outperformed all other methods tested in terms of accuracy with 94.9±1.5%, following an external cross-validation evaluation methodology. The proposed scheme may benefit patients by providing a second opinion consultation during the self-skin examination process and the physician by providing a second opinion estimation regarding the nature of suspicious moles that may assist towards decision making especially for ambiguous cases, safeguarding, in this way from potential diagnostic misinterpretations.

  10. 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...

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. Object-Based Change Detection in Urban Areas from High Spatial Resolution Images Based on Multiple Features and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2018-02-01

    Full Text Available To improve the accuracy of change detection in urban areas using bi-temporal high-resolution remote sensing images, a novel object-based change detection scheme combining multiple features and ensemble learning is proposed in this paper. Image segmentation is conducted to determine the objects in bi-temporal images separately. Subsequently, three kinds of object features, i.e., spectral, shape and texture, are extracted. Using the image differencing process, a difference image is generated and used as the input for nonlinear supervised classifiers, including k-nearest neighbor, support vector machine, extreme learning machine and random forest. Finally, the results of multiple classifiers are integrated using an ensemble rule called weighted voting to generate the final change detection result. Experimental results of two pairs of real high-resolution remote sensing datasets demonstrate that the proposed approach outperforms the traditional methods in terms of overall accuracy and generates change detection maps with a higher number of homogeneous regions in urban areas. Moreover, the influences of segmentation scale and the feature selection strategy on the change detection performance are also analyzed and discussed.

  2. 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.

  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. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    International Nuclear Information System (INIS)

    Guo, Yanrong; Shao, Yeqin; Gao, Yaozong; Price, True; Oto, Aytekin; Shen, Dinggang

    2014-01-01

    different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images

  5. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    Science.gov (United States)

    Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

    2014-01-01

    patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images. PMID:24989402

  6. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.

    Science.gov (United States)

    Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

    2014-07-01

    prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.

  7. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yanrong; Shao, Yeqin [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong; Price, True [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Computer Science, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Oto, Aytekin [Department of Radiology, Section of Urology, University of Chicago, Illinois 60637 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

    2014-07-15

    different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.

  8. 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).

  9. 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).

  10. 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

  11. A Clustering-Oriented Closeness Measure Based on Neighborhood Chain and Its Application in the Clustering Ensemble Framework Based on the Fusion of Different Closeness Measures

    Directory of Open Access Journals (Sweden)

    Shaoyi Liang

    2017-09-01

    Full Text Available Closeness measures are crucial to clustering methods. In most traditional clustering methods, the closeness between data points or clusters is measured by the geometric distance alone. These metrics quantify the closeness only based on the concerned data points’ positions in the feature space, and they might cause problems when dealing with clustering tasks having arbitrary clusters shapes and different clusters densities. In this paper, we first propose a novel Closeness Measure between data points based on the Neighborhood Chain (CMNC. Instead of using geometric distances alone, CMNC measures the closeness between data points by quantifying the difficulty for one data point to reach another through a chain of neighbors. Furthermore, based on CMNC, we also propose a clustering ensemble framework that combines CMNC and geometric-distance-based closeness measures together in order to utilize both of their advantages. In this framework, the “bad data points” that are hard to cluster correctly are identified; then different closeness measures are applied to different types of data points to get the unified clustering results. With the fusion of different closeness measures, the framework can get not only better clustering results in complicated clustering tasks, but also higher efficiency.

  12. 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....

  13. 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

  14. 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.

  15. 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)

  16. 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

  17. 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.

  18. Classifying Physical Morphology of Cocoa Beans Digital Images using Multiclass Ensemble Least-Squares Support Vector Machine

    Science.gov (United States)

    Lawi, Armin; Adhitya, Yudhi

    2018-03-01

    The objective of this research is to determine the quality of cocoa beans through morphology of their digital images. Samples of cocoa beans were scattered on a bright white paper under a controlled lighting condition. A compact digital camera was used to capture the images. The images were then processed to extract their morphological parameters. Classification process begins with an analysis of cocoa beans image based on morphological feature extraction. Parameters for extraction of morphological or physical feature parameters, i.e., Area, Perimeter, Major Axis Length, Minor Axis Length, Aspect Ratio, Circularity, Roundness, Ferret Diameter. The cocoa beans are classified into 4 groups, i.e.: Normal Beans, Broken Beans, Fractured Beans, and Skin Damaged Beans. The model of classification used in this paper is the Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM), a proposed improvement model of SVM using ensemble method in which the separate hyperplanes are obtained by least square approach and the multiclass procedure uses One-Against- All method. The result of our proposed model showed that the classification with morphological feature input parameters were accurately as 99.705% for the four classes, respectively.

  19. 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.

  20. 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.

  1. 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...

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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)

  8. 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.

  9. 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.

  10. 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

  11. 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)

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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).

  3. 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)

  4. 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.

  5. 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)

  6. 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.

  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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. [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.

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. NYYD Ensemble

    Index Scriptorium Estoniae

    2002-01-01

    NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx

  7. Evaluation of Origin Ensemble algorithm for image reconstruction for pixelated solid-state detectors with large number of channels

    Science.gov (United States)

    Kolstein, M.; De Lorenzo, G.; Mikhaylova, E.; Chmeissani, M.; Ariño, G.; Calderón, Y.; Ozsahin, I.; Uzun, D.

    2013-04-01

    The Voxel Imaging PET (VIP) Pathfinder project intends to show the advantages of using pixelated solid-state technology for nuclear medicine applications. It proposes designs for Positron Emission Tomography (PET), Positron Emission Mammography (PEM) and Compton gamma camera detectors with a large number of signal channels (of the order of 106). For PET scanners, conventional algorithms like Filtered Back-Projection (FBP) and Ordered Subset Expectation Maximization (OSEM) are straightforward to use and give good results. However, FBP presents difficulties for detectors with limited angular coverage like PEM and Compton gamma cameras, whereas OSEM has an impractically large time and memory consumption for a Compton gamma camera with a large number of channels. In this article, the Origin Ensemble (OE) algorithm is evaluated as an alternative algorithm for image reconstruction. Monte Carlo simulations of the PET design are used to compare the performance of OE, FBP and OSEM in terms of the bias, variance and average mean squared error (MSE) image quality metrics. For the PEM and Compton camera designs, results obtained with OE are presented.

  8. 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.

  9. 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.

  10. Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images

    Science.gov (United States)

    Ebadi, Ashkan; Dalboni da Rocha, Josué L.; Nagaraju, Dushyanth B.; Tovar-Moll, Fernanda; Bramati, Ivanei; Coutinho, Gabriel; Sitaram, Ranganatha; Rashidi, Parisa

    2017-01-01

    The human brain is a complex network of interacting regions. The gray matter regions of brain are interconnected by white matter tracts, together forming one integrative complex network. In this article, we report our investigation about the potential of applying brain connectivity patterns as an aid in diagnosing Alzheimer's disease and Mild Cognitive Impairment (MCI). We performed pattern analysis of graph theoretical measures derived from Diffusion Tensor Imaging (DTI) data representing structural brain networks of 45 subjects, consisting of 15 patients of Alzheimer's disease (AD), 15 patients of MCI, and 15 healthy subjects (CT). We considered pair-wise class combinations of subjects, defining three separate classification tasks, i.e., AD-CT, AD-MCI, and CT-MCI, and used an ensemble classification module to perform the classification tasks. Our ensemble framework with feature selection shows a promising performance with classification accuracy of 83.3% for AD vs. MCI, 80% for AD vs. CT, and 70% for MCI vs. CT. Moreover, our findings suggest that AD can be related to graph measures abnormalities at Brodmann areas in the sensorimotor cortex and piriform cortex. In this way, node redundancy coefficient and load centrality in the primary motor cortex were recognized as good indicators of AD in contrast to MCI. In general, load centrality, betweenness centrality, and closeness centrality were found to be the most relevant network measures, as they were the top identified features at different nodes. The present study can be regarded as a “proof of concept” about a procedure for the classification of MRI markers between AD dementia, MCI, and normal old individuals, due to the small and not well-defined groups of AD and MCI patients. Future studies with larger samples of subjects and more sophisticated patient exclusion criteria are necessary toward the development of a more precise technique for clinical diagnosis. PMID:28293162

  11. 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

  12. 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.

  13. 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.

  14. 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...

  15. 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...

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 3D soil water nowcasting using electromagnetic conductivity imaging and the ensemble Kalman filter

    Science.gov (United States)

    Huang, Jingyi; McBratney, Alex B.; Minasny, Budiman; Triantafilis, John

    2017-06-01

    Mapping and immediate forecasting of soil water content (θ) and its movement can be challenging. Although inversion of apparent electrical conductivity (ECa) measured by electromagnetic induction to calculate depth-specific electrical conductivity (σ) has been used, it is difficult to apply it across a field. In this paper we use a calibration established along a transect, across a 3.94-ha field with varying soil texture, using an ensemble Kalman filter (EnKF) to monitor and nowcast the 3-dimensional θ dynamics on 16 separate days over a period of 38 days. The EnKF combined a physical model fitted with θ measured by soil moisture sensors and an Artificial Neural Network model comprising σ generated by quasi-3d inversions of DUALEM-421S ECa data. Results showed that the distribution of θ was controlled by soil texture, topography, and vegetation. Soil water dried fastest at the beginning after the initial irrigation event and decreased with time and soil depth, which was consistent with classical soil drying theory and experiments. It was also found that the soil dried fastest in the loamy and duplex soils present in the field, which was attributable to deep drainage and preferential flow. It was concluded that the EnKF approach can be used to improve the irrigation efficiency by applying variable irrigation rates across the field. In addition, soil water status can be nowcasted across large spatial extents using this method with weather forecast information, which will provide guidance to farmers for real-time irrigation management.

  3. An ensemble deep learning based approach for red lesion detection in fundus images.

    Science.gov (United States)

    Orlando, José Ignacio; Prokofyeva, Elena; Del Fresno, Mariana; Blaschko, Matthew B

    2018-01-01

    Diabetic retinopathy (DR) is one of the leading causes of preventable blindness in the world. Its earliest sign are red lesions, a general term that groups both microaneurysms (MAs) and hemorrhages (HEs). In daily clinical practice, these lesions are manually detected by physicians using fundus photographs. However, this task is tedious and time consuming, and requires an intensive effort due to the small size of the lesions and their lack of contrast. Computer-assisted diagnosis of DR based on red lesion detection is being actively explored due to its improvement effects both in clinicians consistency and accuracy. Moreover, it provides comprehensive feedback that is easy to assess by the physicians. Several methods for detecting red lesions have been proposed in the literature, most of them based on characterizing lesion candidates using hand crafted features, and classifying them into true or false positive detections. Deep learning based approaches, by contrast, are scarce in this domain due to the high expense of annotating the lesions manually. In this paper we propose a novel method for red lesion detection based on combining both deep learned and domain knowledge. Features learned by a convolutional neural network (CNN) are augmented by incorporating hand crafted features. Such ensemble vector of descriptors is used afterwards to identify true lesion candidates using a Random Forest classifier. We empirically observed that combining both sources of information significantly improve results with respect to using each approach separately. Furthermore, our method reported the highest performance on a per-lesion basis on DIARETDB1 and e-ophtha, and for screening and need for referral on MESSIDOR compared to a second human expert. Results highlight the fact that integrating manually engineered approaches with deep learned features is relevant to improve results when the networks are trained from lesion-level annotated data. An open source implementation of our

  4. 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

  5. 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.

  6. 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

  7. 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)

  8. 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

  9. Ensembl 2004.

    Science.gov (United States)

    Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

    2004-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

  10. 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.

  11. Ensembl 2017

    OpenAIRE

    Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Gir?n, Carlos Garc?a; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.

    2016-01-01

    Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access ...

  12. Ensemble Sampling

    OpenAIRE

    Lu, Xiuyuan; Van Roy, Benjamin

    2017-01-01

    Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.)

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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).

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Classification and localization of early-stage Alzheimer's disease in magnetic resonance images using a patch-based classifier ensemble

    International Nuclear Information System (INIS)

    Simoes, Rita; Slump, Cornelis H.; Cappellen van Walsum, Anne-Marie van

    2014-01-01

    Classification methods have been proposed to detect Alzheimer's disease (AD) using magnetic resonance images. Most rely on features such as the shape/volume of brain structures that need to be defined a priori. In this work, we propose a method that does not require either the segmentation of specific brain regions or the nonlinear alignment to a template. Besides classification, we also analyze which brain regions are discriminative between a group of normal controls and a group of AD patients. We perform 3D texture analysis using Local Binary Patterns computed at local image patches in the whole brain, combined in a classifier ensemble. We evaluate our method in a publicly available database including very mild-to-mild AD subjects and healthy elderly controls. For the subject cohort including only mild AD subjects, the best results are obtained using a combination of large (30 x 30 x 30 and 40 x 40 x 40 voxels) patches. A spatial analysis on the best performing patches shows that these are located in the medial-temporal lobe and in the periventricular regions. When very mild AD subjects are included in the dataset, the small (10 x 10 x 10 voxels) patches perform best, with the most discriminative ones being located near the left hippocampus. We show that our method is able not only to perform accurate classification, but also to localize discriminative brain regions, which are in accordance with the medical literature. This is achieved without the need to segment-specific brain structures and without performing nonlinear registration to a template, indicating that the method may be suitable for a clinical implementation that can help to diagnose AD at an earlier stage.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

    Directory of Open Access Journals (Sweden)

    Lu Guo

    Full Text Available To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors.A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT and tri-modality (MRI/CT/PET image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV, the average distance between surface and centroid (ADSC, and the local standard deviation (SDlocal. Analysis of COV was also performed to evaluate intra-observer volume variation.The inter-observer variation analysis showed that, the mean COV was 0.14(± 0.09 and 0.07(± 0.01 for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05 with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm and patient 3 (from 0.42 cm to 0.36 cm with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00 with the tri-modality method as compared with using the dual-modality method.With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy.

  4. Evaluation of electrode position in deep brain stimulation by image fusion (MRI and CT)

    Energy Technology Data Exchange (ETDEWEB)

    Barnaure, I.; Lovblad, K.O.; Vargas, M.I. [Geneva University Hospital, Department of Neuroradiology, Geneva 14 (Switzerland); Pollak, P.; Horvath, J.; Boex, C.; Burkhard, P. [Geneva University Hospital, Department of Neurology, Geneva (Switzerland); Momjian, S. [Geneva University Hospital, Department of Neurosurgery, Geneva (Switzerland); Remuinan, J. [Geneva University Hospital, Department of Radiology, Geneva (Switzerland)

    2015-09-15

    Imaging has an essential role in the evaluation of correct positioning of electrodes implanted for deep brain stimulation (DBS). Although MRI offers superior anatomic visualization of target sites, there are safety concerns in patients with implanted material; imaging guidelines are inconsistent and vary. The fusion of postoperative CT with preoperative MRI images can be an alternative for the assessment of electrode positioning. The purpose of this study was to assess the accuracy of measurements realized on fused images (acquired without a stereotactic frame) using a manufacturer-provided software. Data from 23 Parkinson's disease patients who underwent bilateral electrode placement for subthalamic nucleus (STN) DBS were acquired. Preoperative high-resolution T2-weighted sequences at 3 T, and postoperative CT series were fused using a commercially available software. Electrode tip position was measured on the obtained images in three directions (in relation to the midline, the AC-PC line and an AC-PC line orthogonal, respectively) and assessed in relation to measures realized on postoperative 3D T1 images acquired at 1.5 T. Mean differences between measures carried out on fused images and on postoperative MRI lay between 0.17 and 0.97 mm. Fusion of CT and MRI images provides a safe and fast technique for postoperative assessment of electrode position in DBS. (orig.)

  5. A New Fusion Technique of Remote Sensing Images for Land Use/Cover

    Institute of Scientific and Technical Information of China (English)

    WU Lian-Xi; SUN Bo; ZHOU Sheng-Lu; HUANG Shu-E; ZHAO Qi-Guo

    2004-01-01

    In China,accelerating industrialization and urbanization following high-speed economic development and population increases have greatly impacted land use/cover changes,making it imperative to obtain accurate and up to date information on changes so as to evaluate their environmental effects. The major purpose of this study was to develop a new method to fuse lower spatial resolution multispectral satellite images with higher spatial resolution panchromatic ones to assist in land use/cover mapping. An algorithm of a new fusion method known as edge enhancement intensity modulation (EEIM) was proposed to merge two optical image data sets of different spectral ranges. The results showed that the EEIM image was quite similar in color to lower resolution multispectral images,and the fused product was better able to preserve spectral information. Thus,compared to conventional approaches,the spectral distortion of the fused images was markedly reduced. Therefore,the EEIM fusion method could be utilized to fuse remote sensing data from the same or different sensors,including TM images and SPOT5 panchromatic images,providing high quality land use/cover images.

  6. of Hypoxia-Inducible Factor-1α Activity by the Fusion of High-Resolution SPECT and Morphological Imaging Tests

    Directory of Open Access Journals (Sweden)

    Hirofumi Fujii

    2012-01-01

    Full Text Available Purpose. We aimed to clearly visualize heterogeneous distribution of hypoxia-inducible factor 1α (HIF activity in tumor tissues in vivo. Methods. We synthesized of 125I-IPOS, a 125I labeled chimeric protein probe, that would visualize HIF activity. The biodistribution of 125I-IPOS in FM3A tumor-bearing mice was evaluated. Then, the intratumoral localization of this probe was observed by autoradiography, and it was compared with histopathological findings. The distribution of 125I-IPOS in tumors was imaged by a small animal SPECT/CT scanner. The obtained in vivo SPECT-CT fusion images were compared with ex vivo images of excised tumors. Fusion imaging with MRI was also examined. Results. 125I-IPOS well accumulated in FM3A tumors. The intratumoral distribution of 125I-IPOS by autoradiography was quite heterogeneous, and it partially overlapped with that of pimonidazole. High-resolution SPECT-CT fusion images successfully demonstrated the heterogeneity of 125I-IPOS distribution inside tumors. SPECT-MRI fusion images could give more detailed information about the intratumoral distribution of 125I-IPOS. Conclusion. High-resolution SPECT images successfully demonstrated heterogeneous intratumoral distribution of 125I-IPOS. SPECT-CT fusion images, more favorably SPECT-MRI fusion images, would be useful to understand the features of heterogeneous intratumoral expression of HIF activity in vivo.

  7. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  8. PET/CT. Dose-escalated image fusion?

    International Nuclear Information System (INIS)

    Brix, G.; Beyer, T.

    2005-01-01

    Clinical studies demonstrate a gain in diagnostic accuracy by employing combined PET/CT instead of separate CT and PET imaging. However, whole-body PET/CT examinations result in a comparatively high radiation burden to patients and thus require a proper justification and optimization to avoid repeated exposure or over-exposure of patients. This review article summarizes relevant data concerning radiation exposure of patients resulting from the different components of a combined PET/CT examination and presents different imaging strategies that can help to balance the diagnostic needs and the radiation protection requirements. In addition various dose reduction measures are discussed, some of which can be adopted from CT practice, while others mandate modifications to the existing hard- and software of PET/CT systems. (orig.)

  9. Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images.

    Science.gov (United States)

    Favazza, Christopher P; Gorny, Krzysztof R; Callstrom, Matthew R; Kurup, Anil N; Washburn, Michael; Trester, Pamela S; Fowler, Charles L; Hangiandreou, Nicholas J

    2018-05-21

    We present the development of a two-component magnetic resonance (MR) fiducial system, that is, a fiducial marker device combined with an auto-segmentation algorithm, designed to be paired with existing ultrasound probe tracking and image fusion technology to automatically fuse MR and ultrasound (US) images. The fiducial device consisted of four ~6.4 mL cylindrical wells filled with 1 g/L copper sulfate solution. The algorithm was designed to automatically segment the device in clinical abdominal MR images. The algorithm's detection rate and repeatability were investigated through a phantom study and in human volunteers. The detection rate was 100% in all phantom and human images. The center-of-mass of the fiducial device was robustly identified with maximum variations of 2.9 mm in position and 0.9° in angular orientation. In volunteer images, average differences between algorithm-measured inter-marker spacings and actual separation distances were 0.53 ± 0.36 mm. "Proof-of-concept" automatic MR-US fusions were conducted with sets of images from both a phantom and volunteer using a commercial prototype system, which was built based on the above findings. Image fusion accuracy was measured to be within 5 mm for breath-hold scanning. These results demonstrate the capability of this approach to automatically fuse US and MR images acquired across a wide range of clinical abdominal pulse sequences. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

  10. Three-dimensional Image Fusion Guidance for Transjugular Intrahepatic Portosystemic Shunt Placement.

    Science.gov (United States)

    Tacher, Vania; Petit, Arthur; Derbel, Haytham; Novelli, Luigi; Vitellius, Manuel; Ridouani, Fourat; Luciani, Alain; Rahmouni, Alain; Duvoux, Christophe; Salloum, Chady; Chiaradia, Mélanie; Kobeiter, Hicham

    2017-11-01

    To assess the safety, feasibility and effectiveness of image fusion guidance with pre-procedural portal phase computed tomography with intraprocedural fluoroscopy for transjugular intrahepatic portosystemic shunt (TIPS) placement. All consecutive cirrhotic patients presenting at our interventional unit for TIPS creation from January 2015 to January 2016 were prospectively enrolled. Procedures were performed under general anesthesia in an interventional suite equipped with flat panel detector, cone-beam computed tomography (CBCT) and image fusion technique. All TIPSs were placed under image fusion guidance. After hepatic vein catheterization, an unenhanced CBCT acquisition was performed and co-registered with the pre-procedural portal phase CT images. A virtual path between hepatic vein and portal branch was made using the virtual needle path trajectory software. Subsequently, the 3D virtual path was overlaid on 2D fluoroscopy for guidance during portal branch cannulation. Safety, feasibility, effectiveness and per-procedural data were evaluated. Sixteen patients (12 males; median age 56 years) were included. Procedures were technically feasible in 15 of the 16 patients (94%). One procedure was aborted due to hepatic vein catheterization failure related to severe liver distortion. No periprocedural complications occurred within 48 h of the procedure. The median dose-area product was 91 Gy cm 2 , fluoroscopy time 15 min, procedure time 40 min and contrast media consumption 65 mL. Clinical benefit of the TIPS placement was observed in nine patients (56%). This study suggests that 3D image fusion guidance for TIPS is feasible, safe and effective. By identifying virtual needle path, CBCT enables real-time multiplanar guidance and may facilitate TIPS placement.

  11. Spatio-Temporal Series Remote Sensing Image Prediction Based on Multi-Dictionary Bayesian Fusion

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-11-01

    Full Text Available Contradictions in spatial resolution and temporal coverage emerge from earth observation remote sensing images due to limitations in technology and cost. Therefore, how to combine remote sensing images with low spatial yet high temporal resolution as well as those with high spatial yet low temporal resolution to construct images with both high spatial resolution and high temporal coverage has become an important problem called spatio-temporal fusion problem in both research and practice. A Multi-Dictionary Bayesian Spatio-Temporal Reflectance Fusion Model (MDBFM has been proposed in this paper. First, multiple dictionaries from regions of different classes are trained. Second, a Bayesian framework is constructed to solve the dictionary selection problem. A pixel-dictionary likehood function and a dictionary-dictionary prior function are constructed under the Bayesian framework. Third, remote sensing images before and after the middle moment are combined to predict images at the middle moment. Diverse shapes and textures information is learned from different landscapes in multi-dictionary learning to help dictionaries capture the distinctions between regions. The Bayesian framework makes full use of the priori information while the input image is classified. The experiments with one simulated dataset and two satellite datasets validate that the MDBFM is highly effective in both subjective and objective evaluation indexes. The results of MDBFM show more precise details and have a higher similarity with real images when dealing with both type changes and phenology changes.

  12. A novel image fusion algorithm based on 2D scale-mixing complex wavelet transform and Bayesian MAP estimation for multimodal medical images

    Directory of Open Access Journals (Sweden)

    Abdallah Bengueddoudj

    2017-05-01

    Full Text Available In this paper, we propose a new image fusion algorithm based on two-dimensional Scale-Mixing Complex Wavelet Transform (2D-SMCWT. The fusion of the detail 2D-SMCWT coefficients is performed via a Bayesian Maximum a Posteriori (MAP approach by considering a trivariate statistical model for the local neighboring of 2D-SMCWT coefficients. For the approximation coefficients, a new fusion rule based on the Principal Component Analysis (PCA is applied. We conduct several experiments using three different groups of multimodal medical images to evaluate the performance of the proposed method. The obtained results prove the superiority of the proposed method over the state of the art fusion methods in terms of visual quality and several commonly used metrics. Robustness of the proposed method is further tested against different types of noise. The plots of fusion metrics establish the accuracy of the proposed fusion method.

  13. Added Value of Contrast-Enhanced Ultrasound on Biopsies of Focal Hepatic Lesions Invisible on Fusion Imaging Guidance.

    Science.gov (United States)

    Kang, Tae Wook; Lee, Min Woo; Song, Kyoung Doo; Kim, Mimi; Kim, Seung Soo; Kim, Seong Hyun; Ha, Sang Yun

    2017-01-01

    To assess whether contrast-enhanced ultrasonography (CEUS) with Sonazoid can improve the lesion conspicuity and feasibility of percutaneous biopsies for focal hepatic lesions invisible on fusion imaging of real-time ultrasonography (US) with computed tomography/magnetic resonance images, and evaluate its impact on clinical decision making. The Institutional Review Board approved this retrospective study. Between June 2013 and January 2015, 711 US-guided percutaneous biopsies were performed for focal hepatic lesions. Biopsies were performed using CEUS for guidance if lesions were invisible on fusion imaging. We retrospectively evaluated the number of target lesions initially invisible on fusion imaging that became visible after applying CEUS, using a 4-point scale. Technical success rates of biopsies were evaluated based on histopathological results. In addition, the occurrence of changes in clinical decision making was assessed. Among 711 patients, 16 patients (2.3%) were included in the study. The median size of target lesions was 1.1 cm (range, 0.5-1.9 cm) in pre-procedural imaging. After CEUS, 15 of 16 (93.8%) focal hepatic lesions were visualized. The conspicuity score was significantly increased after adding CEUS, as compared to that on fusion imaging (p making for 11 of 16 patients (68.8%). The addition of CEUS could improve the conspicuity of focal hepatic lesions invisible on fusion imaging. This dual guidance using CEUS and fusion imaging may affect patient management via changes in clinical decision-making.

  14. Fusion of MODIS and landsat-8 surface temperature images: a new approach.

    Science.gov (United States)

    Hazaymeh, Khaled; Hassan, Quazi K

    2015-01-01

    Here, our objective was to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS); and implement the developed algorithm over a heterogeneous semi-arid study area in Jordan, Middle East. The STI-FM technique consisted of two major components: (i) establishing a linear relationship between two consecutive MODIS 8-day composite LST images acquired at time 1 and time 2; and (ii) utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat-8 LST image at time 2. It revealed that strong linear relationships (i.e., r2, slopes, and intercepts were in the range 0.93-0.94, 0.94-0.99; and 2.97-20.07) existed between the two consecutive MODIS LST images. We evaluated the synthetic LST images qualitatively and found high visual agreements with the actual Landsat-8 LST images. In addition, we conducted quantitative evaluations of these synthetic images; and found strong agreements with the actual Landsat-8 LST images. For example, r2, root mean square error (RMSE), and absolute average difference (AAD)-values were in the ranges 084-0.90, 0.061-0.080, and 0.003-0.004, respectively.

  15. Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

    Science.gov (United States)

    Savage, Richard C.; Chen, Chin-Tu; Pelizzari, Charles; Ramanathan, Veerabhadran

    1993-01-01

    Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

  16. A 2D Wigner Distribution-based multisize windows technique for image fusion

    Czech Academy of Sciences Publication Activity Database

    Redondo, R.; Fischer, S.; Šroubek, Filip; Cristóbal, G.

    2008-01-01

    Roč. 19, č. 1 (2008), s. 12-19 ISSN 1047-3203 R&D Projects: GA ČR GA102/04/0155; GA ČR GA202/05/0242 Grant - others:CSIC(CZ) 2004CZ0009 Institutional research plan: CEZ:AV0Z10750506 Keywords : Wigner distribution * image fusion * multifocus Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.342, year: 2008

  17. FZUImageReg: A toolbox for medical image registration and dose fusion in cervical cancer radiotherapy.

    Directory of Open Access Journals (Sweden)

    Qinquan Gao

    Full Text Available The combination external-beam radiotherapy and high-dose-rate brachytherapy is a standard form of treatment for patients with locally advanced uterine cervical cancer. Personalized radiotherapy in cervical cancer requires efficient and accurate dose planning and assessment across these types of treatment. To achieve radiation dose assessment, accurate mapping of the dose distribution from HDR-BT onto EBRT is extremely important. However, few systems can achieve robust dose fusion and determine the accumulated dose distribution during the entire course of treatment. We have therefore developed a toolbox (FZUImageReg, which is a user-friendly dose fusion system based on hybrid image registration for radiation dose assessment in cervical cancer radiotherapy. The main part of the software consists of a collection of medical image registration algorithms and a modular design with a user-friendly interface, which allows users to quickly configure, test, monitor, and compare different registration methods for a specific application. Owing to the large deformation, the direct application of conventional state-of-the-art image registration methods is not sufficient for the accurate alignment of EBRT and HDR-BT images. To solve this problem, a multi-phase non-rigid registration method using local landmark-based free-form deformation is proposed for locally large deformation between EBRT and HDR-BT images, followed by intensity-based free-form deformation. With the transformation, the software also provides a dose mapping function according to the deformation field. The total dose distribution during the entire course of treatment can then be presented. Experimental results clearly show that the proposed system can achieve accurate registration between EBRT and HDR-BT images and provide radiation dose warping and fusion results for dose assessment in cervical cancer radiotherapy in terms of high accuracy and efficiency.

  18. PET-CT imaging fusion in the assessment of head and neck carcinoma

    International Nuclear Information System (INIS)

    Santos, Denise Takehana dos; Chojniak, Rubens; Lima, Eduardo Nobrega Pereira; Cavalcanti, Marcelo Gusmao Paraiso

    2006-01-01

    Objective: The authors have established a methodological approach to evaluate head and neck squamous cell carcinoma aiming at identifying and distinguishing high metabolic activity inside the lesion, combining in a single examination, functional, metabolic and morphological data simultaneously acquired by means of different non-dedicated positron emission tomography (PET)-computed tomography (CT) device. Materials and Methods: The study population included 17 patients with head and neck squamous cell carcinoma submitted to a non-dedicated 18 F-FDG-PET imaging at Department of Diagnostic Imaging of Hospital do Cancer, Sao Paulo, SP, Brazil. CT and 18 F-FDG-PET images were simultaneously acquired in a non-dedicated device. The original data were transferred to an independent workstation by means of the Entegra 2 NT software to generate PET-CT imaging fusion. Results: The findings were defined as positive in the presence of a well defined focal area of increased radiopharmaceutical uptake in regions not related with the normal biodistribution of the tracer. Conclusion: The fusion of simultaneously acquired images in a single examination ( 18 F-FDGPET and CT) has allowed the topographic-metabolic mapping of the lesion as well as the localization of high metabolic activity areas inside the tumor, indicating recidivation or metastasis and widening the array of alternatives for radiotherapy or surgical planning. (author)

  19. The registration accuracy analysis of different CT-MRI imaging fusion method in brain tumor

    International Nuclear Information System (INIS)

    Lu Jie; Yin Yong; Shao Qian; Zhang Zicheng; Chen Jinhu; Chen Zhaoqiu

    2010-01-01

    Objective: To find an effective CT-MRI image fusion protocol in brain tumor by analyzing the registration accuracy of different methods. Methods: The simulation CT scan and MRI T 1 WI imaging of 10 brain tumor patients obtained with same position were registered by Tris-Axes landmark ,Tris-Axes landmark + manual adjustment, mutual information and mutual information + manual adjustment method. The clinical tumor volume (CTV) were contoured on both CT and MRI images respectively. The accuracy of image fusion was assessed by the mean distance of five bone markers (d 1-5 ), central position of CTV (d CTV ) the percentage of CTV overlap (P CT-MRI ) between CT and MRI images. The difference between different methods was analyzed by Freedman M non-parameter test. Results: The difference of the means d1-5 between the Tris-Axes landmark,Tris-Axes landmark plus manual adjustment,mutual information and mutual information plus manual adjustment methods were 0.28 cm ±0.12 cm, 0.15 cm ±0.02 cm, 0.25 cm± 0.19 cm, 0.10 cm ± 0.06 cm, (M = 14.41, P = 0.002). the means d CTV were 0.59 cm ± 0.28 cm, 0.60 cm± 0.32 cm, 0.58 cm ± 0.39 cm, 0.42 cm± 0.30 cm (M = 9.72, P = 0.021), the means P CT-MRI were 0.69% ±0.18%, 0.68% ±0.16%, 0.66% ±0.17%, 0.74% ±0.14% (M =14.82, P=0.002), respectively. Conclusions: Mutual information plus manual adjustment registration method was the preferable fusion method for brain tumor patients. (authors)

  20. COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

    Directory of Open Access Journals (Sweden)

    K. Seetharaman

    2015-08-01

    Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

  1. Multisensor fusion in gastroenterology domain through video and echo endoscopic image combination: a challenge

    Science.gov (United States)

    Debon, Renaud; Le Guillou, Clara; Cauvin, Jean-Michel; Solaiman, Basel; Roux, Christian

    2001-08-01

    Medical domain makes intensive use of information fusion. In particular, the gastro-enterology is a discipline where physicians have the choice between several imagery modalities that offer complementary advantages. Among all existing systems, videoendoscopy (based on a CCD sensor) and echoendoscopy (based on an ultrasound sensor) are the most efficient. The use of each system corresponds to a given step in the physician diagnostic elaboration. Nowadays, several works aim to achieve automatic interpretation of videoendoscopic sequences. These systems can quantify color and superficial textures of the digestive tube. Unfortunately the relief information, which is important for the diagnostic, is very difficult to retrieve. On the other hand, some studies have proved that 3D information can be easily quantified using echoendoscopy image sequences. That is why the idea to combine these information, acquired from two very different points of view, can be considered as a real challenge for the medical image fusion topic. In this paper, after a review of actual works concerning numerical exploitation of videoendoscopy and echoendoscopy, the following question will be discussed: how can the use of complementary aspects of the different systems ease the automatic exploitation of videoendoscopy ? In a second time, we will evaluate the feasibility of the achievement of a realistic 3D reconstruction based both on information given by echoendoscopy (relief) and videoendoscopy (texture). Enumeration of potential applications of such a fusion system will then follow. Further discussions and perspectives will conclude this first study.

  2. The TRICLOBS Dynamic Multi-Band Image Data Set for the Development and Evaluation of Image Fusion Methods.

    Directory of Open Access Journals (Sweden)

    Alexander Toet

    Full Text Available The fusion and enhancement of multiband nighttime imagery for surveillance and navigation has been the subject of extensive research for over two decades. Despite the ongoing efforts in this area there is still only a small number of static multiband test images available for the development and evaluation of new image fusion and enhancement methods. Moreover, dynamic multiband imagery is also currently lacking. To fill this gap we present the TRICLOBS dynamic multi-band image data set containing sixteen registered visual (0.4-0.7μm, near-infrared (NIR, 0.7-1.0μm and long-wave infrared (LWIR, 8-14μm motion sequences. They represent different military and civilian surveillance scenarios registered in three different scenes. Scenes include (military and civilian people that are stationary, walking or running, or carrying various objects. Vehicles, foliage, and buildings or other man-made structures are also included in the scenes. This data set is primarily intended for the development and evaluation of image fusion, enhancement and color mapping algorithms for short-range surveillance applications. The imagery was collected during several field trials with our newly developed TRICLOBS (TRI-band Color Low-light OBServation all-day all-weather surveillance system. This system registers a scene in the Visual, NIR and LWIR part of the electromagnetic spectrum using three optically aligned sensors (two digital image intensifiers and an uncooled long-wave infrared microbolometer. The three sensor signals are mapped to three individual RGB color channels, digitized, and stored as uncompressed RGB (false color frames. The TRICLOBS data set enables the development and evaluation of (both static and dynamic image fusion, enhancement and color mapping algorithms. To allow the development of realistic color remapping procedures, the data set also contains color photographs of each of the three scenes. The color statistics derived from these photographs

  3. Scene data fusion: Real-time standoff volumetric gamma-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Barnowski, Ross [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720, United States of America (United States); Haefner, Andrew; Mihailescu, Lucian [Lawrence Berkeley National Lab - Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720, United States of America (United States); Vetter, Kai [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720, United States of America (United States); Lawrence Berkeley National Lab - Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720, United States of America (United States)

    2015-11-11

    An approach to gamma-ray imaging has been developed that enables near real-time volumetric (3D) imaging of unknown environments thus improving the utility of gamma-ray imaging for source-search and radiation mapping applications. The approach, herein dubbed scene data fusion (SDF), is based on integrating mobile radiation imagers with real-time tracking and scene reconstruction algorithms to enable a mobile mode of operation and 3D localization of gamma-ray sources. A 3D model of the scene, provided in real-time by a simultaneous localization and mapping (SLAM) algorithm, is incorporated into the image reconstruction reducing the reconstruction time and improving imaging performance. The SDF concept is demonstrated in this work with a Microsoft Kinect RGB-D sensor, a real-time SLAM solver, and a cart-based Compton imaging platform comprised of two 3D position-sensitive high purity germanium (HPGe) detectors. An iterative algorithm based on Compton kinematics is used to reconstruct the gamma-ray source distribution in all three spatial dimensions. SDF advances the real-world applicability of gamma-ray imaging for many search, mapping, and verification scenarios by improving the tractiblity of the gamma-ray image reconstruction and providing context for the 3D localization of gamma-ray sources within the environment in real-time.

  4. Accuracy verification of PET-CT image fusion and its utilization in target delineation of radiotherapy

    International Nuclear Information System (INIS)

    Wang Xuetao; Yu Jinming; Yang Guoren; Gong Heyi

    2005-01-01

    Objective: Evaluate the accuracy of co-registration of PET and CT (PET-CT) images on line with phantom, and utilize it on patients to provide clinical evidence for target delineation in radiotherapy. Methods: A phantom with markers and different volume cylinders was infused with various concentrations of 18 FDG, and scanned at 4 mm by PET and CT respectively. After having been transmitted into GE eNTEGRA and treatment planning system (TPS) workstations, the images were fused and reconstructed. The distance between the markers and the errors were monitored in PET and CT images respectively. The volume of cylinder in PET and CT images were measured and compared by certain pixel value proportion deduction method. The same procedure was performed on the pulmonary tumor image in ten patients. Results: eNTEGRA and TPS workstations had a good length linearity, but the fusion error of the latter was markedly greater than the former. Tumors in different volume filled by varying concentrations of 18 FDG required different pixel deduction proportion. The cylinder volume of PET and CT images were almost the same, so were the images of pulmonary tumor of ten patients. Conclusions: The accuracy of image co-registration of PET-CT on line may fulfill the clinical demand. Pixel value proportion deduction method can be used for target delineation on PET image. (authors)

  5. Automatically Identifying Fusion Events between GLUT4 Storage Vesicles and the Plasma Membrane in TIRF Microscopy Image Sequences

    Directory of Open Access Journals (Sweden)

    Jian Wu

    2015-01-01

    Full Text Available Quantitative analysis of the dynamic behavior about membrane-bound secretory vesicles has proven to be important in biological research. This paper proposes a novel approach to automatically identify the elusive fusion events between VAMP2-pHluorin labeled GLUT4 storage vesicles (GSVs and the plasma membrane. The differentiation is implemented to detect the initiation of fusion events by modified forward subtraction of consecutive frames in the TIRFM image sequence. Spatially connected pixels in difference images brighter than a specified adaptive threshold are grouped into a distinct fusion spot. The vesicles are located at the intensity-weighted centroid of their fusion spots. To reveal the true in vivo nature of a fusion event, 2D Gaussian fitting for the fusion spot is used to derive the intensity-weighted centroid and the spot size during the fusion process. The fusion event and its termination can be determined according to the change of spot size. The method is evaluated on real experiment data with ground truth annotated by expert cell biologists. The evaluation results show that it can achieve relatively high accuracy comparing favorably to the manual analysis, yet at a small fraction of time.

  6. Multi-focus image fusion based on area-based standard deviation in dual tree contourlet transform domain

    Science.gov (United States)

    Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin

    2018-04-01

    Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.

  7. Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems

    Energy Technology Data Exchange (ETDEWEB)

    Lai, J.; Domier, C. W.; Luhmann, N. C. [Department of Electrical and Computer Engineering, University of California at Davis, Davis, California 95616 (United States)

    2014-03-15

    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{sub e} and n{sub 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.

  8. Moving target detection based on temporal-spatial information fusion for infrared image sequences

    Science.gov (United States)

    Toing, Wu-qin; Xiong, Jin-yu; Zeng, An-jun; Wu, Xiao-ping; Xu, Hao-peng

    2009-07-01

    Moving target detection and localization is one of the most fundamental tasks in visual surveillance. In this paper, through analyzing the advantages and disadvantages of the traditional approaches about moving target detection, a novel approach based on temporal-spatial information fusion is proposed for moving target detection. The proposed method combines the spatial feature in single frame and the temporal properties within multiple frames of an image sequence of moving target. First, the method uses the spatial image segmentation for target separation from background and uses the local temporal variance for extracting targets and wiping off the trail artifact. Second, the logical "and" operator is used to fuse the temporal and spatial information. In the end, to the fusion image sequence, the morphological filtering and blob analysis are used to acquire exact moving target. The algorithm not only requires minimal computation and memory but also quickly adapts to the change of background and environment. Comparing with other methods, such as the KDE, the Mixture of K Gaussians, etc., the simulation results show the proposed method has better validity and higher adaptive for moving target detection, especially in infrared image sequences with complex illumination change, noise change, and so on.

  9. Combined FDG PET/CT imaging for restaging of colorectal cancer patients: impact of image fusion on staging accuracy

    International Nuclear Information System (INIS)

    Strunk, H.; Jaeger, U.; Flacke, S.; Hortling, N.; Bucerius, J.; Joe, A.; Reinhardt, M.; Palmedo, H.

    2005-01-01

    Purpose: To evaluate the diagnostic impact of positron emission tomography (PET) with fluorine-18-labeled deoxy-D-glucose (FDG) combined with non-contrast computed tomography (CT) as PET-CT modality in restaging colorectal cancer patients. Material and methods: In this retrospective study, 29 consecutive patients with histologically proven colorectal cancer (17 female, 12 male, aged 51-76 years) underwent whole body scans in one session on a dual modality PET-CT system (Siemens Biograph) 90 min. after i.v. administration of 370 MBq 18 F-FDG. The CT imaging was performed with 40 mAs, 130 kV, slice-thickness 5 mm and without i.v. contrast administration. PET and CT images were reconstructed with a slice-thickness of 5 mm in coronal, sagittal and transverse planes. During a first step of analysis, PET and CT images were scored blinded and independently by a group of two nuclear medicine physicians and a group of two radiologists, respectively. For this purpose, a five-point-scale was used. The second step of data-analysis consisted of a consensus reading by both groups. During the consensus reading, first a virtual (meaning mental) fusion of PET and CT images and afterwards the 'real' fusion (meaning coregistered) PET-CT images were also scored with the same scale. The imaging results were compared with histopathology findings and the course of disease during further follow-up. Results: The total number of malignant lesions detected with the combined PET/CT were 86. For FDG-PET alone it was n=68, and for CT alone n=65. Comparing PET-CT and PET, concordance was found in 81 of 104 lesions. Discrepancies predominantly occurred in the lung, where PET alone often showed true positive results in lymph nodes and soft tissue masses, where CT often was false negative. Comparing mental fusion and 'real' co-registered images, concordance was found in 94 of 104 lesions. In 13 lesions or, respectively, in 7 of 29 patients, a relevant information was gathered using fused images

  10. Image fusion in open-architecture quality-oriented nuclear medicine and radiology departments

    Energy Technology Data Exchange (ETDEWEB)

    Pohjonen, H

    1998-12-31

    Imaging examinations of patients belong to the most widely used diagnostic procedures in hospitals. Multimodal digital imaging is becoming increasingly common in many fields of diagnosis and therapy planning. Patients are frequently examined with magnetic resonance imaging (MRI), X-ray computed tomography (CT) or ultrasound imaging (US) in addition to single photon (SPET) or positron emission tomography (PET). The aim of the study was to provide means for improving the quality of the whole imaging and viewing chain in nuclear medicine and radiology. The specific aims were: (1) to construct and test a model for a quality assurance system in radiology based on ISO standards, (2) to plan a Dicom based image network for fusion purposes using ATM and Ethernet technologies, (3) to test different segmentation methods in quantitative SPET, (4) to study and implement a registration and visualisation method for multimodal imaging, (5) to apply the developed method in selected clinical brain and abdominal images, and (6) to investigate the accuracy of the registration procedure for brain SPET and MRI 90 refs. The thesis includes also six previous publications by author

  11. Image fusion in open-architecture quality-oriented nuclear medicine and radiology departments

    International Nuclear Information System (INIS)

    Pohjonen, H.

    1997-01-01

    Imaging examinations of patients belong to the most widely used diagnostic procedures in hospitals. Multimodal digital imaging is becoming increasingly common in many fields of diagnosis and therapy planning. Patients are frequently examined with magnetic resonance imaging (MRI), X-ray computed tomography (CT) or ultrasound imaging (US) in addition to single photon (SPET) or positron emission tomography (PET). The aim of the study was to provide means for improving the quality of the whole imaging and viewing chain in nuclear medicine and radiology. The specific aims were: (1) to construct and test a model for a quality assurance system in radiology based on ISO standards, (2) to plan a Dicom based image network for fusion purposes using ATM and Ethernet technologies, (3) to test different segmentation methods in quantitative SPET, (4) to study and implement a registration and visualisation method for multimodal imaging, (5) to apply the developed method in selected clinical brain and abdominal images, and (6) to investigate the accuracy of the registration procedure for brain SPET and MRI

  12. Image fusion in open-architecture quality-oriented nuclear medicine and radiology departments

    Energy Technology Data Exchange (ETDEWEB)

    Pohjonen, H

    1997-12-31

    Imaging examinations of patients belong to the most widely used diagnostic procedures in hospitals. Multimodal digital imaging is becoming increasingly common in many fields of diagnosis and therapy planning. Patients are frequently examined with magnetic resonance imaging (MRI), X-ray computed tomography (CT) or ultrasound imaging (US) in addition to single photon (SPET) or positron emission tomography (PET). The aim of the study was to provide means for improving the quality of the whole imaging and viewing chain in nuclear medicine and radiology. The specific aims were: (1) to construct and test a model for a quality assurance system in radiology based on ISO standards, (2) to plan a Dicom based image network for fusion purposes using ATM and Ethernet technologies, (3) to test different segmentation methods in quantitative SPET, (4) to study and implement a registration and visualisation method for multimodal imaging, (5) to apply the developed method in selected clinical brain and abdominal images, and (6) to investigate the accuracy of the registration procedure for brain SPET and MRI 90 refs. The thesis includes also six previous publications by author

  13. Ultrasound-guided image fusion with computed tomography and magnetic resonance imaging. Clinical utility for imaging and interventional diagnostics of hepatic lesions

    International Nuclear Information System (INIS)

    Clevert, D.A.; Helck, A.; Paprottka, P.M.; Trumm, C.; Reiser, M.F.; Zengel, P.

    2012-01-01

    Abdominal ultrasound is often the first-line imaging modality for assessing focal liver lesions. Due to various new ultrasound techniques, such as image fusion, global positioning system (GPS) tracking and needle tracking guided biopsy, abdominal ultrasound now has great potential regarding detection, characterization and treatment of focal liver lesions. Furthermore, these new techniques will help to improve the clinical management of patients before and during interventional procedures. This article presents the principle and clinical impact of recently developed techniques in the field of ultrasound, e.g. image fusion, GPS tracking and needle tracking guided biopsy and discusses the results based on a feasibility study on 20 patients with focal hepatic lesions. (orig.) [de

  14. CBCT-based 3D MRA and angiographic image fusion and MRA image navigation for neuro interventions.

    Science.gov (United States)

    Zhang, Qiang; Zhang, Zhiqiang; Yang, Jiakang; Sun, Qi; Luo, Yongchun; Shan, Tonghui; Zhang, Hao; Han, Jingfeng; Liang, Chunyang; Pan, Wenlong; Gu, Chuanqi; Mao, Gengsheng; Xu, Ruxiang

    2016-08-01

    Digital subtracted angiography (DSA) remains the gold standard for diagnosis of cerebral vascular diseases and provides intraprocedural guidance. This practice involves extensive usage of x-ray and iodinated contrast medium, which can induce side effects. In this study, we examined the accuracy of 3-dimensional (3D) registration of magnetic resonance angiography (MRA) and DSA imaging for cerebral vessels, and tested the feasibility of using preprocedural MRA for real-time guidance during endovascular procedures.Twenty-three patients with suspected intracranial arterial lesions were enrolled. The contrast medium-enhanced 3D DSA of target vessels were acquired in 19 patients during endovascular procedures, and the images were registered with preprocedural MRA for fusion accuracy evaluation. Low-dose noncontrasted 3D angiography of the skull was performed in the other 4 patients, and registered with the MRA. The MRA was overlaid afterwards with 2D live fluoroscopy to guide endovascular procedures.The 3D registration of the MRA and angiography demonstrated a high accuracy for vessel lesion visualization in all 19 patients examined. Moreover, MRA of the intracranial vessels, registered to the noncontrasted 3D angiography in the 4 patients, provided real-time 3D roadmap to successfully guide the endovascular procedures. Radiation dose to patients and contrast medium usage were shown to be significantly reduced.Three-dimensional MRA and angiography fusion can accurately generate cerebral vasculature images to guide endovascular procedures. The use of the fusion technology could enhance clinical workflow while minimizing contrast medium usage and radiation dose, and hence lowering procedure risks and increasing treatment safety.

  15. Far-infrared imaging arrays for fusion plasma density and magnetic field measurements

    International Nuclear Information System (INIS)

    Neikirk, D.P.; Rutledge, D.B.

    1982-01-01

    Far-infrared imaging detector arrays are required for the determination of density and local magnetic field in fusion plasmas. Analytic calculations point out the difficulties with simple printed slot and dipole antennas on ungrounded substrates for use in submillimeter wave imaging arrays because of trapped surface waves. This is followed by a discussion of the use of substrate-lens coupling to eliminate the associated trapped surface modes responsible for their poor performance. This integrates well with a modified bow-tie antenna and permits diffraction-limited imaging. Arrays using bismuth microbolometers have been successfully fabricated and tested at 1222μm and 119μm. A 100 channel pilot experiment designed for the UCLA Microtor tokamak is described. (author)

  16. Neutron imaging development for megajoule scale inertial confinement fusion experiments{sup 1}

    Energy Technology Data Exchange (ETDEWEB)

    Grim, G P; Bradley, P A; Day, R D; Clark, D D; Fatherley, V E; Finch, J P; Garcia, F P; Jaramillo, S A; Montoya, A J; Morgan, G L; Oertel, J A; Ortiz, T A; Payton, J R; Pazuchanics, P; Schmidt, D W; Valdez, A C; Wilde, C H; Wilke, M D; Wilson, D C [Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM 87545 (United States)], E-mail: gpgrim@lanl.gov

    2008-05-15

    Neutron imaging of Inertial Confinement Fusion (ICF) targets is useful for understanding the implosion conditions of deuterium and tritium filled targets at Mega-Joule/Tera-Watt scale laser facilities. The primary task for imaging ICF targets at the National Ignition Facility, Lawrence Livermore National Laboratory, Livermore CA, is to determine the asymmetry of the imploded target. The image data, along with other nuclear information, are to be used to provide insight into target drive conditions. The diagnostic goal at the National Ignition Facility is to provide neutron images with 10 {mu}m resolution and peak signal-to-background values greater than 20 for neutron yields of {approx} 10{sup 15}. To achieve this requires signal multiplexing apertures with good resolution. In this paper we present results from imaging system development efforts aimed at achieving these requirements using neutron pinholes. The data were collected using directly driven ICF targets at the Omega Laser, University of Rochester, Rochester, NY., and include images collected from a 3 x 3 array of 15.5 {mu}m pinholes. Combined images have peak signal-to-background values greater than 30 at neutron yields of {approx} 10{sup 13}.

  17. [Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain].

    Science.gov (United States)

    Fiedler, E; Platsch, G; Schwarz, A; Schmiedehausen, K; Tomandl, B; Huk, W; Rupprecht, Th; Rahn, N; Kuwert, T

    2003-10-01

    Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. PATIENTS, MATERIAL AND METHOD: In 32 patients regional cerebral blood flow was measured using (99m)Tc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.

  18. Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain

    International Nuclear Information System (INIS)

    Fiedler, E.; Platsch, G.; Schwarz, A.; Schmiedehausen, K.; Kuwert, T.; Tomandl, B.; Huk, W.; Rupprecht, Th.; Rahn, N.

    2003-01-01

    Aim: Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. Patients, material and method: In 32 patients regional cerebral blood flow was measured using 99m Tc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3 D-T1 w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. Results: The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). Conclusion: The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use. (orig.) [de

  19. Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain

    Science.gov (United States)

    Huang, Yan; Bi, Duyan; Wu, Dongpeng

    2018-01-01

    There are many artificial parameters when fuse infrared and visible images, to overcome the lack of detail in the fusion image because of the artifacts, a novel fusion algorithm for infrared and visible images that is based on different constraints in non-subsampled shearlet transform (NSST) domain is proposed. There are high bands and low bands of images that are decomposed by the NSST. After analyzing the characters of the bands, fusing the high level bands by the gradient constraint, the fused image can obtain more details; fusing the low bands by the constraint of saliency in the images, the targets are more salient. Before the inverse NSST, the Nash equilibrium is used to update the coefficient. The fused images and the quantitative results demonstrate that our method is more effective in reserving details and highlighting the targets when compared with other state-of-the-art methods. PMID:29641505

  20. Added value of contrast-enhanced ultrasound on biopsies of focal hepatic lesions invisible on fusion imaging guidance

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Tae Wook; Lee, Min Woo; Song, Kyoung Doo; Kim, Mimi; Kim, Seung Soo; Kim, Seong Hyun; Ha, Sang Yun [Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

    2017-01-15

    To assess whether contrast-enhanced ultrasonography (CEUS) with Sonazoid can improve the lesion conspicuity and feasibility of percutaneous biopsies for focal hepatic lesions invisible on fusion imaging of real-time ultrasonography (US) with computed tomography/magnetic resonance images, and evaluate its impact on clinical decision making. The Institutional Review Board approved this retrospective study. Between June 2013 and January 2015, 711 US-guided percutaneous biopsies were performed for focal hepatic lesions. Biopsies were performed using CEUS for guidance if lesions were invisible on fusion imaging. We retrospectively evaluated the number of target lesions initially invisible on fusion imaging that became visible after applying CEUS, using a 4-point scale. Technical success rates of biopsies were evaluated based on histopathological results. In addition, the occurrence of changes in clinical decision making was assessed. Among 711 patients, 16 patients (2.3%) were included in the study. The median size of target lesions was 1.1 cm (range, 0.5–1.9 cm) in pre-procedural imaging. After CEUS, 15 of 16 (93.8%) focal hepatic lesions were visualized. The conspicuity score was significantly increased after adding CEUS, as compared to that on fusion imaging (p < 0.001). The technical success rate of biopsy was 87.6% (14/16). After biopsy, there were changes in clinical decision making for 11 of 16 patients (68.8%). The addition of CEUS could improve the conspicuity of focal hepatic lesions invisible on fusion imaging. This dual guidance using CEUS and fusion imaging may affect patient management via changes in clinical decision-making.

  1. Added value of contrast-enhanced ultrasound on biopsies of focal hepatic lesions invisible on fusion imaging guidance

    International Nuclear Information System (INIS)

    Kang, Tae Wook; Lee, Min Woo; Song, Kyoung Doo; Kim, Mimi; Kim, Seung Soo; Kim, Seong Hyun; Ha, Sang Yun

    2017-01-01

    To assess whether contrast-enhanced ultrasonography (CEUS) with Sonazoid can improve the lesion conspicuity and feasibility of percutaneous biopsies for focal hepatic lesions invisible on fusion imaging of real-time ultrasonography (US) with computed tomography/magnetic resonance images, and evaluate its impact on clinical decision making. The Institutional Review Board approved this retrospective study. Between June 2013 and January 2015, 711 US-guided percutaneous biopsies were performed for focal hepatic lesions. Biopsies were performed using CEUS for guidance if lesions were invisible on fusion imaging. We retrospectively evaluated the number of target lesions initially invisible on fusion imaging that became visible after applying CEUS, using a 4-point scale. Technical success rates of biopsies were evaluated based on histopathological results. In addition, the occurrence of changes in clinical decision making was assessed. Among 711 patients, 16 patients (2.3%) were included in the study. The median size of target lesions was 1.1 cm (range, 0.5–1.9 cm) in pre-procedural imaging. After CEUS, 15 of 16 (93.8%) focal hepatic lesions were visualized. The conspicuity score was significantly increased after adding CEUS, as compared to that on fusion imaging (p < 0.001). The technical success rate of biopsy was 87.6% (14/16). After biopsy, there were changes in clinical decision making for 11 of 16 patients (68.8%). The addition of CEUS could improve the conspicuity of focal hepatic lesions invisible on fusion imaging. This dual guidance using CEUS and fusion imaging may affect patient management via changes in clinical decision-making

  2. Clinical study of the image fusion between CT and FDG-PET in the head and neck region

    International Nuclear Information System (INIS)

    Shozushima, Masanori; Moriguchi, Hitoshi; Shoji, Satoru; Sakamaki, Kimio; Ishikawa, Yoshihito; Kudo, Keigo; Satoh, Masanobu

    1999-01-01

    Image fusion using PET and CT from the head and neck region was performed with the use of external markers on 7 patients with squamous cell carcinoma. The purpose of this study was to examine a resultant error and the clinical usefulness of image fusion. Patients had primary lesions of the tongue, the maxillary gingiva or the maxillary sinus. All patients underwent PET with FDG and CT to detect tumor sites. Of these 7 patients, diagnostic images and the clinical observation found 6 cases of regional lymph node metastasis of the neck. To ensure the anatomical detail of the PET images, small radioactive markers were placed on the philtrum and below both earlobes. The PET image and CT image were then overlapped on a computer. The image fusion of PET and CT was successfully performed on all patients. The superposition error of this method was examined between the PET and CT images. The accuracy of fit measured as the mean distance between the PET and CT image was in the range of 2-5 mm. PET-CT superimposed images produced an increase in the localization of tumor FDG uptake and localized FDG uptake on the palatine tonsils. The marker system described here for the alignment of PET and CT images can be used on a routine basis without the invasive fixation of external markers, and also improve the management and follow up on patients with head and neck carcinoma. (author)

  3. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Directory of Open Access Journals (Sweden)

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  4. Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Biao Wang

    2017-08-01

    Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

  5. Measurement of the quantum superposition state of an imaging ensemble of photons prepared in orbital angular momentum states using a phase-diversity method

    International Nuclear Information System (INIS)

    Uribe-Patarroyo, Nestor; Alvarez-Herrero, Alberto; Belenguer, Tomas

    2010-01-01

    We propose the use of a phase-diversity technique to estimate the orbital angular momentum (OAM) superposition state of an ensemble of photons that passes through an optical system, proceeding from an extended object. The phase-diversity technique permits the estimation of the optical transfer function (OTF) of an imaging optical system. As the OTF is derived directly from the wave-front characteristics of the observed light, we redefine the phase-diversity technique in terms of a superposition of OAM states. We test this new technique experimentally and find coherent results among different tests, which gives us confidence in the estimation of the photon ensemble state. We find that this technique not only allows us to estimate the square of the amplitude of each OAM state, but also the relative phases among all states, thus providing complete information about the quantum state of the photons. This technique could be used to measure the OAM spectrum of extended objects in astronomy or in an optical communication scheme using OAM states. In this sense, the use of extended images could lead to new techniques in which the communication is further multiplexed along the field.

  6. Fusion set selection with surrogate metric in multi-atlas based image segmentation

    International Nuclear Information System (INIS)

    Zhao, Tingting; Ruan, Dan

    2016-01-01

    Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation. (paper)

  7. Soft sensor design by multivariate fusion of image features and process measurements

    DEFF Research Database (Denmark)

    Lin, Bao; Jørgensen, Sten Bay

    2011-01-01

    This paper presents a multivariate data fusion procedure for design of dynamic soft sensors where suitably selected image features are combined with traditional process measurements to enhance the performance of data-driven soft sensors. A key issue of fusing multiple sensor data, i.e. to determine...... with a multivariate analysis technique from RGB pictures. The color information is also transformed to hue, saturation and intensity components. Both sets of image features are combined with traditional process measurements to obtain an inferential model by partial least squares (PLS) regression. A dynamic PLS model...... oxides (NOx) emission of cement kilns. On-site tests demonstrate improved performance over soft sensors based on conventional process measurements only....

  8. Ring Fusion of Fisheye Images Based on Corner Detection Algorithm for Around View Monitoring System of Intelligent Driving

    Directory of Open Access Journals (Sweden)

    Jianhui Zhao

    2018-01-01

    Full Text Available In order to improve the visual effect of the around view monitor (AVM, we propose a novel ring fusion method to reduce the brightness difference among fisheye images and achieve a smooth transition around stitching seam. Firstly, an integrated corner detection is proposed to automatically detect corner points for image registration. Then, we use equalization processing to reduce the brightness among images. And we match the color of images according to the ring fusion method. Finally, we use distance weight to blend images around stitching seam. Through this algorithm, we have made a Matlab toolbox for image blending. 100% of the required corner is accurately and fully automatically detected. The transition around the stitching seam is very smooth, with no obvious stitching trace.

  9. Electrical characterization of bolus material as phantom for use in electrical impedance and computed tomography fusion imaging

    Directory of Open Access Journals (Sweden)

    Parvind Kaur Grewal

    2014-04-01

    Full Text Available Phantoms are widely used in medical imaging to predict image quality prior to clinical imaging. This paper discusses the possible use of bolus material, as a conductivity phantom, for validation and interpretation of electrical impedance tomography (EIT images. Bolus is commonly used in radiation therapy to mimic tissue. When irradiated, it has radiological characteristics similar to tissue. With increased research interest in CT/EIT fusion imaging there is a need to find a material which has both the absorption coefficient and electrical conductivity similar to biological tissues. In the present study the electrical properties, specifically resistivity, of various commercially available bolus materials were characterized by comparing their frequency response with that of in-vivo connective adipose tissue. It was determined that the resistivity of Gelatin Bolus is similar to in-vivo tissue in the frequency range 10 kHz to 1MHz and therefore has potential to be used in EIT/CT fusion imaging studies.

  10. [Image fusion of gated-SPECT and CT angiography in coronary artery disease. Importance of anatomic-functional correlation].

    Science.gov (United States)

    Nazarena Pizzi, M; Aguadé Bruix, S; Cuéllar Calabria, H; Aliaga, V; Candell Riera, J

    2010-01-01

    A 77-year old patient was admitted for acute coronary syndrome without ST elevation. His risk was stratified using the myocardial perfusion gated SPECT, mild inferior ischemia being observed. Thus, medical therapy was optimized and the patient was discharged. He continued with exertional dyspnea so a coronary CT angiography was performed. It revealed severe lesions in the proximal RCA. SPECT-CT fusion images correlated the myocardial perfusion defect with a posterior descending artery from the RCA, in a co-dominant coronary area. Subsequently, cardiac catheterism was indicated for his treatment. The current use of image fusion studies is limited to patients in whom it is difficult to attribute a perfusion defect to a specific coronary artery. In our patient, the fusion images helped to distinguish between the RCA and the circumflex artery as the culprit artery of ischemia. Copyright © 2010 Elsevier España, S.L. y SEMNIM. All rights reserved.

  11. Simultaneous usage of pinhole and penumbral apertures for imaging small scale neutron sources from inertial confinement fusion experiments.

    Science.gov (United States)

    Guler, N; Volegov, P; Danly, C R; Grim, G P; Merrill, F E; Wilde, C H

    2012-10-01

    Inertial confinement fusion experiments at the National Ignition Facility are designed to understand the basic principles of creating self-sustaining fusion reactions by laser driven compression of deuterium-tritium (DT) filled cryogenic plastic capsules. The neutron imaging diagnostic provides information on the distribution of the central fusion reaction region and the surrounding DT fuel by observing neutron images in two different energy bands for primary (13-17 MeV) and down-scattered (6-12 MeV) neutrons. From this, the final shape and size of the compressed capsule can be estimated and the symmetry of the compression can be inferred. These experiments provide small sources with high yield neutron flux. An aperture design that includes an array of pinholes and penumbral apertures has provided the opportunity to image the same source with two different techniques. This allows for an evaluation of these different aperture designs and reconstruction algorithms.

  12. Anato-metabolic fusion of PET, CT and MRI images; Anatometabolische Bildfusion von PET, CT und MRT

    Energy Technology Data Exchange (ETDEWEB)

    Przetak, C.; Baum, R.P.; Niesen, A. [Zentralklinik Bad Berka (Germany). Klinik fuer Nuklearmedizin/PET-Zentrum; Slomka, P. [University of Western Ontario, Toronto (Canada). Health Sciences Centre; Proeschild, A.; Leonhardi, J. [Zentralklinik Bad Berka (Germany). Inst. fuer bildgebende Diagnostik

    2000-12-01

    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.) [German] Zur Erhoehung der diagnostischen und therapeutischen Sicherheit ist die Fusion von Schnittbildern verschiedener tomographischer Verfahren insbesondere in der Onkologie sehr hilfreich. Trotz bestehender Vorteile hat die Bildfusion bisher nur in einzelnen Zentren Einzug in die nuklearmedizinische und radiologische Routinediagnostik gefunden. Um die Bildfusion allgemein einsetzen zu koennen, sind bestimmte technische und logistische Voraussetzungen notwendig. Dies betrifft die Langzeitarchivierung von diagitalen Daten, die Moeglichkeiten zur Datenuebertragung und die Weiterentwicklung der verfuegbaren Software, auch was den Bedienkomfort und die Dokumentation anbelangt. Zudem ist es notwendig, die Exaktheit der Koregistrierung und damit die Qualitaet der Bildfusion durch kontrollierte Studien zu validieren. (orig.)

  13. Picosecond imaging of inertial confinement fusion plasmas using electron pulse-dilation

    Science.gov (United States)

    Hilsabeck, T. J.; Nagel, S. R.; Hares, J. D.; Kilkenny, J. D.; Bell, P. M.; Bradley, D. K.; Dymoke-Bradshaw, A. K. L.; Piston, K.; Chung, T. M.

    2017-02-01

    Laser driven inertial confinement fusion (ICF) plasmas typically have burn durations on the order of 100 ps. Time resolved imaging of the x-ray self emission during the hot spot formation is an important diagnostic tool which gives information on implosion symmetry, transient features and stagnation time. Traditional x-ray gated imagers for ICF use microchannel plate detectors to obtain gate widths of 40-100 ps. The development of electron pulse-dilation imaging has enabled a 10X improvement in temporal resolution over legacy instruments. In this technique, the incoming x-ray image is converted to electrons at a photocathode. The electrons are accelerated with a time-varying potential that leads to temporal expansion as the electron signal transits the tube. This expanded signal is recorded with a gated detector and the effective temporal resolution of the composite system can be as low as several picoseconds. An instrument based on this principle, known as the Dilation X-ray Imager (DIXI) has been constructed and fielded at the National Ignition Facility. Design features and experimental results from DIXI will be presented.

  14. X-ray crystal imagers for inertial confinement fusion experiments (invited)

    International Nuclear Information System (INIS)

    Aglitskiy, Y.; Lehecka, T.; Obenschain, S.; Pawley, C.; Brown, C.M.; Seely, J.

    1999-01-01

    We report on our continued development of high resolution monochromatic x-ray imaging system based on spherically curved crystals. This system can be extensively used in the relevant experiments of the inertial confinement fusion (ICF) program. The system is currently used, but not limited to diagnostics of the targets ablatively accelerated by the Nike KrF laser. A spherically curved quartz crystal (2d=6.68703 Angstrom, R=200mm) has been used to produce monochromatic backlit images with the He-like Si resonance line (1865 eV) as the source of radiation. Another quartz crystal (2d=8.5099 Angstrom, R=200mm) with the H-like Mg resonance line (1473 eV) has been used for backlit imaging with higher contrast. The spatial resolution of the x-ray optical system is 1.7 μm in selected places and 2 - 3 μm over a larger area. A second crystal with a separate backlighter was added to the imaging system. This makes it possible to make use of all four strips of the framing camera. Time resolved, 20x magnified, backlit monochromatic images of CH planar targets driven by the Nike facility have been obtained with spatial resolution of 2.5 μm in selected places and 5 μm over the focal spot of the Nike laser. We are exploring the enhancement of this technique to the higher and lower backlighter energies. copyright 1999 American Institute of Physics

  15. Preoperative magnetic resonance and intraoperative ultrasound fusion imaging for real-time neuronavigation in brain tumor surgery.

    Science.gov (United States)

    Prada, F; Del Bene, M; Mattei, L; Lodigiani, L; DeBeni, S; Kolev, V; Vetrano, I; Solbiati, L; Sakas, G; DiMeco, F

    2015-04-01

    Brain shift and tissue deformation during surgery for intracranial lesions are the main actual limitations of neuro-navigation (NN), which currently relies mainly on preoperative imaging. Ultrasound (US), being a real-time imaging modality, is becoming progressively more widespread during neurosurgical procedures, but most neurosurgeons, trained on axial computed tomography (CT) and magnetic resonance imaging (MRI) slices, lack specific US training and have difficulties recognizing anatomic structures with the same confidence as in preoperative imaging. Therefore real-time intraoperative fusion imaging (FI) between preoperative imaging and intraoperative ultrasound (ioUS) for virtual navigation (VN) is highly desirable. We describe our procedure for real-time navigation during surgery for different cerebral lesions. We performed fusion imaging with virtual navigation for patients undergoing surgery for brain lesion removal using an ultrasound-based real-time neuro-navigation system that fuses intraoperative cerebral ultrasound with preoperative MRI and simultaneously displays an MRI slice coplanar to an ioUS image. 58 patients underwent surgery at our institution for intracranial lesion removal with image guidance using a US system equipped with fusion imaging for neuro-navigation. In all cases the initial (external) registration error obtained by the corresponding anatomical landmark procedure was below 2 mm and the craniotomy was correctly placed. The transdural window gave satisfactory US image quality and the lesion was always detectable and measurable on both axes. Brain shift/deformation correction has been successfully employed in 42 cases to restore the co-registration during surgery. The accuracy of ioUS/MRI fusion/overlapping was confirmed intraoperatively under direct visualization of anatomic landmarks and the error was surgery and is less expensive and time-consuming than other intraoperative imaging techniques, offering high precision and

  16. Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

    Energy Technology Data Exchange (ETDEWEB)

    Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp [Faculty of Radiological Technology, School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi 470-1192 (Japan); Fujita, Hiroshi [Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu 501-1194 (Japan); Yamamuro, Osamu; Tamaki, Tsuneo [East Nagoya Imaging Diagnosis Center, 3-4-26 Jiyugaoka, Chikusa-ku, Nagoya, Aichi 464-0044 (Japan)

    2016-06-15

    Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using an active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules

  17. Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

    International Nuclear Information System (INIS)

    Teramoto, Atsushi; Fujita, Hiroshi; Yamamuro, Osamu; Tamaki, Tsuneo

    2016-01-01

    Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using an active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules

  18. Blind image fusion for hyperspectral imaging with the directional total variation

    Science.gov (United States)

    Bungert, Leon; Coomes, David A.; Ehrhardt, Matthias J.; Rasch, Jennifer; Reisenhofer, Rafael; Schönlieb, Carola-Bibiane

    2018-04-01

    Hyperspectral imaging is a cutting-edge type of remote sensing used for mapping vegetation properties, rock minerals and other materials. A major drawback of hyperspectral imaging devices is their intrinsic low spatial resolution. In this paper, we propose a method for increasing the spatial resolution of a hyperspectral image by fusing it with an image of higher spatial resolution that was obtained with a different imaging modality. This is accomplished by solving a variational problem in which the regularization functional is the directional total variation. To accommodate for possible mis-registrations between the two images, we consider a non-convex blind super-resolution problem where both a fused image and the corresponding convolution kernel are estimated. Using this approach, our model can realign the given images if needed. Our experimental results indicate that the non-convexity is negligible in practice and that reliable solutions can be computed using a variety of different optimization algorithms. Numerical results on real remote sensing data from plant sciences and urban monitoring show the potential of the proposed method and suggests that it is robust with respect to the regularization parameters, mis-registration and the shape of the kernel.

  19. Ant Colony Clustering Algorithm and Improved Markov Random Fusion Algorithm in Image Segmentation of Brain Images

    Directory of Open Access Journals (Sweden)

    Guohua Zou

    2016-12-01

    Full Text Available New medical imaging technology, such as Computed Tomography and Magnetic Resonance Imaging (MRI, has been widely used in all aspects of medical diagnosis. The purpose of these imaging techniques is to obtain various qualitative and quantitative data of the patient comprehensively and accurately, and provide correct digital information for diagnosis, treatment planning and evaluation after surgery. MR has a good imaging diagnostic advantage for brain diseases. However, as the requirements of the brain image definition and quantitative analysis are always increasing, it is necessary to have better segmentation of MR brain images. The FCM (Fuzzy C-means algorithm is widely applied in image segmentation, but it has some shortcomings, such as long computation time and poor anti-noise capability. In this paper, firstly, the Ant Colony algorithm is used to determine the cluster centers and the number of FCM algorithm so as to improve its running speed. Then an improved Markov random field model is used to improve the algorithm, so that its antinoise ability can be improved. Experimental results show that the algorithm put forward in this paper has obvious advantages in image segmentation speed and segmentation effect.

  20. Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

    Science.gov (United States)

    LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

  1. Dynamic in vivo imaging and cell tracking using a histone fluorescent protein fusion in mice

    Directory of Open Access Journals (Sweden)

    Papaioannou Virginia E

    2004-12-01

    Full Text Available Abstract Background Advances in optical imaging modalities and the continued evolution of genetically-encoded fluorescent proteins are coming together to facilitate the study of cell behavior at high resolution in living organisms. As a result, imaging using autofluorescent protein reporters is gaining popularity in mouse transgenic and targeted mutagenesis applications. Results We have used embryonic stem cell-mediated transgenesis to label cells at sub-cellular resolution in vivo, and to evaluate fusion of a human histone protein to green fluorescent protein for ubiquitous fluorescent labeling of nucleosomes in mice. To this end we have generated embryonic stem cells and a corresponding strain of mice that is viable and fertile and exhibits widespread chromatin-localized reporter expression. High levels of transgene expression are maintained in a constitutive manner. Viability and fertility of homozygous transgenic animals demonstrates that this reporter is developmentally neutral and does not interfere with mitosis or meiosis. Conclusions Using various optical imaging modalities including wide-field, spinning disc confocal, and laser scanning confocal and multiphoton excitation microscopy, we can identify cells in various stages of the cell cycle. We can identify cells in interphase, cells undergoing mitosis or cell death. We demonstrate that this histone fusion reporter allows the direct visualization of active chromatin in situ. Since this reporter segments three-dimensional space, it permits the visualization of individual cells within a population, and so facilitates tracking cell position over time. It is therefore attractive for use in multidimensional studies of in vivo cell behavior and cell fate.

  2. Fusion of High b-valve diffusion-weighted and T2-weighted MR images improves identification of lymph nodes in the pelvis

    International Nuclear Information System (INIS)

    Mir, N.; Sohaib, S.A.; Collins, D.; Koh, D.M.

    2010-01-01

    Full text: Accurate identification of lymph nodes facilities nodal assessment by size, morphological or MR lymphographic criteria. We compared the MR detection of lymph nodes in patients with pelvic cancers using T2-weighted imaging, and fusion of diffusion-weighted imaging (OWl) and T2-weighted imaging. Twenty patients with pelvic tumours underwent 5-mm axial T2-weighted and OWl (b-values 0-750 s/mm 2 ) on a L 5T system. Fusion images of b = 750 s/mm 2 diffusion-weighted MR and T2-weighted images were created. Two radiologists evaluated in consensus the T2-weighted images and fusion images independently. For each image set, the location and diameter of pelvic nodes were recorded, and nodal visibility was scored using a 4-point scale (0-3). Nodal visualisation was compared using Relative to an Identified Distribution (RIDIT) analysis. The mean RIDIT score describes the probability that a randomly selected node will be better visualised relative to the other image set. One hundred fourteen pelvic nodes (mean 5.9 mm; 2-10 mm) were identified on T2-weighted images and 161 nodes (mean 4.3 mm; 2-10 mm) on fusion images. Using fusion images, 47 additional nodes were detected compared with T2-weighted images alone (eight external iliac, 24 inguinal, 12 obturator, two peri-rectal, one presacral). Nodes detected only on fusion images were 2-9 mm (mean 3.7 mm). Nodal visualisation was better using fusion images compared with T2-weighted images (mean RIDIT score 0.689 vs 0.302). Fusion of diffusion-weighted MR with T2-weighted images improves identification of pelvic lymph nodes compared with T2-weighted images alone. The improved nodal identification may aid treatment planning and further nodal characterisation.

  3. Multimodality cranial image fusion using external markers applied via a vacuum mouthpiece and a case report

    International Nuclear Information System (INIS)

    Sweeney, R.A.; Seydl, K.; Lukas, P.; Bale, R.J.; Trieb, T.; Moncayo, R.; Donnemiller, E.; Eisner, W.; Burtscher, J.; Stockhammer, G.

    2003-01-01

    Purpose: To present a simple and precise method of combining functional information of cranial SPECT and PET images with CT and MRI, in any combination. Material and Methods: Imaging is performed with a hockey mask-like reference frame with image modality-specific markers in precisely defined positions. This frame is reproducibly connected to the VBH vacuum mouthpiece, granting objectively identical repositioning of the frame with respect to the cranium. Using these markers, the desired 3-D imaging modalities can then be manually or automatically registered. This information can be used for diagnosis, treatment planning, and evaluation of follow-up, while the same vacuum mouthpiece allows precisely reproducible stereotactic head fixation during radiotherapy. Results: 244 CT and MR data sets of 49 patients were registered to a root square mean error (RSME) of 0.9 mm (mean). 64 SPECT-CT fusions on 18 of these patients gave an RMSE of 1.4 mm, and 40 PET-CT data sets of eight patients were registered to 1.3 mm. An example of the method is given by means of a case report of a 52-year-old patient with bilateral optic nerve meningioma. Conclusion: This technique is a simple, objective and accurate registration tool to combine diagnosis, treatment planning, treatment, and follow-up, all via an individualized vacuum mouthpiece. Especially for low-resolution PET and even more so for some very diffuse SPECT data sets, activity can now be accurately correlated to anatomic structures. (orig.)

  4. A pin diode x-ray camera for laser fusion diagnostic imaging: Final technical report

    International Nuclear Information System (INIS)

    Jernigan, J.G.

    1987-01-01

    An x-ray camera has been constructed and tested for diagnostic imaging of laser fusion targets at the Laboratory for Laser Energetics (LLE) of the University of Rochester. The imaging detector, developed by the Hughes Aircraft Company, is a germanium PIN diode array of 10 x 64 separate elements which are bump bonded to a silicon readout chip containing a separate low noise amplifier for each pixel element. The camera assembly consists of a pinhole alignment mechanism, liquid nitrogen cryostat with detector mount and a thin beryllium entrance window, and a shielded rack containing the analog and digital electronics for operations. This x-ray camera has been tested on the OMEGA laser target chamber, the primary laser target facility of LLE, and operated via an Ethernet link to a SUN Microsystems workstation. X-ray images of laser targets are presented. The successful operation of this particular x-ray camera is a demonstration of the viability of the hybrid detector technology for future imaging and spectroscopic applications. This work was funded by the Department of Energy (DOE) as a project of the National Laser Users Facility (NLUF)

  5. A new ensemble approach based chemosensor for the reversible detection of bio-thiols and its application in live cell imaging

    International Nuclear Information System (INIS)

    Wang, Yue; Zhang, Zhiqiang; Meng, Qingtao; He, Cheng; Zhang, Run; Duan, Chunying

    2016-01-01

    Based on an aldazine-copper chemosensing ensemble (NP-Cu 2+ ), a new fluorescence chemosensor for the detection of biothiols (Cys, Hcy and GSH) was designed and synthesized. In aqueous solution, the ligand NP exhibited high selectivity toward Cu 2+ ions by forming a 2:1 complex, accompanied with a dramatic fluorescence quenching and a notable bathochromic-shift of the absorbance band. Due to the high affinity of thiols and copper, the specific interaction of thiols (Cys, Hcy and GSH) with NP-Cu 2+ ensemble led to the liberation of the NP. As the result, recovery of fluorescence and UV–vis absorbance was observed. The detection limits of NP-Cu 2+ to Cys, Hcy and GSH were estimated to be 1.5 μM, 1.8 μM and 2.2 μM, respectively. The fluorescence “OFF–ON” circle can be repeated to a minimum of 5 times by the alternative addition of thiols and Cu 2+ , implying that NP-Cu 2+ is a recyclable chemosensor for thiols. Results of fluorescence microscopy imaging suggested that NP-Cu 2+ has potential to be used as a powerful tool for the detection of intracellular thiols.

  6. A new ensemble approach based chemosensor for the reversible detection of bio-thiols and its application in live cell imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yue; Zhang, Zhiqiang [Key Laboratory for Functional Material, Educational Department of Liaoning Province, University of Science and Technology Liaoning, Anshan 114051 (China); Meng, Qingtao, E-mail: qtmeng@ustl.edu.cn [Key Laboratory for Functional Material, Educational Department of Liaoning Province, University of Science and Technology Liaoning, Anshan 114051 (China); State Key Laboratory of Fine Chemicals, Dalian University of Technology, 2 Linggong Road, Dalian High-Tech Industrial Zone, 116024 (China); He, Cheng [State Key Laboratory of Fine Chemicals, Dalian University of Technology, 2 Linggong Road, Dalian High-Tech Industrial Zone, 116024 (China); Zhang, Run [Key Laboratory for Functional Material, Educational Department of Liaoning Province, University of Science and Technology Liaoning, Anshan 114051 (China); Department of Chemistry and Biomolecular Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, 2109 (Australia); Duan, Chunying, E-mail: cyduan@dlut.edu.cn [State Key Laboratory of Fine Chemicals, Dalian University of Technology, 2 Linggong Road, Dalian High-Tech Industrial Zone, 116024 (China)

    2016-07-15

    Based on an aldazine-copper chemosensing ensemble (NP-Cu{sup 2+}), a new fluorescence chemosensor for the detection of biothiols (Cys, Hcy and GSH) was designed and synthesized. In aqueous solution, the ligand NP exhibited high selectivity toward Cu{sup 2+} ions by forming a 2:1 complex, accompanied with a dramatic fluorescence quenching and a notable bathochromic-shift of the absorbance band. Due to the high affinity of thiols and copper, the specific interaction of thiols (Cys, Hcy and GSH) with NP-Cu{sup 2+} ensemble led to the liberation of the NP. As the result, recovery of fluorescence and UV–vis absorbance was observed. The detection limits of NP-Cu{sup 2+} to Cys, Hcy and GSH were estimated to be 1.5 μM, 1.8 μM and 2.2 μM, respectively. The fluorescence “OFF–ON” circle can be repeated to a minimum of 5 times by the alternative addition of thiols and Cu{sup 2+}, implying that NP-Cu{sup 2+} is a recyclable chemosensor for thiols. Results of fluorescence microscopy imaging suggested that NP-Cu{sup 2+} has potential to be used as a powerful tool for the detection of intracellular thiols.

  7. Diagnostic performance of fluorodeoxyglucose positron emission tomography/magnetic resonance imaging fusion images of gynecological malignant tumors. Comparison with positron emission tomography/computed tomography

    International Nuclear Information System (INIS)

    Nakajo, Kazuya; Tatsumi, Mitsuaki; Inoue, Atsuo

    2010-01-01

    We compared the diagnostic accuracy of fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and PET/magnetic resonance imaging (MRI) fusion images for gynecological malignancies. A total of 31 patients with gynecological malignancies were enrolled. FDG-PET images were fused to CT, T1- and T2-weighted images (T1WI, T2WI). PET-MRI fusion was performed semiautomatically. We performed three types of evaluation to demonstrate the usefulness of PET/MRI fusion images in comparison with that of inline PET/CT as follows: depiction of the uterus and the ovarian lesions on CT or MRI mapping images (first evaluation); additional information for lesion localization with PET and mapping images (second evaluation); and the image quality of fusion on interpretation (third evaluation). For the first evaluation, the score for T2WI (4.68±0.65) was significantly higher than that for CT (3.54±1.02) or T1WI (3.71±0.97) (P<0.01). For the second evaluation, the scores for the localization of FDG accumulation showing that T2WI (2.74±0.57) provided significantly more additional information for the identification of anatomical sites of FDG accumulation than did CT (2.06±0.68) or T1WI (2.23±0.61) (P<0.01). For the third evaluation, the three-point rating scale for the patient group as a whole demonstrated that PET/T2WI (2.72±0.54) localized the lesion significantly more convincingly than PET/CT (2.23±0.50) or PET/T1WI (2.29±0.53) (P<0.01). PET/T2WI fusion images are superior for the detection and localization of gynecological malignancies. (author)

  8. Offline fusion of co-registered intravascular ultrasound and frequency domain optical coherence tomography images for the analysis of human atherosclerotic plaques

    DEFF Research Database (Denmark)

    Räber, Lorenz; Heo, Jung Ho; Radu, Maria D

    2012-01-01

    To demonstrate the feasibility and potential usefulness of an offline fusion of matched optical coherence tomography (OCT) and intravascular ultrasound (IVUS)/virtual histology (IVUS-VH) images.......To demonstrate the feasibility and potential usefulness of an offline fusion of matched optical coherence tomography (OCT) and intravascular ultrasound (IVUS)/virtual histology (IVUS-VH) images....

  9. Assessment of ion kinetic effects in shock-driven inertial confinement fusion implosions using fusion burn imaging

    International Nuclear Information System (INIS)

    Rosenberg, M. J.; Séguin, F. H.; Rinderknecht, H. G.; Zylstra, A. B.; Li, C. K.; Sio, H.; Johnson, M. Gatu; Frenje, J. A.; Petrasso, R. D.; Amendt, P. A.; Wilks, S. C.; Pino, J.; Atzeni, S.; Hoffman, N. M.; Kagan, G.; Molvig, K.; Glebov, V. Yu.; Stoeckl, C.; Seka, W.; Marshall, F. J.

    2015-01-01

    The significance and nature of ion kinetic effects in D 3 He-filled, shock-driven inertial confinement fusion implosions are assessed through measurements of fusion burn profiles. Over this series of experiments, the ratio of ion-ion mean free path to minimum shell radius (the Knudsen number, N K ) was varied from 0.3 to 9 in order to probe hydrodynamic-like to strongly kinetic plasma conditions; as the Knudsen number increased, hydrodynamic models increasingly failed to match measured yields, while an empirically-tuned, first-step model of ion kinetic effects better captured the observed yield trends [Rosenberg et al., Phys. Rev. Lett. 112, 185001 (2014)]. Here, spatially resolved measurements of the fusion burn are used to examine kinetic ion transport effects in greater detail, adding an additional dimension of understanding that goes beyond zero-dimensional integrated quantities to one-dimensional profiles. In agreement with the previous findings, a comparison of measured and simulated burn profiles shows that models including ion transport effects are able to better match the experimental results. In implosions characterized by large Knudsen numbers (N K  ∼ 3), the fusion burn profiles predicted by hydrodynamics simulations that exclude ion mean free path effects are peaked far from the origin, in stark disagreement with the experimentally observed profiles, which are centrally peaked. In contrast, a hydrodynamics simulation that includes a model of ion diffusion is able to qualitatively match the measured profile shapes. Therefore, ion diffusion or diffusion-like processes are identified as a plausible explanation of the observed trends, though further refinement of the models is needed for a more complete and quantitative understanding of ion kinetic effects

  10. Assessment of ion kinetic effects in shock-driven inertial confinement fusion implosions using fusion burn imaging

    Energy Technology Data Exchange (ETDEWEB)

    Rosenberg, M. J., E-mail: mros@lle.rochester.edu; Séguin, F. H.; Rinderknecht, H. G.; Zylstra, A. B.; Li, C. K.; Sio, H.; Johnson, M. Gatu; Frenje, J. A.; Petrasso, R. D. [Plasma Science and Fusion Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Amendt, P. A.; Wilks, S. C.; Pino, J. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Atzeni, S. [Dipartimento SBAI, Università di Roma “La Sapienza” and CNISM, Via A. Scarpa 14-16, I-00161 Roma (Italy); Hoffman, N. M.; Kagan, G.; Molvig, K. [Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Glebov, V. Yu.; Stoeckl, C.; Seka, W.; Marshall, F. J. [Laboratory for Laser Energetics, University of Rochester, Rochester, New York 14623 (United States); and others

    2015-06-15

    The significance and nature of ion kinetic effects in D{sup 3}He-filled, shock-driven inertial confinement fusion implosions are assessed through measurements of fusion burn profiles. Over this series of experiments, the ratio of ion-ion mean free path to minimum shell radius (the Knudsen number, N{sub K}) was varied from 0.3 to 9 in order to probe hydrodynamic-like to strongly kinetic plasma conditions; as the Knudsen number increased, hydrodynamic models increasingly failed to match measured yields, while an empirically-tuned, first-step model of ion kinetic effects better captured the observed yield trends [Rosenberg et al., Phys. Rev. Lett. 112, 185001 (2014)]. Here, spatially resolved measurements of the fusion burn are used to examine kinetic ion transport effects in greater detail, adding an additional dimension of understanding that goes beyond zero-dimensional integrated quantities to one-dimensional profiles. In agreement with the previous findings, a comparison of measured and simulated burn profiles shows that models including ion transport effects are able to better match the experimental results. In implosions characterized by large Knudsen numbers (N{sub K} ∼ 3), the fusion burn profiles predicted by hydrodynamics simulations that exclude ion mean free path effects are peaked far from the origin, in stark disagreement with the experimentally observed profiles, which are centrally peaked. In contrast, a hydrodynamics simulation that includes a model of ion diffusion is able to qualitatively match the measured profile shapes. Therefore, ion diffusion or diffusion-like processes are identified as a plausible explanation of the observed trends, though further refinement of the models is needed for a more complete and quantitative understanding of ion kinetic effects.

  11. Pros and Cons of 3D Image Fusion in Endovascular Aortic Repair: A Systematic Review and Meta-analysis.

    Science.gov (United States)

    Goudeketting, Seline R; Heinen, Stefan G H; Ünlü, Çağdaş; van den Heuvel, Daniel A F; de Vries, Jean-Paul P M; van Strijen, Marco J; Sailer, Anna M

    2017-08-01

    To systematically review and meta-analyze the added value of 3-dimensional (3D) image fusion technology in endovascular aortic repair for its potential to reduce contrast media volume, radiation dose, procedure time, and fluoroscopy time. Electronic databases were systematically searched for studies published between January 2010 and March 2016 that included a control group describing 3D fusion imaging in endovascular aortic procedures. Two independent reviewers assessed the methodological quality of the included studies and extracted data on iodinated contrast volume, radiation dose, procedure time, and fluoroscopy time. The contrast use for standard and complex endovascular aortic repairs (fenestrated, branched, and chimney) were pooled using a random-effects model; outcomes are reported as the mean difference with 95% confidence intervals (CIs). Seven studies, 5 retrospective and 2 prospective, involving 921 patients were selected for analysis. The methodological quality of the studies was moderate (median 17, range 15-18). The use of fusion imaging led to an estimated mean reduction in iodinated contrast of 40.1 mL (95% CI 16.4 to 63.7, p=0.002) for standard procedures and a mean 70.7 mL (95% CI 44.8 to 96.6, p<0.001) for complex repairs. Secondary outcome measures were not pooled because of potential bias in nonrandomized data, but radiation doses, procedure times, and fluoroscopy times were lower, although not always significantly, in the fusion group in 6 of the 7 studies. Compared with the control group, 3D fusion imaging is associated with a significant reduction in the volume of contrast employed for standard and complex endovascular aortic procedures, which can be particularly important in patients with renal failure. Radiation doses, procedure times, and fluoroscopy times were reduced when 3D fusion was used.

  12. Imaging transient blood vessel fusion events in zebrafish by correlative volume electron microscopy.

    Directory of Open Access Journals (Sweden)

    Hannah E J Armer

    Full Text Available The study of biological processes has become increasingly reliant on obtaining high-resolution spatial and temporal data through imaging techniques. As researchers demand molecular resolution of cellular events in the context of whole organisms, correlation of non-invasive live-organism imaging with electron microscopy in complex three-dimensional samples becomes critical. The developing blood vessels of vertebrates form a highly complex network which cannot be imaged at high resolution using traditional methods. Here we show that the point of fusion between growing blood vessels of transgenic zebrafish, identified in live confocal microscopy, can subsequently be traced through the structure of the organism using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM and Serial Block Face/Scanning Electron Microscopy (SBF/SEM. The resulting data give unprecedented microanatomical detail of the zebrafish and, for the first time, allow visualization of the ultrastructure of a time-limited biological event within the context of a whole organism.

  13. Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

    Science.gov (United States)

    Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria

    2014-08-30

    Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

  14. Multiresolution image registration for multimodal brain images and fusion for better neurosurgical planning

    Directory of Open Access Journals (Sweden)

    Siddeshappa Nandish

    2017-12-01

    Conclusion: The end resultant fused images are validated by the radiologists and mutual information measure is used to validate registration results. It is found that CT and MRI sequence with more number of slices gave promising results. Few cases with deformation during misregistrations recorded with low mutual information of about 0.3 and which is not acceptable and few recorded with 0.6 and above mutual information during registration gives promising results.

  15. Clinical significance of creative 3D-image fusion across multimodalities [PET + CT + MR] based on characteristic coregistration

    International Nuclear Information System (INIS)

    Peng, Matthew Jian-qiao; Ju Xiangyang; Khambay, Balvinder S.; Ayoub, Ashraf F.; Chen, Chin-Tu; Bai Bo

    2012-01-01

    Objective: To investigate a registration approach for 2-dimension (2D) based on characteristic localization to achieve 3-dimension (3D) fusion from images of PET, CT and MR one by one. Method: A cubic oriented scheme of“9-point and 3-plane” for co-registration design was verified to be geometrically practical. After acquisiting DICOM data of PET/CT/MR (directed by radiotracer 18 F-FDG etc.), through 3D reconstruction and virtual dissection, human internal feature points were sorted to combine with preselected external feature points for matching process. By following the procedure of feature extraction and image mapping, “picking points to form planes” and “picking planes for segmentation” were executed. Eventually, image fusion was implemented at real-time workstation mimics based on auto-fuse techniques so called “information exchange” and “signal overlay”. Result: The 2D and 3D images fused across modalities of [CT + MR], [PET + MR], [PET + CT] and [PET + CT + MR] were tested on data of patients suffered from tumors. Complementary 2D/3D images simultaneously presenting metabolic activities and anatomic structures were created with detectable-rate of 70%, 56%, 54% (or 98%) and 44% with no significant difference for each in statistics. Conclusion: Currently, based on the condition that there is no complete hybrid detector integrated of triple-module [PET + CT + MR] internationally, this sort of multiple modality fusion is doubtlessly an essential complement for the existing function of single modality imaging.

  16. Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

    Science.gov (United States)

    Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

    2018-01-01

    Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

  17. Accuracy of volume measurement using 3D ultrasound and development of CT-3D US image fusion algorithm for prostate cancer radiotherapy

    International Nuclear Information System (INIS)

    Baek, Jihye; Huh, Jangyoung; Hyun An, So; Oh, Yoonjin; Kim, Myungsoo; Kim, DongYoung; Chung, Kwangzoo; Cho, Sungho; Lee, Rena

    2013-01-01

    Purpose: To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Methods: Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Results: Volume measurement, using 3D US, shows a 2.8 ± 1.5% error, 4.4 ± 3.0% error for CT, and 3.1 ± 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. Conclusions: 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.

  18. An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

    Science.gov (United States)

    Momeni, Saba; Pourghassem, Hossein

    2014-08-01

    Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

  19. EVALUATION OF METHODS FOR COREGISTRATION AND FUSION OF RPAS-BASED 3D POINT CLOUDS AND THERMAL INFRARED IMAGES

    Directory of Open Access Journals (Sweden)

    L. Hoegner

    2016-06-01

    Full Text Available This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

  20. Added Value of 3D Cardiac SPECT/CTA Fusion Imaging in Patients with Reversible Perfusion Defect on Myocardial Perfusion SPECT

    Energy Technology Data Exchange (ETDEWEB)

    Kong, Eun Jung; Cho, Ihn Ho [Yeungnam University Hospital, Daegu (Korea, Republic of); Kang, Won Jun [Yonsei University Hospital, Seoul (Korea, Republic of); Kim, Seong Min [Chungnam National University Medical School and Hospital, Daejeon (Korea, Republic of); Won, Kyoung Sook [Keomyung University Dongsan Hospital, Daegu (Korea, Republic of); Lim, Seok Tae [Chonbuk National University Medical School and Hospital, Jeonju (Korea, Republic of); Hwang, Kyung Hoon [Gachon University Gil Hospital, Incheon (Korea, Republic of); Lee, Byeong Il; Bom, Hee Seung [Chonnam National University Medical School and Hospital, Gwangju (Korea, Republic of)

    2009-12-15

    Integration of the functional information of myocardial perfusion SPECT (MPS) and the morphoanatomical information of coronary CT angiography (CTA) may provide useful additional diagnostic information of the spatial relationship between perfusion defects and coronary stenosis. We studied to know the added value of three dimensional cardiac SPECT/CTA fusion imaging (fusion image) by comparing between fusion image and MPS. Forty-eight patients (M:F=26:22, Age: 63.3{+-}10.4 years) with a reversible perfusion defect on MPS (adenosine stress/rest SPECT with Tc-99m sestamibi or tetrofosmin) and CTA were included. Fusion images were molded and compared with the findings from the MPS. Invasive coronary angiography served as a reference standard for fusion image and MPS. Total 144 coronary arteries in 48 patients were analyzed; Fusion image yielded the sensitivity, specificity, negative and positive predictive value for the detection of hemodynamically significant stenosis per coronary artery 82.5%, 79.3%, 76.7% and 84.6%, respectively. Respective values for the MPS were 68.8%, 70.7%, 62.1% and 76.4%. And fusion image also could detect more multi-vessel disease. Fused three dimensional volume-rendered SPECT/CTA imaging provides intuitive convincing information about hemodynamic relevant lesion and could improved diagnostic accuracy.

  1. HIGH SPATIAL RESOLUTION IMAGING OF INERTIAL FUSION TARGET PLASMAS USING BUBBLE NEUTRON DETECTORS

    International Nuclear Information System (INIS)

    FISHER, R.K.

    2003-01-01

    OAK B202 HIGH SPATIAL RESOLUTION IMAGING OF INERTIAL FUSION TARGET PLASMAS USING BUBBLE NEUTRON DETECTORS. Bubble detectors, which can detect neutrons with a spatial 5 to 30 (micro), are the most promising approach to imaging NIF target plasmas with the desired 5 (micro) spatial resolution in the target plane. Gel bubble detectors are being tested to record neutron images of ICF implosions in OMEGA experiments. By improving the noise reduction techniques used in analyzing the data taken in June 2000, we have been able to image the neutron emission from 6 · 10 13 yield DT target plasmas with a target plane spatial resolution of ∼ 140 (micro). As expected, the spatial resolution was limited by counting statistics as a result of the low neutron detection efficiency of the easy-to-use gel bubble detectors. The results have been submitted for publication and will be the subject of an invited talk at the October 2001 Meeting of the Division of Plasma Physics of the American Physical Society. To improve the counting statistics, data was taken in May 2001 using a stack of four gel detectors and integrated over a series of up to seven high-yield DT shots. Analysis of the 2001 data is still in its early stages. Gel detectors were chosen for these initial tests since the bubbles can be photographed several hours after the neutron exposure. They consist of ∼ 5000 drops (∼ 100 (micro) in diameter) of bubble detector liquid/cm 3 suspended in an inactive support gel that occupies ∼ 99% of the detector volume. Using a liquid bubble chamber detector and a light scattering system to record the bubble locations a few microseconds after the neutron exposure when the bubbles are ∼ 10 (micro) in diameter, should result in ∼ 1000 times higher neutron detection efficiency and a target plane resolution on OMEGA of ∼ 10 to 50 (micro)

  2. Testing a Modified PCA-Based Sharpening Approach for Image Fusion

    Directory of Open Access Journals (Sweden)

    Jan Jelének

    2016-09-01

    Full Text Available Image data sharpening is a challenging field of remote sensing science, which has become more relevant as high spatial-resolution satellites and superspectral sensors have emerged. Although the spectral property is crucial for mineral mapping, spatial resolution is also important as it allows targeted minerals/rocks to be identified/interpreted in a spatial context. Therefore, improving the spatial context, while keeping the spectral property provided by the superspectral sensor, would bring great benefits for geological/mineralogical mapping especially in arid environments. In this paper, a new concept was tested using superspectral data (ASTER and high spatial-resolution panchromatic data (WorldView-2 for image fusion. A modified Principal Component Analysis (PCA-based sharpening method, which implements a histogram matching workflow that takes into account the real distribution of values, was employed to test whether the substitution of Principal Components (PC1–PC4 can bring a fused image which is spectrally more accurate. The new approach was compared to those most widely used—PCA sharpening and Gram–Schmidt sharpening (GS, both available in ENVI software (Version 5.2 and lower as well as to the standard approach—sharpening Landsat 8 multispectral bands (MUL using its own panchromatic (PAN band. The visual assessment and the spectral quality indicators proved that the spectral performance of the proposed sharpening approach employing PC1 and PC2 improve the performance of the PCA algorithm, moreover, comparable or better results are achieved compared to the GS method. It was shown that, when using the PC1, the visible-near infrared (VNIR part of the spectrum was preserved better, however, if the PC2 was used, the short-wave infrared (SWIR part was preserved better. Furthermore, this approach improved the output spectral quality when fusing image data from different sensors (e.g., ASTER and WorldView-2 while keeping the proper albedo

  3. Cost-Effectiveness Comparison of Imaging-Guided Prostate Biopsy Techniques: Systematic Transrectal Ultrasound, Direct In-Bore MRI, and Image Fusion

    NARCIS (Netherlands)

    Venderink, W.; Govers, T.M.; Rooij, M. de; Futterer, J.J.; Sedelaar, J.P.M.

    2017-01-01

    OBJECTIVE: Three commonly used prostate biopsy approaches are systematic transrectal ultrasound guided, direct in-bore MRI guided, and image fusion guided. The aim of this study was to calculate which strategy is most cost-effective. MATERIALS AND METHODS: A decision tree and Markov model were

  4. Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

    Science.gov (United States)

    Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

    2017-03-01

    It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

  5. Refraction-enhanced backlit imaging of axially symmetric inertial confinement fusion plasmas.

    Science.gov (United States)

    Koch, Jeffrey A; Landen, Otto L; Suter, Laurence J; Masse, Laurent P; Clark, Daniel S; Ross, James S; Mackinnon, Andrew J; Meezan, Nathan B; Thomas, Cliff A; Ping, Yuan

    2013-05-20

    X-ray backlit radiographs of dense plasma shells can be significantly altered by refraction of x rays that would otherwise travel straight-ray paths, and this effect can be a powerful tool for diagnosing the spatial structure of the plasma being radiographed. We explore the conditions under which refraction effects may be observed, and we use analytical and numerical approaches to quantify these effects for one-dimensional radial opacity and density profiles characteristic of inertial-confinement fusion (ICF) implosions. We also show how analytical and numerical approaches allow approximate radial plasma opacity and density profiles to be inferred from point-projection refraction-enhanced radiography data. This imaging technique can provide unique data on electron density profiles in ICF plasmas that cannot be obtained using other techniques, and the uniform illumination provided by point-like x-ray backlighters eliminates a significant source of uncertainty in inferences of plasma opacity profiles from area-backlit pinhole imaging data when the backlight spatial profile cannot be independently characterized. The technique is particularly suited to in-flight radiography of imploding low-opacity shells surrounding hydrogen ice, because refraction is sensitive to the electron density of the hydrogen plasma even when it is invisible to absorption radiography. It may also provide an alternative approach to timing shockwaves created by the implosion drive, that are currently invisible to absorption radiography.

  6. In vivo imaging of brain ischemia using an oxygen-dependent degradative fusion protein probe.

    Directory of Open Access Journals (Sweden)

    Youshi Fujita

    Full Text Available Within the ischemic penumbra, blood flow is sufficiently reduced that it results in hypoxia severe enough to arrest physiological function. Nevertheless, it has been shown that cells present within this region can be rescued and resuscitated by restoring perfusion and through other protective therapies. Thus, the early detection of the ischemic penumbra can be exploited to improve outcomes after focal ischemia. Hypoxia-inducible factor (HIF-1 is a transcription factor induced by a reduction in molecular oxygen levels. Although the role of HIF-1 in the ischemic penumbra remains unknown, there is a strong correlation between areas with HIF-1 activity and the ischemic penumbra. We recently developed a near-infrared fluorescently labeled-fusion protein, POH-N, with an oxygen-dependent degradation property identical to the alpha subunit of HIF-1. Here, we conduct in vivo imaging of HIF-active regions using POH-N in ischemic brains after transient focal cerebral ischemia induced using the intraluminal middle cerebral artery occlusion technique in mice. The results demonstrate that POH-N enables the in vivo monitoring and ex vivo detection of HIF-1-active regions after ischemic brain injury and suggest its potential in imaging and drug delivery to HIF-1-active areas in ischemic brains.

  7. Quantum ensembles of quantum classifiers.

    Science.gov (United States)

    Schuld, Maria; Petruccione, Francesco

    2018-02-09

    Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

  8. Content-Based High-Resolution Remote Sensing Image Retrieval via Unsupervised Feature Learning and Collaborative Affinity Metric Fusion

    Directory of Open Access Journals (Sweden)

    Yansheng Li

    2016-08-01

    Full Text Available With the urgent demand for automatic management of large numbers of high-resolution remote sensing images, content-based high-resolution remote sensing image retrieval (CB-HRRS-IR has attracted much research interest. Accordingly, this paper proposes a novel high-resolution remote sensing image retrieval approach via multiple feature representation and collaborative affinity metric fusion (IRMFRCAMF. In IRMFRCAMF, we design four unsupervised convolutional neural networks with different layers to generate four types of unsupervised features from the fine level to the coarse level. In addition to these four types of unsupervised features, we also implement four traditional feature descriptors, including local binary pattern (LBP, gray level co-occurrence (GLCM, maximal response 8 (MR8, and scale-invariant feature transform (SIFT. In order to fully incorporate the complementary information among multiple features of one image and the mutual information across auxiliary images in the image dataset, this paper advocates collaborative affinity metric fusion to measure the similarity between images. The performance evaluation of high-resolution remote sensing image retrieval is implemented on two public datasets, the UC Merced (UCM dataset and the Wuhan University (WH dataset. Large numbers of experiments show that our proposed IRMFRCAMF can significantly outperform the state-of-the-art approaches.

  9. Fiducial-based fusion of 3D dental models with magnetic resonance imaging.

    Science.gov (United States)

    Abdi, Amir H; Hannam, Alan G; Fels, Sidney

    2018-04-16

    Magnetic resonance imaging (MRI) is widely used in study of maxillofacial structures. While MRI is the modality of choice for soft tissues, it fails to capture hard tissues such as bone and teeth. Virtual dental models, acquired by optical 3D scanners, are becoming more accessible for dental practice and are starting to replace the conventional dental impressions. The goal of this research is to fuse the high-resolution 3D dental models with MRI to enhance the value of imaging for applications where detailed analysis of maxillofacial structures are needed such as patient examination, surgical planning, and modeling. A subject-specific dental attachment was digitally designed and 3D printed based on the subject's face width and dental anatomy. The attachment contained 19 semi-ellipsoidal concavities in predetermined positions where oil-based ellipsoidal fiducial markers were later placed. The MRI was acquired while the subject bit on the dental attachment. The spatial position of the center of mass of each fiducial in the resultant MR Image was calculated by averaging its voxels' spatial coordinates. The rigid transformation to fuse dental models to MRI was calculated based on the least squares mapping of corresponding fiducials and solved via singular-value decomposition. The target registration error (TRE) of the proposed fusion process, calculated in a leave-one-fiducial-out fashion, was estimated at 0.49 mm. The results suggest that 6-9 fiducials suffice to achieve a TRE of equal to half the MRI voxel size. Ellipsoidal oil-based fiducials produce distinguishable intensities in MRI and can be used as registration fiducials. The achieved accuracy of the proposed approach is sufficient to leverage the merged 3D dental models with the MRI data for a finer analysis of the maxillofacial structures where complete geometry models are needed.

  10. Robust super-resolution by fusion of interpolated frames for color and grayscale images

    Directory of Open Access Journals (Sweden)

    Barry eKarch

    2015-04-01

    Full Text Available Multi-frame super-resolution (SR processing seeks to overcome undersampling issues that can lead to undesirable aliasing artifacts. The key to effective multi-frame SR is accurate subpixel inter-frame registration. This accurate registration is challenging when the motion does not obey a simple global translational model and may include local motion. SR processing is further complicated when the camera uses a division-of-focal-plane (DoFP sensor, such as the Bayer color filter array. Various aspects of these SR challenges have been previously investigated. Fast SR algorithms tend to have difficulty accommodating complex motion and DoFP sensors. Furthermore, methods that can tolerate these complexities tend to be iterative in nature and may not be amenable to real-time processing. In this paper, we present a new fast approach for performing SR in the presence of these challenging imaging conditions. We refer to the new approach as Fusion of Interpolated Frames (FIF SR. The FIF SR method decouples the demosaicing, interpolation, and restoration steps to simplify the algorithm. Frames are first individually demosaiced and interpolated to the desired resolution. Next, FIF uses a novel weighted sum of the interpolated frames to fuse them into an improved resolution estimate. Finally, restoration is applied to deconvolve the modeled system PSF. The proposed FIF approach has a lower computational complexity than most iterative methods, making it a candidate for real-time implementation. We provide a detailed description of the FIF SR method and show experimental results using synthetic and real datasets in both constrained and complex imaging scenarios. The experiments include airborne grayscale imagery and Bayer color array images with affine background motion plus local motion.

  11. A modified VMAT adaptive radiotherapy for nasopharyngeal cancer patients based on CT-CT image fusion

    International Nuclear Information System (INIS)

    Jin, Xiance; Han, Ce; Zhou, Yongqiang; Yi, Jinling; Yan, Huawei; Xie, Congying

    2013-01-01

    To investigate the feasibility and benefits of a modified adaptive radiotherapy (ART) by replanning in the initial CT (iCT) with new contours from a repeat CT (rCT) based on CT-CT image fusion for nasopharyngeal cancer (NPC) patients underwent volumetric modulated arc radiotherapy (VMAT). Nine NPC patients underwent VMAT treatment with a rCT at 23rd fraction were enrolled in this study. Dosimetric differences for replanning VMAT plans in the iCT and in the rCT were compared. Volumetric and dosimetric changes of gross tumor volume (GTV) and organs at risk (OARs) of this modified ART were also investigated. No dosimetric differences between replanning in the iCT and in the rCT were observed. The average volume of GTV decreased from 78.83 ± 38.42 cm 3 in the iCT to 71.44 ± 37.46 cm 3 in the rCT, but with no significant difference (p = 0.42).The average volume of the left and right parotid decreased from 19.91 ± 4.89 cm 3 and 21.58 ± 6.16 cm 3 in the iCT to 11.80 ± 2.79 cm 3 and 13.29 ± 4.17 cm 3 in the rCT (both p < 0.01), respectively. The volume of other OARs did not shrink very much. No significant differences on PTV GTV and PTV CTV coverage were observed for replanning with this modified ART. Compared to the initial plans, the average mean dose of the left and right parotid after re-optimization were decreased by 62.5 cGy (p = 0.05) and 67.3 cGy (p = 0.02), respectively, and the V5 (the volume receiving 5 Gy) of the left and right parotids were decreased by 7.8% (p = 0.01) and 11.2% (p = 0.001), respectively. There was no significant difference on the dose delivered to other OARs. Patients with NPC undergoing VMAT have significant anatomic and dosimetric changes to parotids. Repeat CT as an anatomic changes reference and re-optimization in the iCT based on CT-CT image fusion was accurate enough to identify the volume changes and to ensure safe dose to parotids

  12. World Music Ensemble: Kulintang

    Science.gov (United States)

    Beegle, Amy C.

    2012-01-01

    As instrumental world music ensembles such as steel pan, mariachi, gamelan and West African drums are becoming more the norm than the exception in North American school music programs, there are other world music ensembles just starting to gain popularity in particular parts of the United States. The kulintang ensemble, a drum and gong ensemble…

  13. Biodistribution and tumor imaging of an anti-CEA single-chain antibody-albumin fusion protein

    International Nuclear Information System (INIS)

    Yazaki, Paul J.; Kassa, Thewodros; Cheung, Chia-wei; Crow, Desiree M.; Sherman, Mark A.; Bading, James R.; Anderson, Anne-Line J.; Colcher, David; Raubitschek, Andrew

    2008-01-01

    Albumin fusion proteins have demonstrated the ability to prolong the in vivo half-life of small therapeutic proteins/peptides in the circulation and thereby potentially increase their therapeutic efficacy. To evaluate if this format can be employed for antibody-based imaging, an anticarcinoembryonic antigen (CEA) single-chain antibody(scFv)-albumin fusion protein was designed, expressed and radiolabeled for biodistribution and imaging studies in athymic mice bearing human colorectal carcinoma LS-174T xenografts. The [ 125 I]-T84.66 fusion protein demonstrated rapid tumor uptake of 12.3% injected dose per gram (ID/g) at 4 h that reached a plateau of 22.7% ID/g by 18 h. This was a dramatic increase in tumor uptake compared to 4.9% ID/g for the scFv alone. The radiometal [ 111 In]-labeled version resulted in higher tumor uptake, 37.2% ID/g at 18 h, which persisted at the tumor site with tumor: blood ratios reaching 18:1 and with normal tissues showing limited uptake. Based on these favorable imaging properties, a pilot [ 64 Cu]-positron emission tomography imaging study was performed with promising results. The anti-CEA T84.66 scFv-albumin fusion protein demonstrates highly specific tumor uptake that is comparable to cognate recombinant antibody fragments. The radiometal-labeled version, which shows lower normal tissue accumulation than these recombinant antibodies, provides a promising and novel platform for antibody-based imaging agents

  14. Three-way (N-way) fusion of brain imaging data based on mCCA+jICA and its application to discriminating schizophrenia

    NARCIS (Netherlands)

    J. Sui (Jing); H. He (Hao); G. Pearlson (Godfrey); T. Adali (Tülay); K.A. Kiehl (Kent ); Q. Yu (Qingbao); V.P. Clark; E. Castro (Elena); T.J.H. White (Tonya); B.A. Mueller (Bryon ); B.C. Ho (Beng ); N.C. Andreasen; V.D. Calhoun (Vince)

    2013-01-01

    textabstractMultimodal fusion is an effective approach to better understand brain diseases. However, most such instances have been limited to pair-wise fusion; because there are often more than two imaging modalities available per subject, there is a need for approaches that can combine multiple

  15. A proposal of Fourier-Bessel expansion with optimized ensembles of bases to analyse two dimensional image

    Science.gov (United States)

    Yamasaki, K.; Fujisawa, A.; Nagashima, Y.

    2017-09-01

    It is a critical issue to find the best set of fitting function bases in mode structural analysis of two dimensional images like plasma emission profiles. The paper proposes a method to optimize a set of the bases in the case of Fourier-Bessel function series, using their orthonormal property, for more efficient and precise analysis. The method is applied on a tomography image of plasma emission obtained with the Maximum-likelihood expectation maximization method in a linear cylindrical device. The result demonstrates the excellency of the method that realizes the smaller residual error and minimum Akaike information criterion using smaller number of fitting function bases.

  16. A Comparison of Accuracy of Image- versus Hardware-based Tracking Technologies in 3D Fusion in Aortic Endografting.

    Science.gov (United States)

    Rolls, A E; Maurel, B; Davis, M; Constantinou, J; Hamilton, G; Mastracci, T M

    2016-09-01

    Fusion of three-dimensional (3D) computed tomography and intraoperative two-dimensional imaging in endovascular surgery relies on manual rigid co-registration of bony landmarks and tracking of hardware to provide a 3D overlay (hardware-based tracking, HWT). An alternative technique (image-based tracking, IMT) uses image recognition to register and place the fusion mask. We present preliminary experience with an agnostic fusion technology that uses IMT, with the aim of comparing the accuracy of overlay for this technology with HWT. Data were collected prospectively for 12 patients. All devices were deployed using both IMT and HWT fusion assistance concurrently. Postoperative analysis of both systems was performed by three blinded expert observers, from selected time-points during the procedures, using the displacement of fusion rings, the overlay of vascular markings and the true ostia of renal arteries. The Mean overlay error and the deviation from mean error was derived using image analysis software. Comparison of the mean overlay error was made between IMT and HWT. The validity of the point-picking technique was assessed. IMT was successful in all of the first 12 cases, whereas technical learning curve challenges thwarted HWT in four cases. When independent operators assessed the degree of accuracy of the overlay, the median error for IMT was 3.9 mm (IQR 2.89-6.24, max 9.5) versus 8.64 mm (IQR 6.1-16.8, max 24.5) for HWT (p = .001). Variance per observer was 0.69 mm(2) and 95% limit of agreement ±1.63. In this preliminary study, the error of magnitude of displacement from the "true anatomy" during image overlay in IMT was less than for HWT. This confirms that ongoing manual re-registration, as recommended by the manufacturer, should be performed for HWT systems to maintain accuracy. The error in position of the fusion markers for IMT was consistent, thus may be considered predictable. Copyright © 2016 European Society for Vascular Surgery. Published by

  17. Imaging of dihydrofolate reductase fusion gene expression in xenografts of human liver metastases of colorectal cancer in living rats

    Energy Technology Data Exchange (ETDEWEB)

    Mayer-Kuckuk, Philipp; Bertino, Joseph R.; Banerjee, Debabrata [Molecular Pharmacology and Therapeutics Program, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); The Cancer Institute of New Jersey, Robert Wood Johnson Medical School/UMDNJ, 195 Little Albany Street, NJ 08903, New Brunswick (United States); Doubrovin, Mikhail; Blasberg, Ronald; Tjuvajev, Juri Gelovani [Department of Neurooncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Gusani, Niraj J.; Fong, Yuman [Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Gade, Terence; Koutcher, Jason A. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Balatoni, Julius; Finn, Ronald [Radiochemistry/Cyclotron Core Facility, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Akhurst, Tim; Larson, Steven [Nuclear Medicine Service, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)

    2003-09-01

    Radionuclide imaging has been demonstrated to be feasible to monitor transgene expression in vivo. We hypothesized that a potential application of this technique is to non-invasively detect in deep tissue, such as cancer cells metastatic to the liver, a specific molecular response following systemic drug treatment. Utilizing human colon adenocarcinoma cells derived from a patient's liver lesion we first developed a nude rat xenograft model for colorectal cancer metastatic to the liver. Expression of a dihydrofolate reductase-herpes simplex virus 1 thymidine kinase fusion (DHFR-HSV1 TK) transgene in the hepatic tumors was monitored in individual animals using the tracer [{sup 124}I]2'-fluoro-2'-deoxy-5-iodouracil-{beta}-d-arabinofuranoside (FIAU) and a small animal micro positron emission tomograph (microPET), while groups of rats were imaged using the tracer [{sup 131}I]FIAU and a clinical gamma camera. Growth of the human metastatic colorectal cancer cells in the rat liver was detected using magnetic resonance imaging and confirmed by surgical inspection. Single as well as multiple lesions of different sizes and sites were observed in the liver of the animals. Next, using a subset of rats bearing hepatic tumors, which were retrovirally bulk transduced to express the DHFR-HSV1 TK transgene, we imaged the fusion protein expression in the hepatic tumor of living rats using the tracer [{sup 124}I]FIAU and a microPET. The observed deep tissue signals were highly specific for the tumors expressing the DHFR-HSV1 TK fusion protein compared with parental untransduced tumors and other tissues as determined by gamma counting of tissue samples. A subsequent study used the tracer [{sup 131}I]FIAU and a gamma camera to monitor two groups of transduced hepatic tumor-bearing rats. Prior to imaging, one group was treated with trimetrexate to exploit DHFR-mediated upregulation of the fusion gene product. Imaging in the living animal as well as subsequent gamma

  18. Multi-information fusion sparse coding with preserving local structure for hyperspectral image classification

    Science.gov (United States)

    Wei, Xiaohui; Zhu, Wen; Liao, Bo; Gu, Changlong; Li, Weibiao

    2017-10-01

    The key question of sparse coding (SC) is how to exploit the information that already exists to acquire the robust sparse representations (SRs) of distinguishing different objects for hyperspectral image (HSI) classification. We propose a multi-information fusion SC framework, which fuses the spectral, spatial, and label information in the same level, to solve the above question. In particular, pixels from disjointed spatial clusters, which are obtained by cutting the given HSI in space, are individually and sparsely encoded. Then, due to the importance of spatial structure, graph- and hypergraph-based regularizers are enforced to motivate the obtained representations smoothness and to preserve the local consistency for each spatial cluster. The latter simultaneously considers the spectrum, spatial, and label information of multiple pixels that have a great probability with the same label. Finally, a linear support vector machine is selected as the final classifier with the learned SRs as input. Experiments conducted on three frequently used real HSIs show that our methods can achieve satisfactory results compared with other state-of-the-art methods.

  19. Fusion imaging of computed tomographic pulmonary angiography and SPECT ventilation/perfusion scintigraphy: initial experience and potential benefit

    International Nuclear Information System (INIS)

    Harris, Benjamin; Bailey, Dale; Roach, Paul; Bailey, Elizabeth; King, Gregory

    2007-01-01

    The objective of this study was to examine the feasibility of fusing ventilation and perfusion data from single-photon emission computed tomography (SPECT) ventilation perfusion (V/Q) scintigraphy together with computed tomographic pulmonary angiography (CTPA) data. We sought to determine the accuracy of this fusion process. In addition, we correlated the findings of this technique with the final clinical diagnosis. Thirty consecutive patients (17 female, 13 male) who had undergone both CTPA and SPECT V/Q scintigraphy during their admission for investigation of potential pulmonary embolism were identified retrospectively. Image datasets from these two modalities were co-registered and fused using commercial software. Accuracy of the fusion process was determined subjectively by correlation between modalities of the anatomical boundaries and co-existent pleuro-parenchymal abnormalities. In all 30 cases, SPECT V/Q images were accurately fused with CTPA images. An automated registration algorithm was sufficient alone in 23 cases (77%). Additional linear z-axis scaling was applied in seven cases. There was accurate topographical co-localisation of vascular, parenchymal and pleural disease on the fused images. Nine patients who had positive CTPA performed as an initial investigation had co-localised perfusion defects on the subsequent fused CTPA/SPECT images. Three of the 11 V/Q scans initially reported as intermediate could be reinterpreted as low probability owing to co-localisation of defects with parenchymal or pleural pathology. Accurate fusion of SPECT V/Q scintigraphy to CTPA images is possible. This technique may be clinically useful in patients who have non-diagnostic initial investigations or in whom corroborative imaging is sought. (orig.)

  20. Image registration/fusion software for PET and CT/MRI by using simultaneous emission and transmission scans

    International Nuclear Information System (INIS)

    Kitamura, Keishi; Amano, Masaharu; Sato, Tomohiko; Okumura, Takeshi; Konishi, Norihiro; Komatsu, Masahiko

    2003-01-01

    When PET (positron emission tomography) is used for oncology studies, it is important to register and over-lay PET images with the images of other anatomical modalities, such as those obtained by CT (computed tomography) or MRI (magnetic resonance imaging), in order for the lesions to be anatomically located with high accuracy. The Shimadzu SET-2000W Series PET scanners provide simultaneous acquisition of emission and transmission data, which is capable of complete spatial alignment of both functional and attenuation images. This report describes our newly developed image registration/fusion software, which reformats PET emission images to the CT/MRI grid by using the transform matrix obtained by matching PET transmission images with CT/MRI images. Transmission images are registered and fused either automatically or manually, through 3-dimensional rotation and translation, with the transaxial, sagittal, and coronal fused images being monitored on the screen. This new method permits sufficiently accurate registration and efficient data processing with promoting effective use of CT/MRI images of the DICOM format, without using markers in data acquisition or any special equipment, such as a combined PET/CT scanner. (author)

  1. Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

    Directory of Open Access Journals (Sweden)

    Brian Johnson

    2015-01-01

    Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

  2. Magnetic Resonance and Ultrasound Image Fusion Supported Transperineal Prostate Biopsy Using the Ginsburg Protocol: Technique, Learning Points, and Biopsy Results.

    Science.gov (United States)

    Hansen, Nienke; Patruno, Giulio; Wadhwa, Karan; Gaziev, Gabriele; Miano, Roberto; Barrett, Tristan; Gnanapragasam, Vincent; Doble, Andrew; Warren, Anne; Bratt, Ola; Kastner, Christof

    2016-08-01

    Prostate biopsy supported by transperineal image fusion has recently been developed as a new method to the improve accuracy of prostate cancer detection. To describe the Ginsburg protocol for transperineal prostate biopsy supported by multiparametric magnetic resonance imaging (mpMRI) and transrectal ultrasound (TRUS) image fusion, provide learning points for its application, and report biopsy results. The article is supplemented by a Surgery in Motion video. This single-centre retrospective outcome study included 534 patients from March 2012 to October 2015. A total of 107 had no previous prostate biopsy, 295 had benign TRUS-guided biopsies, and 159 were on active surveillance for low-risk cancer. A Likert scale reported mpMRI for suspicion of cancer from 1 (no suspicion) to 5 (cancer highly likely). Transperineal biopsies were obtained under general anaesthesia using BiopSee fusion software (Medcom, Darmstadt, Germany). All patients had systematic biopsies, two cores from each of 12 anatomic sectors. Likert 3-5 lesions were targeted with a further two cores per lesion. Any cancer and Gleason score 7-10 cancer on biopsy were noted. Descriptive statistics and positive predictive values (PPVs) and negative predictive values (NPVs) were calculated. The detection rate of Gleason score 7-10 cancer was similar across clinical groups. Likert scale 3-5 MRI lesions were reported in 378 (71%) of the patients. Cancer was detected in 249 (66%) and Gleason score 7-10 cancer was noted in 157 (42%) of these patients. PPV for detecting 7-10 cancer was 0.15 for Likert score 3, 0.43 for score 4, and 0.63 for score 5. NPV of Likert 1-2 findings was 0.87 for Gleason score 7-10 and 0.97 for Gleason score ≥4+3=7 cancer. Limitations include lack of data on complications. Transperineal prostate biopsy supported by MRI/TRUS image fusion using the Ginsburg protocol yielded high detection rates of Gleason score 7-10 cancer. Because the NPV for excluding Gleason score 7-10 cancer was very

  3. Comparison and evaluation of fusion methods used for GF-2 satellite image in coastal mangrove area

    Science.gov (United States)

    Ling, Chengxing; Ju, Hongbo; Liu, Hua; Zhang, Huaiqing; Sun, Hua

    2018-04-01

    GF-2 satellite is the highest spatial resolution Remote Sensing Satellite of the development history of China's satellite. In this study, three traditional fusion methods including Brovey, Gram-Schmidt and Color Normalized (CN were used to compare with the other new fusion method NNDiffuse, which used the qualitative assessment and quantitative fusion quality index, including information entropy, variance, mean gradient, deviation index, spectral correlation coefficient. Analysis results show that NNDiffuse method presented the optimum in qualitative and quantitative analysis. It had more effective for the follow up of remote sensing information extraction and forest, wetland resources monitoring applications.

  4. Utility of 18F sodium fluoride PET/CT imaging in the evaluation of postoperative pain following surgical spine fusion.

    Science.gov (United States)

    Pouldar, D; Bakshian, S; Matthews, R; Rao, V; Manzano, M; Dardashti, S

    2017-08-01

    A retrospective case review of patients who underwent 18F sodium fluoride PET/CT imaging of the spine with postoperative pain following vertebral fusion. To determine the benefit of 18F sodium fluoride PET/CT imaging in the diagnosis of persistent pain in the postoperative spine. The diagnosis of pain generators in the postoperative spine has proven to be a diagnostic challenge. The conventional radiologic evaluation of persistent pain after spine surgery with the use of plain radiographs, MRI, and CT can often fall short of diagnosis in the complex patient. 18F sodium fluoride PET/CT imaging is an alternative tool to accurately identify a patient's source of pain in the difficult patient. This retrospective study looked at 25 adult patients who had undergone 18F sodium fluoride PET/CT imaging. All patients had persistent or recurrent back pain over the course of a 15-month period after having undergone spinal fusion surgery. All patients had inconclusive dedicated MRI. The clinical accuracy of PET/CT in identifying the pain generator and contribution to altering the decision making process was compared to the use of CT scan alone. Of the 25 patients studied, 17 patients had increased uptake on the 18F sodium fluoride PET/CT fusion images. There was a high-level correlation of radiotracer uptake to the patients' pain generator. Overall 88% of the studies were considered beneficial with either PET/CT altering the clinical diagnosis and treatment plan of the patient or confirming unnecessary surgery. 18F sodium fluoride PET/CT proves to be a useful tool in the diagnosis of complex spine pathology of the postoperative patients. In varied cases, a high correlation of metabolic activity to the source of the patient's pain was observed.

  5. Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

    Science.gov (United States)

    Ertosun, Mehmet Günhan; Rubin, Daniel L

    2015-01-01

    Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository.

  6. Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain

    Science.gov (United States)

    Jin, Xin; Jiang, Qian; Yao, Shaowen; Zhou, Dongming; Nie, Rencan; Lee, Shin-Jye; He, Kangjian

    2018-01-01

    In order to promote the performance of infrared and visual image fusion and provide better visual effects, this paper proposes a hybrid fusion method for infrared and visual image by the combination of discrete stationary wavelet transform (DSWT), discrete cosine transform (DCT) and local spatial frequency (LSF). The proposed method has three key processing steps. Firstly, DSWT is employed to decompose the important features of the source image into a series of sub-images with different levels and spatial frequencies. Secondly, DCT is used to separate the significant details of the sub-images according to the energy of different frequencies. Thirdly, LSF is applied to enhance the regional features of DCT coefficients, and it can be helpful and useful for image feature extraction. Some frequently-used image fusion methods and evaluation metrics are employed to evaluate the validity of the proposed method. The experiments indicate that the proposed method can achieve good fusion effect, and it is more efficient than other conventional image fusion methods.

  7. Thermodynamic free-energy minimization for unsupervised fusion of dual-color infrared breast images

    Science.gov (United States)

    Szu, Harold; Miao, Lidan; Qi, Hairong

    2006-04-01

    function [A] may vary from the point tumor to its neighborhood, we could not rely on neighborhood statistics as did in a popular unsupervised independent component analysis (ICA) mathematical statistical method, we instead impose the physics equilibrium condition of the minimum of Helmholtz free-energy, H = E - T °S. In case of the point breast cancer, we can assume the constant ground state energy E ° to be normalized by those benign neighborhood tissue, and then the excited state can be computed by means of Taylor series expansion in terms of the pixel I/O data. We can augment the X-ray mammogram technique with passive IR imaging to reduce the unwanted X-rays during the chemotherapy recovery. When the sequence is animated into a movie, and the recovery dynamics is played backward in time, the movie simulates the cameras' potential for early detection without suffering the PD=0.1 search uncertainty. In summary, we applied two satellite-grade dual-color IR imaging cameras and advanced military (automatic target recognition) ATR spectrum fusion algorithm at the middle wavelength IR (3 - 5μm) and long wavelength IR (8 - 12μm), which are capable to screen malignant tumors proved by the time-reverse fashion of the animated movie experiments. On the contrary, the traditional thermal breast scanning/imaging, known as thermograms over decades, was IR spectrum-blind, and limited to a single night-vision camera and the necessary waiting for the cool down period for taking a second look for change detection suffers too many environmental and personnel variabilities.

  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. An image acquisition and registration strategy for the fusion of hyperpolarized helium-3 MRI and x-ray CT images of the lung

    Science.gov (United States)

    Ireland, Rob H.; Woodhouse, Neil; Hoggard, Nigel; Swinscoe, James A.; Foran, Bernadette H.; Hatton, Matthew Q.; Wild, Jim M.

    2008-11-01

    The purpose of this ethics committee approved prospective study was to evaluate an image acquisition and registration protocol for hyperpolarized helium-3 magnetic resonance imaging (3He-MRI) and x-ray computed tomography. Nine patients with non-small cell lung cancer (NSCLC) gave written informed consent to undergo a free-breathing CT, an inspiration breath-hold CT and a 3D ventilation 3He-MRI in CT position using an elliptical birdcage radiofrequency (RF) body coil. 3He-MRI to CT image fusion was performed using a rigid registration algorithm which was assessed by two observers using anatomical landmarks and a percentage volume overlap coefficient. Registration of 3He-MRI to breath-hold CT was more accurate than to free-breathing CT; overlap 82.9 ± 4.2% versus 59.8 ± 9.0% (p < 0.001) and mean landmark error 0.75 ± 0.24 cm versus 1.25 ± 0.60 cm (p = 0.002). Image registration is significantly improved by using an imaging protocol that enables both 3He-MRI and CT to be acquired with similar breath holds and body position through the use of a birdcage 3He-MRI body RF coil and an inspiration breath-hold CT. Fusion of 3He-MRI to CT may be useful for the assessment of patients with lung diseases.

  10. SU-F-T-42: MRI and TRUS Image Fusion as a Mode of Generating More Accurate Prostate Contours

    Energy Technology Data Exchange (ETDEWEB)

    Petronek, M; Purysko, A; Balik, S; Ciezki, J; Klein, E; Wilkinson, D [Cleveland Clinic Foundation, Cleveland, OH (United States)

    2016-06-15

    Purpose: Transrectal Ultrasound (TRUS) imaging is utilized intra-operatively for LDR permanent prostate seed implant treatment planning. Prostate contouring with TRUS can be challenging at the apex and base. This study attempts to improve accuracy of prostate contouring with MRI-TRUS fusion to prevent over- or under-estimation of the prostate volume. Methods: 14 patients with previous MRI guided prostate biopsy and undergone an LDR permanent prostate seed implant have been selected. The prostate was contoured on the MRI images (1 mm slice thickness) by a radiologist. The prostate was also contoured on TRUS images (5 mm slice thickness) during LDR procedure by a urologist. MRI and TRUS images were rigidly fused manually and the prostate contours from MRI and TRUS were compared using Dice similarity coefficient, percentage volume difference and length, height and width differences. Results: The prostate volume was overestimated by 8 ± 18% (range: 34% to −25%) in TRUS images compared to MRI. The mean Dice was 0.77 ± 0.09 (range: 0.53 to 0.88). The mean difference (TRUS-MRI) in the prostate width was 0 ± 4 mm (range: −11 to 5 mm), height was −3 ± 6 mm (range: −13 to 6 mm) and length was 6 ± 6 (range: −10 to 16 mm). Prostate was overestimated with TRUS imaging at the base for 6 cases (mean: 8 ± 4 mm and range: 5 to 14 mm), at the apex for 6 cases (mean: 11 ± 3 mm and range: 5 to 15 mm) and 1 case was underestimated at both base and apex by 4 mm. Conclusion: Use of intra-operative TRUS and MRI image fusion can help to improve the accuracy of prostate contouring by accurately accounting for prostate over- or under-estimations, especially at the base and apex. The mean amount of discrepancy is within a range that is significant for LDR sources.

  11. SU-F-T-42: MRI and TRUS Image Fusion as a Mode of Generating More Accurate Prostate Contours

    International Nuclear Information System (INIS)

    Petronek, M; Purysko, A; Balik, S; Ciezki, J; Klein, E; Wilkinson, D

    2016-01-01

    Purpose: Transrectal Ultrasound (TRUS) imaging is utilized intra-operatively for LDR permanent prostate seed implant treatment planning. Prostate contouring with TRUS can be challenging at the apex and base. This study attempts to improve accuracy of prostate contouring with MRI-TRUS fusion to prevent over- or under-estimation of the prostate volume. Methods: 14 patients with previous MRI guided prostate biopsy and undergone an LDR permanent prostate seed implant have been selected. The prostate was contoured on the MRI images (1 mm slice thickness) by a radiologist. The prostate was also contoured on TRUS images (5 mm slice thickness) during LDR procedure by a urologist. MRI and TRUS images were rigidly fused manually and the prostate contours from MRI and TRUS were compared using Dice similarity coefficient, percentage volume difference and length, height and width differences. Results: The prostate volume was overestimated by 8 ± 18% (range: 34% to −25%) in TRUS images compared to MRI. The mean Dice was 0.77 ± 0.09 (range: 0.53 to 0.88). The mean difference (TRUS-MRI) in the prostate width was 0 ± 4 mm (range: −11 to 5 mm), height was −3 ± 6 mm (range: −13 to 6 mm) and length was 6 ± 6 (range: −10 to 16 mm). Prostate was overestimated with TRUS imaging at the base for 6 cases (mean: 8 ± 4 mm and range: 5 to 14 mm), at the apex for 6 cases (mean: 11 ± 3 mm and range: 5 to 15 mm) and 1 case was underestimated at both base and apex by 4 mm. Conclusion: Use of intra-operative TRUS and MRI image fusion can help to improve the accuracy of prostate contouring by accurately accounting for prostate over- or under-estimations, especially at the base and apex. The mean amount of discrepancy is within a range that is significant for LDR sources.

  12. Image Fusion Applied to Satellite Imagery for the Improved Mapping and Monitoring of Coral Reefs: a Proposal

    Science.gov (United States)

    Gholoum, M.; Bruce, D.; Hazeam, S. Al

    2012-07-01

    A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine the quality of the

  13. IMAGE FUSION APPLIED TO SATELLITE IMAGERY FOR THE IMPROVED MAPPING AND MONITORING OF CORAL REEFS: A PROPOSAL

    Directory of Open Access Journals (Sweden)

    M. Gholoum

    2012-07-01

    Full Text Available A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine

  14. The impact of image fusion in resolving discrepant findings between FDG-PET and MRI/CT in patients with gynaecological cancers

    International Nuclear Information System (INIS)

    Tsai, Cheng-Chien; Kao, Pan-Fu; Yen, Tzu-Chen; Tsai, Chien-Sheng; Hong, Ji-Hong; Ng, Koon-Kwan; Lai, Chyong-Huey; Chang, Ting-Chang; Hsueh, Swei

    2003-01-01

    This study was performed to prospectively investigate the impact of image fusion in resolving discrepant findings between fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI) or X-ray computed tomography (CT) in patients with gynaecological cancers. Discrepant findings were defined as lesions where the difference between the FDG-PET and MRI/CT images was assigned a value of at least 2 on a 5-point probability scale. The FDG-PET and MRI/CT images were taken within 1 month of each other. Image fusion between FDG-PET and CT was performed by automatic registration between the two images. During an 18-month period, 34 malignant lesions and seven benign lesions from 32 patients who had undergone either surgical excision or a CT-guided histopathological investigation were included for analysis. Among these cases, image fusion was most frequently required to determine the nature and/or the extent of abdominal and pelvic lesions (28/41, 68%), especially as regards peritoneal seeding (8/41, 20%). Image fusion was most useful in providing better localisation for biopsy (16/41, 39%) and in discriminating between lesions with pathological versus physiological FDG uptake (12/41, 29%). Image fusion changed the original diagnosis based on MRI/CT alone in 9/41 lesions (22%), and the original diagnosis based on FDG-PET alone in 5/41 lesions (12%). It led to alteration of treatment planning (surgery or radiotherapy) in seven of the 32 patients (22%). In patients with gynaecological cancers, the technique of image fusion is helpful in discriminating the nature of FDG-avid lesions, in effectively localising lesions for CT-guided biopsy and in providing better surgical or radiotherapy planning. (orig.)

  15. Short fusion

    CERN Multimedia

    2002-01-01

    French and UK researchers are perfecting a particle accelerator technique that could aid the quest for fusion energy or make X-rays that are safer and produce higher-resolution images. Led by Dr Victor Malka from the Ecole Nationale Superieure des Techniques Avancees in Paris, the team has developed a better way of accelerating electrons over short distances (1 page).

  16. Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

    Science.gov (United States)

    Jin, Y.; Lee, D.

    2017-12-01

    North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods

  17. Neurosurgical treatment of drug-resistant epilepsy on the basis of a fusion of MRI and SPECT images - case report

    International Nuclear Information System (INIS)

    Jurkiewicz, E.; Bekiesinska-Figatowska, M.; Misko, J.; Kaminska, A.; Kwiatkowski, S.; Terczynska, I.

    2010-01-01

    Background: Epilepsy concerns at least 0.5% of population and in most of the cases (approx. 70%) can be treated pharmacologically, which helps to prevent seizures. In all other patients, such a treatment does not produce the desired results. Their condition may require neurosurgical management. The aim of this work was to fuse anatomical MRI images and functional SPECT images in patients with drug resistant epilepsy, without structural changes on MRI or with changes so severe that it would be impossible to establish which ones are responsible for seizures. The authors presented a case of a child subjected to a neurosurgical procedure carried out on the basis of the fused MRI and SPECT images. Case Report: A seven-year-old boy with an extensive defect of the right hemisphere (cortical dysplasia with multiple balloon-like cells) operated on three times due to a history of treatment-resistant seizures present since the age of one. A subsequent MRI examination was performed with magnetic field intensity of 1.5 T, within a routine epilepsy protocol applying volumetric thin-slice T1-weighted images. Next, in the interictal period, a SPECT examination was performed with the use of the 99mT c-labelled ethyl cysteinate dimer ( 99mT cECD). For fusion and postprocessing, the following software was used: PMOD (Biomedical Image Quantification PMOD Technologies) with PFUS (Flexible Image Matching and Fusion Tool) and a program for a quantitative analysis of counts in the region of interest, so called VOI Constructor (Volume of Interest Constructor). On the basis of the fusion of images, the boy was subjected to the next operation procedure. The remaining fragments of the right frontal and parietal lobe adjacent to the occipital lobe were removed. Seizure remission was obtained and it was already 31 months long when we were writing this article. Conclusions: Owing to this multi-stage procedure, it was possible to avoid a total anatomical and functional hemispherectomy. This

  18. Fusion of lens-free microscopy and mobile-phone microscopy images for high-color-accuracy and high-resolution pathology imaging

    Science.gov (United States)

    Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

    2017-03-01

    Digital pathology and telepathology require imaging tools with high-throughput, high-resolution and accurate color reproduction. Lens-free on-chip microscopy based on digital in-line holography is a promising technique towards these needs, as it offers a wide field of view (FOV >20 mm2) and high resolution with a compact, low-cost and portable setup. Color imaging has been previously demonstrated by combining reconstructed images at three discrete wavelengths in the red, green and blue parts of the visible spectrum, i.e., the RGB combination method. However, this RGB combination method is subject to color distortions. To improve the color performance of lens-free microscopy for pathology imaging, here we present a wavelet-based color fusion imaging framework, termed "digital color fusion microscopy" (DCFM), which digitally fuses together a grayscale lens-free microscope image taken at a single wavelength and a low-resolution and low-magnification color-calibrated image taken by a lens-based microscope, which can simply be a mobile phone based cost-effective microscope. We show that the imaging results of an H&E stained breast cancer tissue slide with the DCFM technique come very close to a color-calibrated microscope using a 40x objective lens with 0.75 NA. Quantitative comparison showed 2-fold reduction in the mean color distance using the DCFM method compared to the RGB combination method, while also preserving the high-resolution features of the lens-free microscope. Due to the cost-effective and field-portable nature of both lens-free and mobile-phone microscopy techniques, their combination through the DCFM framework could be useful for digital pathology and telepathology applications, in low-resource and point-of-care settings.

  19. Myometrial invasion and overall staging of endometrial carcinoma: assessment using fusion of T2-weighted magnetic resonance imaging and diffusion-weighted magnetic resonance imaging

    Directory of Open Access Journals (Sweden)

    Guo Y

    2017-12-01

    Full Text Available Yu Guo,1,2 Ping Wang,2 Penghui Wang,2 Wei Gao,1 Fenge Li,3 Xueling Yang,1 Hongyan Ni,2 Wen Shen,2 Zhi Guo1 1Department of Interventional Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin, 2Department of Radiology, Tianjin First Center Hospital, The First Central Clinical College of Tianjin Medical University, Tianjin, 3Department of Gynecology, Tianjin First Center Hospital, Tianjin, People’s Republic of China Background: The age of onset of endometrial carcinoma has been decreasing in recent years. In endometrial carcinoma, it is important to accurately assess invasion depth and preoperative staging. Fusion of T2-weighted magnetic resonance imaging (T2WI and diffusion-weighted magnetic resonance imaging (DWI may contribute to the improvement of anatomical localization of lesions.Materials and methods: In our study, a total of 58 endometrial carcinoma cases were included. Based on the revised 2009 International Federation of Gynecology and Obstetrics staging system, a fusion of T2WI and DWI was utilized for the evaluation of invasion depth and determination of the overall stage. Postoperative pathologic assessment was considered as the reference standard. The consistency of T2WI image staging and pathologic staging, and the consistency of fused T2WI and DWI and pathologic staging were all analyzed using Kappa statistics.Results: Compared with the T2WI group, a significantly higher diagnostic accuracy was observed for myometrial invasion with fusion of T2WI and DWI (77.6% for T2WI; 94.8% for T2WI-DWI. For the identification of deep invasion, we calculated values for diagnostic sensitivity (69.2% for T2WI; 92.3% for T2WI-DWI, specificity (80% for T2WI; 95.6% for T2WI-DWI, positive predictive value (50% for T2WI; 85.7% for T2WI-DWI, and negative predictive value (90% for

  20. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  1. Entropy of network ensembles

    Science.gov (United States)

    Bianconi, Ginestra

    2009-03-01

    In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

  2. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  3. Effect of Prostate Magnetic Resonance Imaging/Ultrasound Fusion-guided Biopsy on Radiation Treatment Recommendations

    Energy Technology Data Exchange (ETDEWEB)

    Reed, Aaron; Valle, Luca F.; Shankavaram, Uma; Krauze, Andra; Kaushal, Aradhana; Schott, Erica; Cooley-Zgela, Theresa [Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Wood, Bradford [Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland (United States); Pinto, Peter [Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Choyke, Peter; Turkbey, Baris [Molecular Imaging Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Citrin, Deborah E., E-mail: citrind@mail.nih.gov [Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States)

    2017-04-01

    Purpose: Targeted magnetic resonance imaging (MRI)/ultrasound fusion prostate biopsy (MRI-Bx) has recently been compared with the standard of care extended sextant ultrasound-guided prostate biopsy (SOC-Bx), with the former associated with an increased rate of detection of clinically significant prostate cancer. The present study sought to determine the influence of MRI-Bx on radiation therapy and androgen deprivation therapy (ADT) recommendations. Methods and Materials: All patients who had received radiation treatment and had undergone SOC-Bx and MRI-Bx at our institution were included. Using the clinical T stage, pretreatment prostate-specific antigen, and Gleason score, patients were categorized into National Comprehensive Cancer Network risk groups and radiation treatment or ADT recommendations assigned. Intensification of the recommended treatment after multiparametric MRI, SOC-Bx, and MRI-Bx was evaluated. Results: From January 2008 to January 2016, 73 patients received radiation therapy at our institution after undergoing a simultaneous SOC-Bx and MRI-Bx (n=47 with previous SOC-Bx). Repeat SOC-Bx and MRI-Bx resulted in frequent upgrading compared with previous SOC-Bx (Gleason score 7, 6.7% vs 44.6%; P<.001; Gleason score 8-10, 2.1% vs 38%; P<.001). MRI-Bx increased the proportion of patients classified as very high risk from 24.7% to 41.1% (P=.027). Compared with SOC-Bx alone, including the MRI-Bx findings resulted in a greater percentage of pathologically positive cores (mean 37% vs 44%). Incorporation of multiparametric MRI and MRI-Bx results increased the recommended use and duration of ADT (duration increased in 28 of 73 patients and ADT was added for 8 of 73 patients). Conclusions: In patients referred for radiation treatment, MRI-Bx resulted in an increase in the percentage of positive cores, Gleason score, and risk grouping. The benefit of treatment intensification in accordance with the MRI-Bx findings is unknown.

  4. The Ensembl REST API: Ensembl Data for Any Language.

    Science.gov (United States)

    Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

    2015-01-01

    We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

  5. Simultaneous neutron and x-ray imaging of inertial confinement fusion experiments along a single line of sight at Omega

    Energy Technology Data Exchange (ETDEWEB)

    Danly, C. R.; Day, T. H.; Herrmann, H.; Kim, Y. H.; Martinez, J. I.; Merrill, F. E.; Schmidt, D. W.; Simpson, R. A.; Volegov, P. L.; Wilde, C. H. [Los Alamos National Laboratory, Los Alamos, New Mexico 87544 (United States); Fittinghoff, D. N.; Izumi, N. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)

    2015-04-15

    Neutron and x-ray imaging provide critical information about the geometry and hydrodynamics of inertial confinement fusion implosions. However, existing diagnostics at Omega and the National Ignition Facility (NIF) cannot produce images in both neutrons and x-rays along the same line of sight. This leads to difficulty comparing these images, which capture different parts of the plasma geometry, for the asymmetric implosions seen in present experiments. Further, even when opposing port neutron and x-ray images are available, they use different detectors and cannot provide positive information about the relative positions of the neutron and x-ray sources. A technique has been demonstrated on implosions at Omega that can capture x-ray images along the same line of sight as the neutron images. The technique is described, and data from a set of experiments are presented, along with a discussion of techniques for coregistration of the various images. It is concluded that the technique is viable and could provide valuable information if implemented on NIF in the near future.

  6. The pre-image problem for Laplacian Eigenmaps utilizing L 1 regularization with applications to data fusion

    International Nuclear Information System (INIS)

    Cloninger, Alexander; Czaja, Wojciech; Doster, Timothy

    2017-01-01

    As the popularity of non-linear manifold learning techniques such as kernel PCA and Laplacian Eigenmaps grows, vast improvements have been seen in many areas of data processing, including heterogeneous data fusion and integration. One problem with the non-linear techniques, however, is the lack of an easily calculable pre-image. Existence of such pre-image would allow visualization of the fused data not only in the embedded space, but also in the original data space. The ability to make such comparisons can be crucial for data analysts and other subject matter experts who are the end users of novel mathematical algorithms. In this paper, we propose a pre-image algorithm for Laplacian Eigenmaps. Our method offers major improvements over existing techniques, which allow us to address the problem of noisy inputs and the issue of how to calculate the pre-image of a point outside the convex hull of training samples; both of which have been overlooked in previous studies in this field. We conclude by showing that our pre-image algorithm, combined with feature space rotations, allows us to recover occluded pixels of an imaging modality based off knowledge of that image measured by heterogeneous modalities. We demonstrate this data recovery on heterogeneous hyperspectral (HS) cameras, as well as by recovering LIDAR measurements from HS data. (paper)

  7. The pre-image problem for Laplacian Eigenmaps utilizing L 1 regularization with applications to data fusion

    Science.gov (United States)

    Cloninger, Alexander; Czaja, Wojciech; Doster, Timothy

    2017-07-01

    As the popularity of non-linear manifold learning techniques such as kernel PCA and Laplacian Eigenmaps grows, vast improvements have been seen in many areas of data processing, including heterogeneous data fusion and integration. One problem with the non-linear techniques, however, is the lack of an easily calculable pre-image. Existence of such pre-image would allow visualization of the fused data not only in the embedded space, but also in the original data space. The ability to make such comparisons can be crucial for data analysts and other subject matter experts who are the end users of novel mathematical algorithms. In this paper, we propose a pre-image algorithm for Laplacian Eigenmaps. Our method offers major improvements over existing techniques, which allow us to address the problem of noisy inputs and the issue of how to calculate the pre-image of a point outside the convex hull of training samples; both of which have been overlooked in previous studies in this field. We conclude by showing that our pre-image algorithm, combined with feature space rotations, allows us to recover occluded pixels of an imaging modality based off knowledge of that image measured by heterogeneous modalities. We demonstrate this data recovery on heterogeneous hyperspectral (HS) cameras, as well as by recovering LIDAR measurements from HS data.

  8. Elastic Versus Rigid Image Registration in Magnetic Resonance Imaging-transrectal Ultrasound Fusion Prostate Biopsy: A Systematic Review and Meta-analysis.

    Science.gov (United States)

    Venderink, Wulphert; de Rooij, Maarten; Sedelaar, J P Michiel; Huisman, Henkjan J; Fütterer, Jurgen J

    2016-07-29

    The main difference between the available magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion platforms for prostate biopsy is the method of image registration being either rigid or elastic. As elastic registration compensates for possible deformation caused by the introduction of an ultrasound probe for example, it is expected that it would perform better than rigid registration. The aim of this meta-analysis is to compare rigid with elastic registration by calculating the detection odds ratio (OR) for both subgroups. The detection OR is defined as the ratio of the odds of detecting clinically significant prostate cancer (csPCa) by MRI-TRUS fusion biopsy compared with systematic TRUS biopsy. Secondary objectives were the OR for any PCa and the OR after pooling both registration techniques. The electronic databases PubMed, Embase, and Cochrane were systematically searched for relevant studies according to the Preferred Reporting Items for Systematic Review and Meta-analysis Statement. Studies comparing MRI-TRUS fusion and systematic TRUS-guided biopsies in the same patient were included. The quality assessment of included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies version 2. Eleven papers describing elastic and 10 describing rigid registration were included. Meta-analysis showed an OR of csPCa for elastic and rigid registration of 1.45 (95% confidence interval [CI]: 1.21-1.73, pimaging-transrectal ultrasound fusion systems which vary in their method of compensating for prostate deformation. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  9. A novel technique combining laparoscopic and endovascular approaches using image fusion guidance for anterior embolization of type II endoleak

    Directory of Open Access Journals (Sweden)

    M. Mujeeb Zubair, MD

    2017-03-01

    Full Text Available Type II endoleak (T2E leading to aneurysm sac enlargement is one of the challenging complications associated with endovascular aneurysm repair. Recent guidelines recommend embolization of T2E associated with aneurysmal sac enlargement. Various percutaneous and endovascular techniques have been reported for embolization of T2E. We report a novel technique for T2E embolization combining laparoscopic and endovascular approaches using preoperative image fusion. We believe our technique provides a more direct access to the lumbar feeding vessels that is typically challenging with transarterial or translumbar embolization techniques.

  10. Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging and Fusion Guided Targeted Biopsy Evaluated by Transperineal Template Saturation Prostate Biopsy for the Detection and Characterization of Prostate Cancer.

    Science.gov (United States)

    Mortezavi, Ashkan; Märzendorfer, Olivia; Donati, Olivio F; Rizzi, Gianluca; Rupp, Niels J; Wettstein, Marian S; Gross, Oliver; Sulser, Tullio; Hermanns, Thomas; Eberli, Daniel

    2018-02-21

    We evaluated the diagnostic accuracy of multiparametric magnetic resonance imaging and multiparametric magnetic resonance imaging/transrectal ultrasound fusion guided targeted biopsy against that of transperineal template saturation prostate biopsy to detect prostate cancer. We retrospectively analyzed the records of 415 men who consecutively presented for prostate biopsy between November 2014 and September 2016 at our tertiary care center. Multiparametric magnetic resonance imaging was performed using a 3 Tesla device without an endorectal coil, followed by transperineal template saturation prostate biopsy with the BiopSee® fusion system. Additional fusion guided targeted biopsy was done in men with a suspicious lesion on multiparametric magnetic resonance imaging, defined as Likert score 3 to 5. Any Gleason pattern 4 was defined as clinically significant prostate cancer. The detection rates of multiparametric magnetic resonance imaging and fusion guided targeted biopsy were compared with the detection rate of transperineal template saturation prostate biopsy using the McNemar test. We obtained a median of 40 (range 30 to 55) and 3 (range 2 to 4) transperineal template saturation prostate biopsy and fusion guided targeted biopsy cores, respectively. Of the 124 patients (29.9%) without a suspicious lesion on multiparametric magnetic resonance imaging 32 (25.8%) were found to have clinically significant prostate cancer on transperineal template saturation prostate biopsy. Of the 291 patients (70.1%) with a Likert score of 3 to 5 clinically significant prostate cancer was detected in 129 (44.3%) by multiparametric magnetic resonance imaging fusion guided targeted biopsy, in 176 (60.5%) by transperineal template saturation prostate biopsy and in 187 (64.3%) by the combined approach. Overall 58 cases (19.9%) of clinically significant prostate cancer would have been missed if fusion guided targeted biopsy had been performed exclusively. The sensitivity of

  11. Musical ensembles in Ancient Mesapotamia

    NARCIS (Netherlands)

    Krispijn, T.J.H.; Dumbrill, R.; Finkel, I.

    2010-01-01

    Identification of musical instruments from ancient Mesopotamia by comparing musical ensembles attested in Sumerian and Akkadian texts with depicted ensembles. Lexicographical contributions to the Sumerian and Akkadian lexicon.

  12. Net-based data transfer and automatic image fusion of metabolic (PET) and morphologic (CT/MRI) images for radiosurgical planning of brain tumors

    International Nuclear Information System (INIS)

    Baum, R.P.; Przetak, C.; Schmuecking, M.; Klener, G.; Surber, G.; Hamm, K.

    2002-01-01

    Aim: The main purpose of radiosurgery in comparison to conventional radiotherapy of brain tumors is to reach a higher radiation dose in the tumor and sparing normal brain tissue as much as possible. To reach this aim it is crucial to define the target volume extremely accurately. For this purpose, MRI and CT examinations are used for radiotherapy planning. In certain cases, however, metabolic information obtained by positron emission tomography (PET) may be useful to achieve a higher therapeutic accuracy by sparing important brain structures. This can be the case, i.e. in low grade astrocytomas for exact delineation of vital tumor as well as in differentiating scaring tissue from tumor recurrence and edema after operation. For this purpose, radiolabeled aminoacid analogues (e.g. C-11 methionine) and recently O-2-[ 18 F] Fluorethyl-L-Tyrosin (F-18 FET) have been introduced as PET tracers to detect the area of highest tumor metabolism which allows to obtain additional information as compared to FDG-PET that reflects the local glucose metabolism. In these cases, anatomical and metabolic data have to be combined with the technique of digital image fusion to exactly determine the target volume, the isodoses and the area where the highest dose has to be applied. Materials: We have set up a data transfer from the PET Center of the Zentralklinik Bad Berka with the Department of Stereotactic Radiation at the Helios Klinik Erfurt (distance approx. 25 km) to enable this kind of image fusion. PET data (ECAT EXACT 47, Siemens/CTI) are transferred to a workstation (NOVALIS) in the Dept. of Stereotactic Radiation to be co-registered with the CT or MRI data of the patient. All PET images are in DICOM format (obtained by using a HERMES computer, Nuclear Diagnostics, Sweden) and can easily be introduced into the NOVALIS workstation. The software uses the optimation of mutual information to achieve a good fusion quality. Sometimes manual corrections have to be performed to get an

  13. Imaging Characteristics in ALK Fusion-Positive Lung Adenocarcinomas by Using HRCT

    Science.gov (United States)

    Okumura, Sakae; Kuroda, Hiroaki; Uehara, Hirofumi; Mun, Mingyon; Takeuchi, Kengo; Nakagawa, Ken

    2014-01-01

    Objectives: We aimed to identify high-resolution computed tomography (HRCT) features useful to distinguish the anaplastic lymphoma kinase gene (ALK) fusion-positive and negative lung adenocarcinomas. Methods: We included 236 surgically resected adenocarcinoma lesions, which included 27 consecutive ALK fusion-positive (AP) lesions, 115 epidermal growth factor receptor mutation-positive lesions, and 94 double-negative lesions. HRCT parameters including size, air bronchograms, pleural indentation, spiculation, and tumor disappearance rate (TDR) were compared. In addition, prevalence of small lesions (≤20 mm) and solid lesions (TDR ≤20%) were compared. Results: AP lesions were significantly smaller and had lower TDR (%) than ALK fusion-negative (AN) lesions (tumor diameter: 20.7 mm ± 14.1 mm vs. 27.4 mm ± 13.8 mm, respectively, p 20 mm (n = 7, 25.9%) showed a solid pattern. Among all small lesions, AP lesions had lower TDR and more frequent spiculation than AN lesions (p 20 mm lesions may be ALK fusion-negative. PMID:24899136

  14. Value of image fusion using single photon emission computed tomography with integrated low dose computed tomography in comparison with a retrospective voxel-based method in neuroendocrine tumours

    International Nuclear Information System (INIS)

    Amthauer, H.; Denecke, T.; Ruf, J.; Gutberlet, M.; Felix, R.; Lemke, A.J.; Rohlfing, T.; Boehmig, M.; Ploeckinger, U.

    2005-01-01

    The objective was the evaluation of single photon emission computed tomography (SPECT) with integrated low dose computed tomography (CT) in comparison with a retrospective fusion of SPECT and high-resolution CT and a side-by-side analysis for lesion localisation in patients with neuroendocrine tumours. Twenty-seven patients were examined by multidetector CT. Additionally, as part of somatostatin receptor scintigraphy (SRS), an integrated SPECT-CT was performed. SPECT and CT data were fused using software with a registration algorithm based on normalised mutual information. The reliability of the topographic assignment of lesions in SPECT-CT, retrospective fusion and side-by-side analysis was evaluated by two blinded readers. Two patients were not enrolled in the final analysis because of misregistrations in the retrospective fusion. Eighty-seven foci were included in the analysis. For the anatomical assignment of foci, SPECT-CT and retrospective fusion revealed overall accuracies of 91 and 94% (side-by-side analysis 86%). The correct identification of foci as lymph node manifestations (n=25) was more accurate by retrospective fusion (88%) than from SPECT-CT images (76%) or by side-by-side analysis (60%). Both modalities of image fusion appear to be well suited for the localisation of SRS foci and are superior to side-by-side analysis of non-fused images especially concerning lymph node manifestations. (orig.)

  15. Prediction of the microsurgical window for skull-base tumors by advanced three-dimensional multi-fusion volumetric imaging

    International Nuclear Information System (INIS)

    Oishi, Makoto; Fukuda, Masafumi; Saito, Akihiko; Hiraishi, Tetsuya; Fujii, Yukihiko; Ishida, Go

    2011-01-01

    The surgery of skull base tumors (SBTs) is difficult due to the complex and narrow surgical window that is restricted by the cranium and important structures. The utility of three-dimensional multi-fusion volumetric imaging (3-D MFVI) for visualizing the predicted window for SBTs was evaluated. Presurgical simulation using 3-D MFVI was performed in 32 patients with SBTs. Imaging data were collected from computed tomography, magnetic resonance imaging, and digital subtraction angiography. Skull data was processed to imitate actual bone resection and integrated with various structures extracted from appropriate imaging modalities by image-analyzing software. The simulated views were compared with the views obtained during surgery. All craniotomies and bone resections except opening of the acoustic canal in 2 patients were performed as simulated. The simulated window allowed observation of the expected microsurgical anatomies including tumors, vasculatures, and cranial nerves, through the predicted operative window. We could not achieve the planned tumor removal in only 3 patients. 3-D MFVI afforded high quality images of the relevant microsurgical anatomies during the surgery of SBTs. The intraoperative deja-vu effect of the simulation increased the confidence of the surgeon in the planned surgical procedures. (author)

  16. ASSESSMENT OF CROPPING SYSTEM DIVERSITY IN THE FERGANA VALLEY THROUGH IMAGE FUSION OF LANDSAT 8 AND SENTINEL-1

    Directory of Open Access Journals (Sweden)

    D. Dimov

    2016-06-01

    Full Text Available In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object´s textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.

  17. Assessment of Cropping System Diversity in the Fergana Valley Through Image Fusion of Landsat 8 and SENTINEL-1

    Science.gov (United States)

    Dimov, D.; Kuhn, J.; Conrad, C.

    2016-06-01

    In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object's textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.

  18. An image acquisition and registration strategy for the fusion of hyperpolarized helium-3 MRI and x-ray CT images of the lung

    International Nuclear Information System (INIS)

    Ireland, Rob H; Woodhouse, Neil; Hoggard, Nigel; Swinscoe, James A; Foran, Bernadette H; Hatton, Matthew Q; Wild, Jim M

    2008-01-01

    The purpose of this ethics committee approved prospective study was to evaluate an image acquisition and registration protocol for hyperpolarized helium-3 magnetic resonance imaging ( 3 He-MRI) and x-ray computed tomography. Nine patients with non-small cell lung cancer (NSCLC) gave written informed consent to undergo a free-breathing CT, an inspiration breath-hold CT and a 3D ventilation 3 He-MRI in CT position using an elliptical birdcage radiofrequency (RF) body coil. 3 He-MRI to CT image fusion was performed using a rigid registration algorithm which was assessed by two observers using anatomical landmarks and a percentage volume overlap coefficient. Registration of 3 He-MRI to breath-hold CT was more accurate than to free-breathing CT; overlap 82.9 ± 4.2% versus 59.8 ± 9.0% (p 3 He-MRI and CT to be acquired with similar breath holds and body position through the use of a birdcage 3 He-MRI body RF coil and an inspiration breath-hold CT. Fusion of 3 He-MRI to CT may be useful for the assessment of patients with lung diseases.

  19. Development of a novel fluorescent imaging probe for tumor hypoxia by use of a fusion protein with oxygen-dependent degradation domain of HIF-1α

    Science.gov (United States)

    Tanaka, Shotaro; Kizaka-Kondoh, Shinae; Harada, Hiroshi; Hiraoka, Masahiro

    2007-02-01

    More malignant tumors contain more hypoxic regions. In hypoxic tumor cells, expression of a series of hypoxiaresponsive genes related to malignant phenotype such as angiogenesis and metastasis are induced. Hypoxia-inducible factor-1 (HIF-1) is a master transcriptional activator of such genes, and thus imaging of hypoxic tumor cells where HIF-1 is active, is important in cancer therapy. We have been developing PTD-ODD fusion proteins, which contain protein transduction domain (PTD) and the VHL-mediated protein destruction motif in oxygen-dependent degradation (ODD) domain of HIF-1 alpha subunit (HIF-1α). Thus PTD-ODD fusion proteins can be delivered to any tissue in vivo through PTD function and specifically stabilized in hypoxic cells through ODD function. To investigate if PTD-ODD fusion protein can be applied to construct hypoxia-specific imaging probes, we first constructed a fluorescent probe because optical imaging enable us to evaluate a probe easily, quickly and economically in a small animal. We first construct a model fusion porein PTD-ODD-EGFP-Cy5.5 named POEC, which is PTD-ODD protein fused with EGFP for in vitro imaging and stabilization of fusion protein, and conjugated with a near-infrared dye Cy5.5. This probe is designed to be degraded in normoxic cells through the function of ODD domain and followed by quick clearance of free fluorescent dye. On the other hand, this prove is stabilized in hypoxic tumor cells and thus the dye is stayed in the cells. Between normoxic and hypoxic conditions, the difference in the clearance rate of the dye will reveals suited contrast for tumor-hypoxia imaging. The optical imaging probe has not been optimized yet but the results presented here exhibit a potential of PTD-ODD fusion protein as a hypoxia-specific imaging probe.

  20. Single photon emission computed tomography/spiral computed tomography fusion imaging for the diagnosis of bone metastasis in patients with known cancer

    International Nuclear Information System (INIS)

    Zhao, Zhen; Li, Lin; Li, Fanglan; Zhao, Lixia

    2010-01-01

    To evaluate single photon emission computed tomography (SPECT)/spiral computed tomography (CT) fusion imaging for the diagnosis of bone metastasis in patients with known cancer and to compare the diagnostic efficacy of SPECT/CT fusion imaging with that of SPECT alone and with SPECT + CT. One hundred forty-one bone lesions of 125 cancer patients (with nonspecific bone findings on bone scintigraphy) were investigated in the study. SPECT, CT, and SPECT/CT fusion images were acquired simultaneously. All images were interpreted independently by two experienced nuclear medicine physicians. In cases of discrepancy, consensus was obtained by a joint reading. The final diagnosis was based on biopsy proof and radiologic follow-up over at least 1 year. The final diagnosis revealed 63 malignant bone lesions and 78 benign lesions. The diagnostic sensitivity of SPECT, SPECT + CT, and SPECT/CT fusion imaging for malignant lesions was 82.5%, 93.7%, and 98.4%, respectively. Specificity was 66.7%, 80.8%, and 93.6%, respectively. Accuracy was 73.8%, 86.5%, and 95.7%, respectively. The specificity and accuracy of SPECT/CT fusion imaging for the diagnosis malignant bone lesions were significantly higher than those of SPECT alone and of SPECT + CT (P 2 = 9.855, P = 0.002). The numbers of equivocal lesions were 37, 18, and 5 for SPECT, SPECT + CT, and SPECT/CT fusion imaging, respectively, and 29.7% (11/37), 27.8% (5/18), and 20.0% (1/5) of lesions were confirmed to be malignant by radiologic follow-up over at least 1 year. SPECT/spiral CT is particularly valuable for the diagnosis of bone metastasis in patients with known cancer by providing precise anatomic localization and detailed morphologic characteristics. (orig.)

  1. Clinical assessment of CT-MRI image fusion software in localization of the prostate for 3D conformal radiation therapy

    International Nuclear Information System (INIS)

    Kagawa, Kazufumi; Lee, W. Robert; Schultheiss, Timothy E.; Hunt, Margie A.; Shaer, Andrew H.; Hanks, Gerald E.

    1996-01-01

    Purpose: To assess the utility of image fusion software and compare MRI prostate localization with CT localization in patients undergoing 3D conformal radiation therapy of prostate cancer. Materials and Methods: After a phantom study was performed to ensure the accuracy of image fusion procedure, 22 prostate cancer patients had CT and MRI studies before the start of radiotherapy. Immobilization casts used during radiation treatment were also used for both imaging studies. After the clinical target volume (CTV) (prostate or prostate + seminal vesicles) was defined on CT, slices from MRI study were reconstructed to match precisely the corresponding CT slices by identifying three common bony landmarks on each study. The CTV was separately defined on the matched MRI slices. Data related to the size and location of the prostate were compared between CT and MRI. The spatial relationship between the tip of urethrogram cone on CT and prostate apex seen on MRI was also scrutinized. Results: The phantom study showed the registration discrepancies between CT and MRI smaller than 1.0 mm in any pair of comparison. The patient study showed mean image registration error of 0.9 (± 0.6) mm. The average prostate volume was 63.0 (± 25.8) cm 3 and 50.9 (± 22.9) cm 3 determined by CT and MRI respectively (Fig. 1). The difference in prostate location with the two studies most commonly differed at the base and at the apex of the prostate (Fig. 2). On transverse MRI, the prostate apex was situated 7.1 (± 4.5) mm dorsal and 15.1 (± 4.0) mm cephalad to the tip of urethrogram cone (Fig. 3). Conclusions: CT-MRI image fusion study made it possible to compare the two modalities directly. MRI localization of the prostate is more accurate than CT, and indicates the distance from cone to apex is 15 mm. In view of excellent treatment results obtained with current CT localization of the prostate, still it may not be wise to reduce target volume to that demonstrated on MRI

  2. Multi-Sensor Fusion of Infrared and Electro-Optic Signals for High Resolution Night Images

    Directory of Open Access Journals (Sweden)

    Victor Lawrence

    2012-07-01

    Full Text Available Electro-optic (EO image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF of a uniform detector array and the incoherent optical transfer function (OTF of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1 inverse filter-based IR image transformation; (2 EO image edge detection; (3 registration; and (4 blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.

  3. A stochastic approach for automatic registration and fusion of left atrial electroanatomic maps with 3D CT anatomical images

    International Nuclear Information System (INIS)

    Cristoforetti, Alessandro; Mase, Michela; Faes, Luca; Centonze, Maurizio; Greco, Maurizio Del; Antolini, Renzo; Nollo, Giandomenico; Ravelli, Flavia

    2007-01-01

    The integration of electroanatomic maps with highly resolved computed tomography cardiac images plays an important role in the successful planning of the ablation procedure of arrhythmias. In this paper, we present and validate a fully-automated strategy for the registration and fusion of sparse, atrial endocardial electroanatomic maps (CARTO maps) with detailed left atrial (LA) anatomical reconstructions segmented from a pre-procedural MDCT scan. Registration is accomplished by a parameterized geometric transformation of the CARTO points and by a stochastic search of the best parameter set which minimizes the misalignment between transformed CARTO points and the LA surface. The subsequent fusion of electrophysiological information on the registered CT atrium is obtained through radial basis function interpolation. The algorithm is validated by simulation and by real data from 14 patients referred to CT imaging prior to the ablation procedure. Results are presented, which show the validity of the algorithmic scheme as well as the accuracy and reproducibility of the integration process. The obtained results encourage the application of the integration method in post-intervention ablation assessment and basic AF research and suggest the development for real-time applications in catheter guiding during ablation intervention

  4. Accuracy evaluation of fusion of CT, MR, and SPECT images using commercially available software packages (SRS PLATO and IFS)

    International Nuclear Information System (INIS)

    Mongioj, Valeria; Brusa, Anna; Loi, Gianfranco; Pignoli, Emanuele; Gramaglia, Alberto; Scorsetti, Marta; Bombardieri, Emilio; Marchesini, Renato

    1999-01-01

    Purpose: A problem for clinicians is to mentally integrate information from multiple diagnostic sources, such as computed tomography (CT), magnetic resonance (MR), and single photon emission computed tomography (SPECT), whose images give anatomic and metabolic information. Methods and Materials: To combine this different imaging procedure information, and to overlay correspondent slices, we used commercially available software packages (SRS PLATO and IFS). The algorithms utilize a fiducial-based coordinate system (or frame) with 3 N-shaped markers, which allows coordinate transformation of a clinical examination data set (9 spots for each transaxial section) to a stereotactic coordinate system. The N-shaped markers were filled with fluids visible in each modality (gadolinium for MR, calcium chloride for CT, and 99m Tc for SPECT). The frame is relocatable, in the different acquisition modalities, by means of a head holder to which a face mask is fixed so as to immobilize the patient. Position errors due to the algorithms were obtained by evaluating the stereotactic coordinates of five sources detectable in each modality. Results: SPECT and MR position errors due to the algorithms were evaluated with respect to CT: Δx was ≤ 0.9 mm for MR and ≤ 1.4 mm for SPECT, Δy was ≤ 1 mm and ≤ 3 mm for MR and SPECT, respectively. Maximal differences in distance between estimated and actual fiducial centers (geometric mismatch) were in the order of the pixel size (0.8 mm for CT, 1.4 mm for MR, and 1.8 mm for SPECT). In an attempt to distinguish necrosis from residual disease, the image fusion protocol was studied in 35 primary or metastatic brain tumor patients. Conclusions: The image fusion technique has a good degree of accuracy as well as the potential to improve the specificity of tissue identification and the precision of the subsequent treatment planning

  5. Ensemble Data Mining Methods

    Science.gov (United States)

    Oza, Nikunj C.

    2004-01-01

    Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

  6. Ensemble Data Mining Methods

    Data.gov (United States)

    National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...

  7. Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

    Science.gov (United States)

    Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

    2010-01-01

    In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

  8. Ensembl variation resources

    Directory of Open Access Journals (Sweden)

    Marin-Garcia Pablo

    2010-05-01

    Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.

  9. Semi-automated measurements of heart-to-mediastinum ratio on 123I-MIBG myocardial scintigrams by using image fusion method with chest X-ray images

    Science.gov (United States)

    Kawai, Ryosuke; Hara, Takeshi; Katafuchi, Tetsuro; Ishihara, Tadahiko; Zhou, Xiangrong; Muramatsu, Chisako; Abe, Yoshiteru; Fujita, Hiroshi

    2015-03-01

    MIBG (iodine-123-meta-iodobenzylguanidine) is a radioactive medicine that is used to help diagnose not only myocardial diseases but also Parkinson's diseases (PD) and dementia with Lewy Bodies (DLB). The difficulty of the segmentation around the myocardium often reduces the consistency of measurement results. One of the most common measurement methods is the ratio of the uptake values of the heart to mediastinum (H/M). This ratio will be a stable independent of the operators when the uptake value in the myocardium region is clearly higher than that in background, however, it will be unreliable indices when the myocardium region is unclear because of the low uptake values. This study aims to develop a new measurement method by using the image fusion of three modalities of MIBG scintigrams, 201-Tl scintigrams, and chest radiograms, to increase the reliability of the H/M measurement results. Our automated method consists of the following steps: (1) construct left ventricular (LV) map from 201-Tl myocardium image database, (2) determine heart region in chest radiograms, (3) determine mediastinum region in chest radiograms, (4) perform image fusion of chest radiograms and MIBG scintigrams, and 5) perform H/M measurements on MIBG scintigrams by using the locations of heart and mediastinum determined on the chest radiograms. We collected 165 cases with 201-Tl scintigrams and chest radiograms to construct the LV map. Another 65 cases with MIBG scintigrams and chest radiograms were also collected for the measurements. Four radiological technologists (RTs) manually measured the H/M in the MIBG images. We compared the four RTs' results with our computer outputs by using Pearson's correlation, the Bland-Altman method, and the equivalency test method. As a result, the correlations of the H/M between four the RTs and the computer were 0.85 to 0.88. We confirmed systematic errors between the four RTs and the computer as well as among the four RTs. The variation range of the H

  10. The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

    Science.gov (United States)

    Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

    2011-08-01

    Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

  11. Development of new gamma camera localization method for sentinel nodes by image fusion and navigation in lymphoscintigraphy

    International Nuclear Information System (INIS)

    Fidler, V.; Milanez, T.; Prepadnik, M.; Skalic, S.; Skalic, K.; Vidrgar-Kralj, B.; Fidler, S.; Medved, M.

    2004-01-01

    Full text: The objective of this study was the development of the localization technique for skin marking the lesions with low accumulating Tc-99m labeled radiopharmaceuticals. Fusion of high count static planar scan (base image) with real time acquired scan (fluent image) and with added moving point source (Tc-99m or Co-57) in the same patient position was performed for best overlapping the target lesions and point source spot. Special acquisition software in Windows (Oncology MedicView) was developed. Both images were pre-processed by online visual inspection and then fluently fused in the way that only point source spot is overlapped to the base image. Image normalization was done by linear, log or combined log/linear conversions followed by on-line contrasting of fused image by high sensitive color scaling and spatial contrast filtering. The localization was performed in several patient positions with fixed bed and patient. Navigation tools using audio and visual signals were continuously created from the 'lesion-point source spot' distance information. Localization accuracy for SLN(s) using this technique was considerably high. SLN detection improved from 76 % (95 patients, 72 detected SLNs, 23 undetectable SLNs) to 95 % (45 pts, 42 detected SLNs, 3 undetectable SLNs). Localization procedure was shortened for at least 3 times. The new technique substantially lowered the localization time and increased the lesion detection by on-line interactive optimization of fused images. It can be used for all radioisotope localizations in oncology diagnostics using simple analog or semi digital gamma cameras connected to low-cost IAEA acquisition module and specially developed acquisition/processing software. (author)

  12. Fusion of multimodal medical images. Application to dynamic tri dimensional study of vertebral column

    International Nuclear Information System (INIS)

    Brunie, L.

    1992-12-01

    The object of this thesis is to put in correspondence images coming from different ways. The area of application is biomedical imaging, particularly dynamic imaging in three dimensional calculations of spinal cord. The use of computers allows modeling. Then a study of validation by clinical experimentation on spinal cord proves the efficiency of the simulation

  13. Image fusion analysis of 99mTc-HYNIC-Tyr3-octreotide SPECT and diagnostic CT using an immobilisation device with external markers in patients with endocrine tumours

    International Nuclear Information System (INIS)

    Gabriel, Michael; Hausler, Florian; Moncayo, Roy; Decristoforo, Clemens; Virgolini, Irene; Bale, Reto; Kovacs, Peter

    2005-01-01

    The aim of this study was to assess the value of multimodality imaging using a novel repositioning device with external markers for fusion of single-photon emission computed tomography (SPECT) and computed tomography (CT) images. The additional benefit derived from this methodological approach was analysed in comparison with SPECT and diagnostic CT alone in terms of detection rate, reliability and anatomical assignment of abnormal findings with SPECT. Fifty-three patients (30 males, 23 females) with known or suspected endocrine tumours were studied. Clinical indications for somatostatin receptor (SSTR) scintigraphy (SPECT/CT image fusion) included staging of newly diagnosed tumours (n=14) and detection of unknown primary tumour in the presence of clinical and/or biochemical suspicion of neuroendocrine malignancy (n=20). Follow-up studies after therapy were performed in 19 patients. A mean activity of 400 MBq of 99m Tc-EDDA/HYNIC-Tyr 3 -octreotide was given intravenously. SPECT using a dual-detector scintillation camera and diagnostic multi-detector CT were sequentially performed. To ensure reproducible positioning, patients were fixed in an individualised vacuum mattress with modality-specific external markers for co-registration. SPECT and CT data were initially interpreted separately and the fused images were interpreted jointly in consensus by nuclear medicine and diagnostic radiology physicians. SPECT was true-positive (TP) in 18 patients, true-negative (TN) in 16, false-negative (FN) in ten and false-positive (FP) in nine; CT was TP in 18 patients, TN in 21, FP in ten and FN in four. With image fusion (SPECT and CT), the scan result was TP in 27 patients (50.9%), TN in 25 patients (47.2%) and FN in one patient, this FN result being caused by multiple small liver metastases; sensitivity was 95% and specificity, 100%. The difference between SPECT and SPECT/CT was statistically as significant as the difference between CT and SPECT/CT image fusion (P<0

  14. Generating description with multi-feature fusion and saliency maps of image

    Science.gov (United States)

    Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

    2018-04-01

    Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

  15. 'Lazy' quantum ensembles

    International Nuclear Information System (INIS)

    Parfionov, George; Zapatrin, Roman

    2006-01-01

    We compare different strategies aimed to prepare an ensemble with a given density matrix ρ. Preparing the ensemble of eigenstates of ρ with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ρ, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ρ. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error

  16. The semantic similarity ensemble

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2013-12-01

    Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

  17. Magnetic quadrupoles lens for hot spot proton imaging in inertial confinement fusion

    Energy Technology Data Exchange (ETDEWEB)

    Teng, J. [Science and Technology on Plasma Physics Laboratory, Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Gu, Y.Q., E-mail: yqgu@caep.cn [Science and Technology on Plasma Physics Laboratory, Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Center for Applied Physics and Technology, HEDPS, Peking University, Beijing 100871 (China); Chen, J.; Zhu, B.; Zhang, B.; Zhang, T.K.; Tan, F.; Hong, W.; Zhang, B.H. [Science and Technology on Plasma Physics Laboratory, Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Wang, X.Q. [Academy of Nuclear Science and Technology, University of Science and Technology of China, Hefei 230026 (China)

    2016-08-01

    Imaging of DD-produced protons from an implosion hot spot region by miniature permanent magnetic quadrupole (PMQ) lens is proposed. Corresponding object-image relation is deduced and an adjust method for this imaging system is discussed. Ideal point-to-point imaging demands a monoenergetic proton source; nevertheless, we proved that the blur of image induced by proton energy spread is a second order effect therefore controllable. A proton imaging system based on miniature PMQ lens is designed for 2.8 MeV DD-protons and the adjust method in case of proton energy shift is proposed. The spatial resolution of this system is better than 10 μm when proton yield is above 10{sup 9} and the spectra width is within 10%.

  18. Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA

    Directory of Open Access Journals (Sweden)

    Jian-Gang Wang

    2007-08-01

    Full Text Available This paper presents a novel approach for face recognition based on the fusion of the appearance and depth information at the match score level. We apply passive stereoscopy instead of active range scanning as popularly used by others. We show that present-day passive stereoscopy, though less robust and accurate, does make positive contribution to face recognition. By combining the appearance and disparity in a linear fashion, we verified experimentally that the combined results are noticeably better than those for each individual modality. We also propose an original learning method, the bilateral two-dimensional linear discriminant analysis (B2DLDA, to extract facial features of the appearance and disparity images. We compare B2DLDA with some existing 2DLDA methods on both XM2VTS database and our database. The results show that the B2DLDA can achieve better results than others.

  19. Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA

    Directory of Open Access Journals (Sweden)

    Kong Hui

    2007-01-01

    Full Text Available This paper presents a novel approach for face recognition based on the fusion of the appearance and depth information at the match score level. We apply passive stereoscopy instead of active range scanning as popularly used by others. We show that present-day passive stereoscopy, though less robust and accurate, does make positive contribution to face recognition. By combining the appearance and disparity in a linear fashion, we verified experimentally that the combined results are noticeably better than those for each individual modality. We also propose an original learning method, the bilateral two-dimensional linear discriminant analysis (B2DLDA, to extract facial features of the appearance and disparity images. We compare B2DLDA with some existing 2DLDA methods on both XM2VTS database and our database. The results show that the B2DLDA can achieve better results than others.

  20. The impact of early shame memories in Binge Eating Disorder: The mediator effect of current body image shame and cognitive fusion.

    Science.gov (United States)

    Duarte, Cristiana; Pinto-Gouveia, José

    2017-12-01

    This study examined the phenomenology of shame experiences from childhood and adolescence in a sample of women with Binge Eating Disorder. Moreover, a path analysis was investigated testing whether the association between shame-related memories which are traumatic and central to identity, and binge eating symptoms' severity, is mediated by current external shame, body image shame and body image cognitive fusion. Participants in this study were 114 patients, who were assessed through the Eating Disorder Examination and the Shame Experiences Interview, and through self-report measures of external shame, body image shame, body image cognitive fusion and binge eating symptoms. Shame experiences where physical appearance was negatively commented or criticized by others were the most frequently recalled. A path analysis showed a good fit between the hypothesised mediational model and the data. The traumatic and centrality qualities of shame-related memories predicted current external shame, especially body image shame. Current shame feelings were associated with body image cognitive fusion, which, in turn, predicted levels of binge eating symptomatology. Findings support the relevance of addressing early shame-related memories and negative affective and self-evaluative experiences, namely related to body image, in the understanding and management of binge eating. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Multiresolution, Geometric, and Learning Methods in Statistical Image Processing, Object Recognition, and Sensor Fusion

    National Research Council Canada - National Science Library

    Willsky, Alan

    2004-01-01

    .... Our research blends methods from several fields-statistics and probability, signal and image processing, mathematical physics, scientific computing, statistical learning theory, and differential...

  2. FUSION OF MULTI-SCALE DEMS FROM DESCENT AND NAVCM IMAGES OF CHANG’E-3 USING COMPRESSED SENSING METHOD

    Directory of Open Access Journals (Sweden)

    M. Peng

    2017-07-01

    Full Text Available The multi-source DEMs generated using the images acquired in the descent and landing phase and after landing contain supplementary information, and this makes it possible and beneficial to produce a higher-quality DEM through fusing the multi-scale DEMs. The proposed fusion method consists of three steps. First, source DEMs are split into small DEM patches, then the DEM patches are classified into a few groups by local density peaks clustering. Next, the grouped DEM patches are used for sub-dictionary learning by stochastic coordinate coding. The trained sub-dictionaries are combined into a dictionary for sparse representation. Finally, the simultaneous orthogonal matching pursuit (SOMP algorithm is used to achieve sparse representation. We use the real DEMs generated from Chang’e-3 descent images and navigation camera (Navcam stereo images to validate the proposed method. Through the experiments, we have reconstructed a seamless DEM with the highest resolution and the largest spatial coverage among the input data. The experimental results demonstrated the feasibility of the proposed method.

  3. A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

    Science.gov (United States)

    Li, Jing; Xie, Weixin; Pei, Jihong

    2018-03-01

    Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

  4. Fusion of spectra and texture data of hyperspectral imaging for the prediction of the water-holding capacity of fresh chicken breast filets

    Science.gov (United States)

    This study investigated the fusion of spectra and texture data of hyperspectral imaging (HSI, 1000–2500 nm) for predicting the water-holding capacity (WHC) of intact, fresh chicken breast filets. Three physical and chemical indicators drip loss, expressible fluid, and salt-induced water gain were me...

  5. Relation between lung perfusion defects and intravascular clots in acute pulmonary thromboembolism: assessment with breath-hold SPECT-CT pulmonary angiography fusion images.

    Science.gov (United States)

    Suga, Kazuyoshi; Yasuhiko, Kawakami; Iwanaga, Hideyuki; Tokuda, Osamu; Matsunaga, Naofumi

    2008-09-01

    The relation between lung perfusion defects and intravascular clots in acute pulmonary thromboembolism (PTE) was comprehensively assessed on deep-inspiratory breath-hold (DIBrH) perfusion SPECT-computed tomographic pulmonary angiography (CTPA) fusion images. Subjects were 34 acute PTE patients, who had successfully performed DIBrH perfusion SPECT using a dual-headed SPECT and a respiratory tracking system. Automated DIBrH SPECT-CTPA fusion images were used to assess the relation between lung perfusion defects and intravascular clots detected by CTPA. DIBrH SPECT visualized 175 lobar/segmental or subsegmental defects in 34 patients, and CTPA visualized 61 intravascular clots at variable locations in 30 (88%) patients, but no clots in four (12%) patients. In 30 patients with clots, the fusion images confirmed that 69 (41%) perfusion defects (20 segmental, 45 subsegmental and 4 lobar defects) of total 166 defects were located in lung territories without clots, although the remaining 97 (58%) defects were located in lung territories with clots. Perfusion defect was absent in lung territories with clots (one lobar branch and three segmental branches) in four (12%) of these patients. In four patients without clots, nine perfusion defects including four segmental ones were present. Because of unexpected dissociation between intravascular clots and lung perfusion defects, the present fusion images will be a useful adjunct to CTPA in the diagnosis of acute PTE.

  6. Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images

    Directory of Open Access Journals (Sweden)

    Chih-Lung Lin

    2015-12-01

    Full Text Available In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1 automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2 applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3 extracting the line-like features (LLFs from the fused image; (4 obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5 using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods.

  7. Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images.

    Science.gov (United States)

    Lin, Chih-Lung; Wang, Shih-Hung; Cheng, Hsu-Yung; Fan, Kuo-Chin; Hsu, Wei-Lieh; Lai, Chin-Rong

    2015-12-12

    In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods.

  8. Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images

    Science.gov (United States)

    Lin, Chih-Lung; Wang, Shih-Hung; Cheng, Hsu-Yung; Fan, Kuo-Chin; Hsu, Wei-Lieh; Lai, Chin-Rong

    2015-01-01

    In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods. PMID:26703596

  9. Red to far-red multispectral fluorescence image fusion for detection of fecal contamination on apples

    Science.gov (United States)

    This research developed a multispectral algorithm derived from hyperspectral line-scan fluorescence imaging under violet/blue LED excitation for detection of fecal contamination on Golden Delicious apples. Using a hyperspectral line-scan imaging system consisting of an EMCCD camera, spectrograph, an...

  10. TU-AB-202-11: Tumor Segmentation by Fusion of Multi-Tracer PET Images Using Copula Based Statistical Methods

    International Nuclear Information System (INIS)

    Lapuyade-Lahorgue, J; Ruan, S; Li, H; Vera, P

    2016-01-01

    Purpose: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. Methods: Non-standardized Gamma distributions are convenient to model intensity distributions in PET. As a serious correlation exists in multi-tracer PET images, we proposed a new fusion method based on copula which is capable to represent dependency between different tracers. The Hidden Markov Field (HMF) model is used to represent spatial relationship between PET image voxels and statistical dynamics of intensities for each modality. Real PET images of five patients with FDG and FMISO are used to evaluate quantitatively and qualitatively our method. A comparison between individual and multi-tracer segmentations was conducted to show advantages of the proposed fusion method. Results: The segmentation results show that fusion with Gaussian copula can receive high Dice coefficient of 0.84 compared to that of 0.54 and 0.3 of monomodal segmentation results based on individual segmentation of FDG and FMISO PET images. In addition, high correlation coefficients (0.75 to 0.91) for the Gaussian copula for all five testing patients indicates the dependency between tumor regions in the multi-tracer PET images. Conclusion: This study shows that using multi-tracer PET imaging can efficiently improve the segmentation of tumor region where hypoxia and glucidic consumption are present at the same time. Introduction of copulas for modeling the dependency between two tracers can simultaneously take into account information from both tracers and deal with two pathological phenomena. Future work will be to consider other families of copula such as spherical and archimedian copulas, and to eliminate partial volume

  11. Detection and localization of underground networks by fusion of electromagnetic signal and GPR images

    Science.gov (United States)

    Hafsi, Meriem; Bolon, Philippe; Dapoigny, Richard

    2017-03-01

    In this paper, we purpose a new approach to the post-processing of multi-sensor detection based on knowledge representation and data fusion provided by several technologies. The aim is to improve the detection and localization of underground networks. This work is part of the G4M project, leaded by ENGIE LAB CRIGEN, the objective of which is the design of a versatile device for a reliable detection and localization of underground networks. The objective of this work, which is at the core of the G4M project, focuses on the validity of current detection methods, to optimize the process of detection using these methods and to establish a 3D map of subsoil networks.

  12. [Effect of image fusion technology of radioactive particles implantation before and after the planning target and dosimetry].

    Science.gov (United States)

    Jiang, Y L; Yu, J P; Sun, H T; Guo, F X; Ji, Z; Fan, J H; Zhang, L J; Li, X; Wang, J J

    2017-08-01

    Objective: To compare the post-implant target volumes and dosimetric evaluation with pre-plan, the gross tumor volume(GTV) by CT image fusion-based and the manual delineation of target volume in CT guided radioactive seeds implantation. Methods: A total of 10 patients treated under CT-guidance (125)I seed implantation during March 2016 to April 2016 were analyzed in Peking University Third Hospital.All patients underwent pre-operative CT simulation, pre-operative planning, implantation seeds, CT scanning after seed implantation and dosimetric evaluation of GTV.In every patient, post-implant target volumes were delineated by both two methods, and were divided into two groups. Group 1: image fusion pre-implantation simulation and post-operative CT image, then the contours of GTV were automatically performed by brachytherapy treatment planning system; Group 2: the contouring of the GTV on post-operative CT image were performed manually by three senior radiation oncologists independently. The average of three data was sets. Statistical analyses were performed using SPSS software, version 3.2.0. The paired t -test was used to compare the target volumes and D(90) parameters in two modality. Results: In Group 1, average volume of GTV in post-operation group was 12-167(73±56) cm(3). D(90) was 101-153 (142±19)Gy. In Group 2, they were 14-186(80±58)cm(3) and 96-146(122±16) Gy respectively. In both target volumes and D(90), there was no statistical difference between pre-operation and post-operation in Group 1.The D(90) was slightly lower than that of pre-plan group, but there was no statistical difference ( P =0.142); in Group 2, between pre-operation and post-operation group, there was a significant statistical difference in the GTV ( P =0.002). The difference of D(90) was similarly ( P manual delineation of target volume by maximum reduce the interference from artificial factor and metal artifacts. Further work and more cases are required in the future.

  13. Universal Stochastic Multiscale Image Fusion: An Example Application for Shale Rock.

    Science.gov (United States)

    Gerke, Kirill M; Karsanina, Marina V; Mallants, Dirk

    2015-11-02

    Spatial data captured with sensors of different resolution would provide a maximum degree of information if the data were to be merged into a single image representing all scales. We develop a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images of shale rock representing macro, micro and nanoscale spatial information on mineral, organic matter and porosity distribution. Merging multiscale images of shale rock is pivotal to quantify more reliably petrophysical properties needed for production optimization and environmental impacts minimization. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Practical applications are not limited to petroleum engineering or more broadly geosciences, but will also find their way in material sciences, climatology, and remote sensing.

  14. Image Fusion Based on the \\({\\Delta ^{ - 1}} - T{V_0}\\ Energy Function

    Directory of Open Access Journals (Sweden)

    Qiwei Xie

    2014-11-01

    Full Text Available This article proposes a \\({\\Delta^{-1}}-T{V_0}\\ energy function to fuse a multi-spectral image with a panchromatic image. The proposed energy function consists of two components, a \\(TV_0\\ component and a \\(\\Delta^{-1}\\ component. The \\(TV_0\\ term uses the sparse priority to increase the detailed spatial information; while the \\({\\Delta ^{ - 1}}\\ term removes the block effect of the multi-spectral image. Furthermore, as the proposed energy function is non-convex, we also adopt an alternative minimization algorithm and the \\(L_0\\ gradient minimization to solve it. Experimental results demonstrate the improved performance of the proposed method over existing methods.

  15. Splenogonadal Fusion

    Directory of Open Access Journals (Sweden)

    Sung-Lang Chen

    2008-11-01

    Full Text Available Splenogonadal fusion (SGF is a rare congenital non-malignant anomaly characterized by fusion of splenic tissue to the gonad, and can be continuous or discontinuous. Very few cases have been diagnosed preoperatively, and many patients who present with testicular swelling undergo unnecessary orchiectomy under the suspicion of testicular neoplasm. A 16-year-old boy presented with a left scrotal mass and underwent total excision of a 1.6-cm tumor without damaging the testis, epididymis or its accompanying vessels. Pathologic examination revealed SFG (discontinuous type. If clinically suspected before surgery, the diagnosis may be confirmed by Tc-99m sulfur colloid imaging, which shows uptake in both the spleen and accessory splenic tissue within the scrotum. Frozen section should be considered if there remains any doubt regarding the diagnosis during operation.

  16. Clinical use of digital retrospective image fusion of CT, MRI, FDG-PET and SPECT - fields of indications and results; Klinischer Einsatz der digitalen retrospektiven Bildfusion von CT, MRT, FDG-PET und SPECT - Anwendungsgebiete und Ergebnisse

    Energy Technology Data Exchange (ETDEWEB)

    Lemke, A.J.; Niehues, S.M.; Amthauer, H.; Felix, R. [Campus Virchow-Klinikum, Klinik fuer Strahlenheilkunde, Charite, Universitaetsmedizin Berlin (Germany); Rohlfing, T. [Dept. of Neurosurgery, Stanford Univ. (United States); Hosten, N. [Inst. fuer Diagnostische Radiologie, Ernst-Moritz-Arndt-Univ. Greifswald (Germany)

    2004-12-01

    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.)

  17. Fusion of Thresholding Rules During Wavelet-Based Noisy Image Compression

    Directory of Open Access Journals (Sweden)

    Bekhtin Yury

    2016-01-01

    Full Text Available The new method for combining semisoft thresholding rules during wavelet-based data compression of images with multiplicative noise is suggested. The method chooses the best thresholding rule and the threshold value using the proposed criteria which provide the best nonlinear approximations and take into consideration errors of quantization. The results of computer modeling have shown that the suggested method provides relatively good image quality after restoration in the sense of some criteria such as PSNR, SSIM, etc.

  18. Fusion energy

    International Nuclear Information System (INIS)

    Gross, R.A.

    1984-01-01

    This textbook covers the physics and technology upon which future fusion power reactors will be based. It reviews the history of fusion, reaction physics, plasma physics, heating, and confinement. Descriptions of commercial plants and design concepts are included. Topics covered include: fusion reactions and fuel resources; reaction rates; ignition, and confinement; basic plasma directory; Tokamak confinement physics; fusion technology; STARFIRE: A commercial Tokamak fusion power plant. MARS: A tandem-mirror fusion power plant; and other fusion reactor concepts

  19. A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

    Science.gov (United States)

    Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

    2010-05-15

    Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

  20. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.