WorldWideScience

Sample records for multi-spectral image analysis

  1. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2011-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

  2. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat......In the present study, fresh beef fillets were purchased from a local butcher shop and stored aerobically and in modified atmosphere packaging (MAP, CO2 40%/O2 30%/N2 30%) at six different temperatures (0, 4, 8, 12, 16 and 20°C). Microbiological analysis in terms of total viable counts (TVC......) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...

  3. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R

    2006-02-01

    Full Text Available channel are boresighted with two beamsplitter windows; and • The IR system is boresighted. APPLICATION High-voltage environment • Detecting loose strands, bolts and nuts; • Detecting Corona discharges on insulator discs; • Detecting... and locating spark gaps; • Detecting and locating RIV sources; • Audit sub-stations and transmission lines for audio noise and Corona activities. RECORDINGS / APPLICATIONS REPORTING TOOL: MultiSOFT • Image handling software for grabbing, processing...

  4. Multi Spectral Fluorescence Imager (MSFI)

    Science.gov (United States)

    Caron, Allison

    2016-01-01

    Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

  5. Precise Multi-Spectral Dermatological Imaging

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Carstensen, Jens Michael; Ersbøll, Bjarne Kjær

    2004-01-01

    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral dermatological images is proposed. The system is made up of an integrating sphere, light emitting diodes and a generic monochromatic camera. The system can collect up to 10 different spectral bands....... These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

  6. Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

    2016-09-01

    In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

  7. Cloud-based processing of multi-spectral imaging data

    Science.gov (United States)

    Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

    2017-03-01

    Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

  8. Multi-spectral endogenous fluorescence imaging for bacterial differentiation

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

    2017-07-01

    In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

  9. AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

    NARCIS (Netherlands)

    Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

    2008-01-01

    The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

  10. Multi-spectral confocal microendoscope for in-vivo imaging

    Science.gov (United States)

    Rouse, Andrew Robert

    The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

  11. Semiconductor Laser Multi-Spectral Sensing and Imaging

    Directory of Open Access Journals (Sweden)

    Han Q. Le

    2010-01-01

    Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  12. Semiconductor laser multi-spectral sensing and imaging.

    Science.gov (United States)

    Le, Han Q; Wang, Yang

    2010-01-01

    Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  13. Scattering and absorption measurements of cervical tissues measures using low cost multi-spectral imaging

    Science.gov (United States)

    Bernat, Amir S.; Bar-Am, Kfir; Cataldo, Leigh; Bolton, Frank J.; Kahn, Bruce S.; Levitz, David

    2018-02-01

    Cervical cancer is a leading cause of death for women in low resource settings. In order to better detect cervical dysplasia, a low cost multi-spectral colposcope was developed utilizing low costs LEDs and an area scan camera. The device is capable of both traditional colposcopic imaging and multi-spectral image capture. Following initial bench testing, the device was deployed to a gynecology clinic where it was used to image patients in a colposcopy setting. Both traditional colposcopic images and spectral data from patients were uploaded to a cloud server for remote analysis. Multi-spectral imaging ( 30 second capture) took place before any clinical procedure; the standard of care was followed thereafter. If acetic acid was used in the standard of care, a post-acetowhitening colposcopic image was also captured. In analyzing the data, normal and abnormal regions were identified in the colposcopic images by an expert clinician. Spectral data were fit to a theoretical model based on diffusion theory, yielding information on scattering and absorption parameters. Data were grouped according to clinician labeling of the tissue, as well as any additional clinical test results available (Pap, HPV, biopsy). Altogether, N=20 patients were imaged in this study, with 9 of them abnormal. In comparing normal and abnormal regions of interest from patients, substantial differences were measured in blood content, while differences in oxygen saturation parameters were more subtle. These results suggest that optical measurements made using low cost spectral imaging systems can distinguish between normal and pathological tissues.

  14. Quantitative functional optical imaging of the human skin using multi-spectral imaging

    International Nuclear Information System (INIS)

    Kainerstorfer, J. M.

    2010-01-01

    Light tissue interactions can be described by the physical principles of absorption and scattering. Based on those parameters, different tissue types and analytes can be distinguished. Extracting blood volume and oxygenation is of particular interest in clinical routines for tumor diagnostics and treatment follow up, since they are parameters of angiogenic processes. The quantification of those analytes in tissue can be done by physical modeling of light tissue interaction. The physical model used here is the random walk theory. However, for quantification and clinical usefulness, one has to account for multiple challenges. First, one must consider the effect of topology of the sample on measured physical parameters. Second, diffusion of light inside the tissue is dependent on the structure of the sample imaged. Thus, the structural conformation has to be taken into account. Third, clinical translation of imaging modalities is often hindered due to the complicated post-processing of data, not providing results in real-time. In this thesis, two imaging modalities are being utilized, where the first one, diffuse multi-spectral imaging, is based on absorption contrast and spectral characteristics and the second one, Optical Coherence Tomography (OCT), is based on scattering changes within the tissue. Multi-spectral imaging can provide spatial distributions of blood volume and blood oxygenation and OCT yields 3D structural images with micrometer resolution. In order to address the challenges mentioned above, a curvature correction algorithm for taking the topology into account was developed. Without taking curvature of the object into account, reconstruction of optical properties is not accurate. The method developed removes this artifact and recovers the underlying data, without the necessity of measuring the object's shape. The next step was to recover blood volume and oxygenation values in real time. Principal Component Analysis (PCA) on multi spectral images is

  15. Terahertz detectors for long wavelength multi-spectral imaging.

    Energy Technology Data Exchange (ETDEWEB)

    Lyo, Sungkwun Kenneth; Wanke, Michael Clement; Reno, John Louis; Shaner, Eric Arthur; Grine, Albert D.

    2007-10-01

    The purpose of this work was to develop a wavelength tunable detector for Terahertz spectroscopy and imaging. Our approach was to utilize plasmons in the channel of a specially designed field-effect transistor called the grating-gate detector. Grating-gate detectors exhibit narrow-linewidth, broad spectral tunability through application of a gate bias, and no angular dependence in their photoresponse. As such, if suitable sensitivity can be attained, they are viable candidates for Terahertz multi-spectral focal plane arrays. When this work began, grating-gate gate detectors, while having many promising characteristics, had a noise-equivalent power (NEP) of only 10{sup -5} W/{radical}Hz. Over the duration of this project, we have obtained a true NEP of 10{sup -8} W/{radical}Hz and a scaled NEP of 10{sup -9}W/{radical}Hz. The ultimate goal for these detectors is to reach a NEP in the 10{sup -9{yields}-10}W/{radical}Hz range; we have not yet seen a roadblock to continued improvement.

  16. Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

  17. Deblurring sequential ocular images from multi-spectral imaging (MSI) via mutual information.

    Science.gov (United States)

    Lian, Jian; Zheng, Yuanjie; Jiao, Wanzhen; Yan, Fang; Zhao, Bojun

    2018-06-01

    Multi-spectral imaging (MSI) produces a sequence of spectral images to capture the inner structure of different species, which was recently introduced into ocular disease diagnosis. However, the quality of MSI images can be significantly degraded by motion blur caused by the inevitable saccades and exposure time required for maintaining a sufficiently high signal-to-noise ratio. This degradation may confuse an ophthalmologist, reduce the examination quality, or defeat various image analysis algorithms. We propose an early work specially on deblurring sequential MSI images, which is distinguished from many of the current image deblurring techniques by resolving the blur kernel simultaneously for all the images in an MSI sequence. It is accomplished by incorporating several a priori constraints including the sharpness of the latent clear image, the spatial and temporal smoothness of the blur kernel and the similarity between temporally-neighboring images in MSI sequence. Specifically, we model the similarity between MSI images with mutual information considering the different wavelengths used for capturing different images in MSI sequence. The optimization of the proposed approach is based on a multi-scale framework and stepwise optimization strategy. Experimental results from 22 MSI sequences validate that our approach outperforms several state-of-the-art techniques in natural image deblurring.

  18. Optical perception for detection of cutaneous T-cell lymphoma by multi-spectral imaging

    International Nuclear Information System (INIS)

    Hsiao, Yu-Ping; Wang, Hsiang-Chen; Chen, Shih-Hua; Tsai, Chung-Hung; Yang, Jen-Hung

    2014-01-01

    In this study, the spectrum of each picture element of the patient’s skin image was obtained by multi-spectral imaging technology. Spectra of normal or pathological skin were collected from 15 patients. Principal component analysis and principal component scores of skin spectra were employed to distinguish the spectral characteristics with different diseases. Finally, skin regions with suspected cutaneous T-cell lymphoma (CTCL) lesions were successfully predicted by evaluation and classification of the spectra of pathological skin. The sensitivity and specificity of this technique were 89.65% and 95.18% after the analysis of about 109 patients. The probability of atopic dermatitis and psoriasis patients misinterpreted as CTCL were 5.56% and 4.54%, respectively. (paper)

  19. Distant Determination of Bilirubin Distribution in Skin by Multi-Spectral Imaging

    Science.gov (United States)

    Saknite, I.; Jakovels, D.; Spigulis, J.

    2011-01-01

    For mapping the bilirubin distribution in bruised skin the multi-spectral imaging technique was employed, which made it possible to observe temporal changes of the bilirubin content in skin photo-types II and III. The obtained results confirm the clinical potential of this technique for skin bilirubin diagnostics.

  20. Tissues segmentation based on multi spectral medical images

    Science.gov (United States)

    Li, Ya; Wang, Ying

    2017-11-01

    Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

  1. 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).

  2. An improved feature extraction algorithm based on KAZE for multi-spectral image

    Science.gov (United States)

    Yang, Jianping; Li, Jun

    2018-02-01

    Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

  3. Multi-spectral lifetime imaging: methods and applications

    NARCIS (Netherlands)

    Fereidouni, F.

    2013-01-01

    The aim of this PhD project is to further develop multispectral life time imaging hardware and analyses methods. The hardware system, Lambda-Tau, generates a considerable amount of data at high speed. To fully exploit the power of this new hardware, fast and reliable data analyses methods are

  4. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

    International Nuclear Information System (INIS)

    Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

    2013-01-01

    Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment. (paper)

  5. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

    Science.gov (United States)

    Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

    2013-05-01

    Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment.

  6. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  7. Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

    Science.gov (United States)

    Platnick, Steven

    2004-01-01

    MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

  8. High performance multi-spectral interrogation for surface plasmon resonance imaging sensors.

    Science.gov (United States)

    Sereda, A; Moreau, J; Canva, M; Maillart, E

    2014-04-15

    Surface plasmon resonance (SPR) sensing has proven to be a valuable tool in the field of surface interactions characterization, especially for biomedical applications where label-free techniques are of particular interest. In order to approach the theoretical resolution limit, most SPR-based systems have turned to either angular or spectral interrogation modes, which both offer very accurate real-time measurements, but at the expense of the 2-dimensional imaging capability, therefore decreasing the data throughput. In this article, we show numerically and experimentally how to combine the multi-spectral interrogation technique with 2D-imaging, while finding an optimum in terms of resolution, accuracy, acquisition speed and reduction in data dispersion with respect to the classical reflectivity interrogation mode. This multi-spectral interrogation methodology is based on a robust five parameter fitting of the spectral reflectivity curve which enables monitoring of the reflectivity spectral shift with a resolution of the order of ten picometers, and using only five wavelength measurements per point. In fine, such multi-spectral based plasmonic imaging system allows biomolecular interaction monitoring in a linear regime independently of variations of buffer optical index, which is illustrated on a DNA-DNA model case. © 2013 Elsevier B.V. All rights reserved.

  9. A Lightweight Compact Multi-Spectral Imager Using Novel Computer-Generated Micro-Optics and Spectral-Extraction Algorithms

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this NASA Early-stage research proposal is to demonstrate an ultra-compact, lightweight broadband hyper- and multi-spectral imaging system that is...

  10. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  11. Using Non-Invasive Multi-Spectral Imaging to Quantitatively Assess Tissue Vasculature

    Energy Technology Data Exchange (ETDEWEB)

    Vogel, A; Chernomordik, V; Riley, J; Hassan, M; Amyot, F; Dasgeb, B; Demos, S G; Pursley, R; Little, R; Yarchoan, R; Tao, Y; Gandjbakhche, A H

    2007-10-04

    This research describes a non-invasive, non-contact method used to quantitatively analyze the functional characteristics of tissue. Multi-spectral images collected at several near-infrared wavelengths are input into a mathematical optical skin model that considers the contributions from different analytes in the epidermis and dermis skin layers. Through a reconstruction algorithm, we can quantify the percent of blood in a given area of tissue and the fraction of that blood that is oxygenated. Imaging normal tissue confirms previously reported values for the percent of blood in tissue and the percent of blood that is oxygenated in tissue and surrounding vasculature, for the normal state and when ischemia is induced. This methodology has been applied to assess vascular Kaposi's sarcoma lesions and the surrounding tissue before and during experimental therapies. The multi-spectral imaging technique has been combined with laser Doppler imaging to gain additional information. Results indicate that these techniques are able to provide quantitative and functional information about tissue changes during experimental drug therapy and investigate progression of disease before changes are visibly apparent, suggesting a potential for them to be used as complementary imaging techniques to clinical assessment.

  12. Multi-spectral quantitative phase imaging based on filtration of light via ultrasonic wave

    Science.gov (United States)

    Machikhin, A. S.; Polschikova, O. V.; Ramazanova, A. G.; Pozhar, V. E.

    2017-07-01

    A new digital holographic microscopy scheme for multi-spectral quantitative phase imaging is proposed and implemented. It is based on acousto-optic filtration of wide-band low-coherence light at the entrance of a Mach-Zehnder interferometer, recording and digital processing of interferograms. The key requirements for the acousto-optic filter are discussed. The effectiveness of the technique is demonstrated by calculating the phase maps of human red blood cells at multiple wavelengths in the range 770-810 nm. The scheme can be used for the measurement of dispersion of thin films and biological samples.

  13. Identification of a murine erythroblast subpopulation enriched in enucleating events by multi-spectral imaging flow cytometry.

    Science.gov (United States)

    Konstantinidis, Diamantis G; Pushkaran, Suvarnamala; Giger, Katie; Manganaris, Stefanos; Zheng, Yi; Kalfa, Theodosia A

    2014-06-06

    Erythropoiesis in mammals concludes with the dramatic process of enucleation that results in reticulocyte formation. The mechanism of enucleation has not yet been fully elucidated. A common problem encountered when studying the localization of key proteins and structures within enucleating erythroblasts by microscopy is the difficulty to observe a sufficient number of cells undergoing enucleation. We have developed a novel analysis protocol using multiparameter high-speed cell imaging in flow (Multi-Spectral Imaging Flow Cytometry), a method that combines immunofluorescent microscopy with flow cytometry, in order to identify efficiently a significant number of enucleating events, that allows to obtain measurements and perform statistical analysis. We first describe here two in vitro erythropoiesis culture methods used in order to synchronize murine erythroblasts and increase the probability of capturing enucleation at the time of evaluation. Then, we describe in detail the staining of erythroblasts after fixation and permeabilization in order to study the localization of intracellular proteins or lipid rafts during enucleation by multi-spectral imaging flow cytometry. Along with size and DNA/Ter119 staining which are used to identify the orthochromatic erythroblasts, we utilize the parameters "aspect ratio" of a cell in the bright-field channel that aids in the recognition of elongated cells and "delta centroid XY Ter119/Draq5" that allows the identification of cellular events in which the center of Ter119 staining (nascent reticulocyte) is far apart from the center of Draq5 staining (nucleus undergoing extrusion), thus indicating a cell about to enucleate. The subset of the orthochromatic erythroblast population with high delta centroid and low aspect ratio is highly enriched in enucleating cells.

  14. Radical advancement in multi-spectral imaging for autonomous vehicles (UAVs, UGVs, and UUVs) using active compensation.

    Energy Technology Data Exchange (ETDEWEB)

    Clark, Brian F.; Bagwell, Brett E.; Wick, David Victor

    2007-01-01

    The purpose of this LDRD was to demonstrate a compact, multi-spectral, refractive imaging systems using active optical compensation. Compared to a comparable, conventional lens system, our system has an increased operational bandwidth, provides for spectral selectivity and, non-mechanically corrects aberrations induced by the wavelength dependent properties of a passive refractive optical element (i.e. lens). The compact nature and low power requirements of the system lends itself to small platforms such as autonomous vehicles. In addition, the broad spectral bandwidth of our system would allow optimized performance for both day/night use, and the multi-spectral capability allows for spectral discrimination and signature identification.

  15. Primer on Use of Multi-Spectral and Infra Red Imaging for On-Site Inspections

    Energy Technology Data Exchange (ETDEWEB)

    Henderson, J R

    2010-10-26

    The purpose of an On-Site Inspection (OSI) is to determine whether a nuclear explosion has occurred in violation of the Comprehensive Nuclear Test Ban Treaty (CTBT), and to gather information which might assist in identifying the violator (CTBT, Article IV, Paragraph 35) Multi-Spectral and Infra Red Imaging (MSIR) is allowed by the treaty to detect observables which might help reduce the search area and thus expedite an OSI and make it more effective. MSIR is permitted from airborne measurements, and at and below the surface to search for anomalies and artifacts (CTBT, Protocol, Part II, Paragraph 69b). The three broad types of anomalies and artifacts MSIR is expected to be capable of observing are surface disturbances (disturbed earth, plant stress or anomalous surface materials), human artifacts (man-made roads, buildings and features), and thermal anomalies. The purpose of this Primer is to provide technical information on MSIR relevant to its use for OSI. It is expected that this information may be used for general background information, to inform decisions about the selection and testing of MSIR equipment, to develop operational guidance for MSIR use during an OSI, and to support the development of a training program for OSI Inspectors. References are provided so readers can pursue a topic in more detail than the summary information provided here. The following chapters will provide more information on how MSIR can support an OSI (Section 2), a short summary what Multi-Spectral Imaging and Infra Red Imaging is (Section 3), guidance from the CTBT regarding the use of MSIR (Section 4), and a description of several nuclear explosion scenarios (Section 5) and consequent observables (Section 6). The remaining sections focus on practical aspects of using MSIR for an OSI, such as specification and selection of MSIR equipment, operational considerations for deployment of MISR equipment from an aircraft, and the conduct of field exercises to mature MSIR for an OSI

  16. Crop status sensing system by multi-spectral imaging sensor, 1: Image processing and paddy field sensing

    International Nuclear Information System (INIS)

    Ishii, K.; Sugiura, R.; Fukagawa, T.; Noguchi, N.; Shibata, Y.

    2006-01-01

    The objective of the study is to construct a sensing system for precision farming. A Multi-Spectral Imaging Sensor (MSIS), which can obtain three images (G. R and NIR) simultaneously, was used for detecting growth status of plants. The sensor was mounted on an unmanned helicopter. An image processing method for acquiring information of crop status with high accuracy was developed. Crop parameters that were measured include SPAD, leaf height, and stems number. Both direct seeding variety and transplant variety of paddy rice were adopted in the research. The result of a field test showed that crop status of both varieties could be detected with sufficient accuracy to apply to precision farming

  17. Geo-oculus: high resolution multi-spectral earth imaging mission from geostationary orbit

    Science.gov (United States)

    Vaillon, L.; Schull, U.; Knigge, T.; Bevillon, C.

    2017-11-01

    Geo-Oculus is a GEO-based Earth observation mission studied by Astrium for ESA in 2008-2009 to complement the Sentinel missions, the space component of the GMES (Global Monitoring for Environment & Security). Indeed Earth imaging from geostationary orbit offers new functionalities not covered by existing LEO observation missions, like real-time monitoring and fast revisit capability of any location within the huge area in visibility of the satellite. This high revisit capability is exploited by the Meteosat meteorogical satellites, but with a spatial resolution (500 m nadir for the third generation) far from most of GMES needs (10 to 100 m). To reach such ground resolution from GEO orbit with adequate image quality, large aperture instruments (> 1 m) and high pointing stability (challenges of such missions. To address the requirements from the GMES user community, the Geo-Oculus mission is a combination of routine observations (daily systematic coverage of European coastal waters) with "on-demand" observation for event monitoring (e.g. disasters, fires and oil slicks). The instrument is a large aperture imaging telescope (1.5 m diameter) offering a nadir spatial sampling of 10.5 m (21 m worst case over Europe, below 52.5°N) in a PAN visible channel used for disaster monitoring. The 22 multi-spectral channels have resolutions over Europe ranging from 40 m in UV/VNIR (0.3 to 1 μm) to 750 m in TIR (10-12 μm).

  18. Determining fast orientation changes of multi-spectral line cameras from the primary images

    Science.gov (United States)

    Wohlfeil, Jürgen

    2012-01-01

    Fast orientation changes of airborne and spaceborne line cameras cannot always be avoided. In such cases it is essential to measure them with high accuracy to ensure a good quality of the resulting imagery products. Several approaches exist to support the orientation measurement by using optical information received through the main objective/telescope. In this article an approach is proposed that allows the determination of non-systematic orientation changes between every captured line. It does not require any additional camera hardware or onboard processing capabilities but the payload images and a rough estimate of the camera's trajectory. The approach takes advantage of the typical geometry of multi-spectral line cameras with a set of linear sensor arrays for different spectral bands on the focal plane. First, homologous points are detected within the heavily distorted images of different spectral bands. With their help a connected network of geometrical correspondences can be built up. This network is used to calculate the orientation changes of the camera with the temporal and angular resolution of the camera. The approach was tested with an extensive set of aerial surveys covering a wide range of different conditions and achieved precise and reliable results.

  19. The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions.

    Science.gov (United States)

    Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S

    2017-09-01

    BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided ( p quantitative data were provided. Negative predictive value also increased (68% vs. 91%, panalysis (64% vs. 86%, p data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.

  20. Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

    Science.gov (United States)

    The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

  1. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Directory of Open Access Journals (Sweden)

    Liang Lu

    2018-03-01

    Full Text Available Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

  2. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Science.gov (United States)

    Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

    2018-01-01

    Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

  3. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  4. Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI Data for Burned Area Discrimination

    Directory of Open Access Journals (Sweden)

    Haiyan Huang

    2016-10-01

    Full Text Available Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance and atmospherically corrected (surface reflectance images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence and non-parametric (decision tree approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms.

  5. A comparison of dimension reduction methods with application to multi-spectral images of sand used in concrete

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, M. E.; Ersbøll, Bjarne Kjær

    2010-01-01

    This paper presents a comparison of dimension reduction methods based on a novel machine vision application for estimating moisture content in sand used to make concrete. For the application in question it is very important to know the moisture content of the sand so as to ensure good-quality...... sand types were examined with 20-60 images for each type. To reduce the amount of data, features were extracted from the multi-spectral images; the features were summary statistics on single bands and pairs of bands as well as morphological summaries. The number of features (2,016) is high in relation...

  6. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  7. The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

    Science.gov (United States)

    Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

    2017-12-01

    The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

  8. 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.

  9. Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS).

    Energy Technology Data Exchange (ETDEWEB)

    Speed, Ann Elizabeth; Spahn, Olga Blum; Hsu, Alan Yuan-Chun

    2009-09-01

    Functional brain imaging is of great interest for understanding correlations between specific cognitive processes and underlying neural activity. This understanding can provide the foundation for developing enhanced human-machine interfaces, decision aides, and enhanced cognition at the physiological level. The functional near infrared spectroscopy (fNIRS) based event-related optical signal (EROS) technique can provide direct, high-fidelity measures of temporal and spatial characteristics of neural networks underlying cognitive behavior. However, current EROS systems are hampered by poor signal-to-noise-ratio (SNR) and depth of measure, limiting areas of the brain and associated cognitive processes that can be investigated. We propose to investigate a flexible, tunable, multi-spectral fNIRS EROS system which will provide up to 10x greater SNR as well as improved spatial and temporal resolution through significant improvements in electronics, optoelectronics and optics, as well as contribute to the physiological foundation of higher-order cognitive processes and provide the technical foundation for miniaturized portable neuroimaging systems.

  10. Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research

    OpenAIRE

    Milchenko, Mikhail; Snyder, Abraham Z.; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L.; Fouke, Sarah Jost; Marcus, Daniel S.

    2016-01-01

    Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis.

  11. Online Multi-Spectral Meat Inspection

    DEFF Research Database (Denmark)

    Nielsen, Jannik Boll; Larsen, Anders Boesen Lindbo

    2013-01-01

    We perform an explorative study on multi-spectral image data from a prototype device developed for fast online quality inspection of meat products. Because the camera setup is built for speed, we sacrifice exact pixel correspondences between the different bands of the multi-spectral images. Our...... work is threefold as we 1) investigate the color distributions and construct a model to describe pork loins, 2) classify the different components in pork loins (meat, fat, membrane), and 3) detect foreign objects on the surface of pork loins. Our investigation shows that the color distributions can...

  12. Sperm Scoring Using Multi-Spectral Flow Imaging and FISH-IS Final Report CRADA No. TC02088.0

    Energy Technology Data Exchange (ETDEWEB)

    Marchetti, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Morrissey, P. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-09-27

    This was to be a collaborative effort between The Regents of the University of California, Lawrence Livermore National Laboratory (LLNL) and Amnis Corporation, to develop an automated system for scoring sperm interphase cells for the presence of chromosomal abnormalities using fluorescence in situ hybridization and the Amnis ImageStream technology platform.

  13. Multi-Spectral Imaging from an Unmanned Aerial Vehicle Enables the Assessment of Seasonal Leaf Area Dynamics of Sorghum Breeding Lines

    Directory of Open Access Journals (Sweden)

    Andries B. Potgieter

    2017-09-01

    Full Text Available Genetic improvement in sorghum breeding programs requires the assessment of adaptation traits in small-plot breeding trials across multiple environments. Many of these phenotypic assessments are made by manual measurement or visual scoring, both of which are time consuming and expensive. This limits trial size and the potential for genetic gain. In addition, these methods are typically restricted to point estimates of particular traits, such as leaf senescence or flowering and do not capture the dynamic nature of crop growth. In water-limited environments in particular, information on leaf area development over time would provide valuable insight into water use and adaptation to water scarcity during specific phenological stages of crop development. Current methods to estimate plant leaf area index (LAI involve destructive sampling and are not practical in breeding. Unmanned aerial vehicles (UAV and proximal-sensing technologies open new opportunities to assess these traits multiple times in large small-plot trials. We analyzed vegetation-specific crop indices obtained from a narrowband multi-spectral camera on board a UAV platform flown over a small pilot trial with 30 plots (10 genotypes randomized within 3 blocks. Due to variable emergence we were able to assess the utility of these vegetation indices to estimate canopy cover and LAI over a large range of plant densities. We found good correlations between the Normalized Difference Vegetation Index (NDVI and the Enhanced Vegetation Index (EVI with plant number per plot, canopy cover and LAI both during the vegetative growth phase (pre-anthesis and at maximum canopy cover shortly after anthesis. We also analyzed the utility of time-sequence data to assess the senescence pattern of sorghum genotypes known as fast (senescent or slow senescing (stay-green types. The Normalized Difference Red Edge (NDRE index which estimates leaf chlorophyll content was most useful in characterizing the leaf area

  14. Multi spectral scaling data acquisition system

    International Nuclear Information System (INIS)

    Behere, Anita; Patil, R.D.; Ghodgaonkar, M.D.; Gopalakrishnan, K.R.

    1997-01-01

    In nuclear spectroscopy applications, it is often desired to acquire data at high rate with high resolution. With the availability of low cost computers, it is possible to make a powerful data acquisition system with minimum hardware and software development, by designing a PC plug-in acquisition board. But in using the PC processor for data acquisition, the PC can not be used as a multitasking node. Keeping this in view, PC plug-in acquisition boards with on-board processor find tremendous applications. Transputer based data acquisition board has been designed which can be configured as a high count rate pulse height MCA or as a Multi Spectral Scaler. Multi Spectral Scaling (MSS) is a new technique, in which multiple spectra are acquired in small time frames and are then analyzed. This paper describes the details of this multi spectral scaling data acquisition system. 2 figs

  15. Airborne Multi-Spectral Minefield Survey

    Science.gov (United States)

    2005-05-01

    Swedish Defence Research Agency), GEOSPACE (Austria), GTD ( Ingenieria de Sistemas y Software Industrial, Spain), IMEC (Ineruniversity MicroElectronic...RTO-MP-SET-092 18 - 1 UNCLASSIFIED/UNLIMITED UNCLASSIFIED/UNLIMITED Airborne Multi-Spectral Minefield Survey Dirk-Jan de Lange, Eric den...actions is the severe lack of baseline information. To respond to this in a rapid way, cost-efficient data acquisition methods are a key issue. de

  16. Multi-spectral optical scanners for commercial earth observation missions

    Science.gov (United States)

    Schröter, Karin; Engel, Wolfgang; Berndt, Klaus

    2017-11-01

    In recent years, a number of commercial Earth observation missions have been initiated with the aim to gather data in the visible and near-infrared wavelength range. Some of these missions aim at medium resolution (5 to 10 m) multi-spectral imaging with the special background of daily revisiting. Typical applications aim at monitoring of farming area for growth control and harvest prediction, irrigation control, or disaster monitoring such as hail damage in farming, or flood survey. In order to arrive at profitable business plans for such missions, it is mandatory to establish the space segment, i.e. the spacecraft with their opto -electronic payloads, at minimum cost while guaranteeing maximum reliability for mission success. As multiple spacecraft are required for daily revisiting, the solutions are typically based on micro-satellites. This paper presents designs for multi-spectral opto-electric scanners for this type of missions. These designs are drive n by minimum mass and power budgets of microsatellites, and the need for minimum cost. As a consequence, it is mandatory to arrive at thermally robust, compact telescope designs. The paper gives a comparison between refractive, catadioptric, and TMA optics. For mirror designs, aluminium and Zerodur mirror technologies are briefly discussed. State-of-the art focal plane designs are presented. The paper also addresses the choice of detector technologies such as CCDs and CMOS Active Pixel Sensors. The electronics of the multi-spectral scanners represent the main design driver regarding power consumption, reliability, and (most often) cost. It can be subdivided into the detector drive electronics, analog and digital data processing chains, the data mass memory unit, formatting and down - linking units, payload control electronics, and local power supply. The paper gives overviews and trade-offs between data compression strategies and electronics solutions, mass memory unit designs, and data formatting approaches

  17. From Digital Imaging to Computer Image Analysis of Fine Art

    Science.gov (United States)

    Stork, David G.

    An expanding range of techniques from computer vision, pattern recognition, image analysis, and computer graphics are being applied to problems in the history of art. The success of these efforts is enabled by the growing corpus of high-resolution multi-spectral digital images of art (primarily paintings and drawings), sophisticated computer vision methods, and most importantly the engagement of some art scholars who bring questions that may be addressed through computer methods. This paper outlines some general problem areas and opportunities in this new inter-disciplinary research program.

  18. FUNSTAT and statistical image representations

    Science.gov (United States)

    Parzen, E.

    1983-01-01

    General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

  19. Exploiting physical constraints for multi-spectral exo-planet detection

    Science.gov (United States)

    Thiébaut, Éric; Devaney, Nicholas; Langlois, Maud; Hanley, Kenneth

    2016-07-01

    We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters. The residual speckles1, 2 set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE3 at the VLT, GPI4, 5 at Gemini, or SCExAO6 at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI7 are based on angular differential imaging8 (ADI), spectral differential imaging9, 10 (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation

  20. Automated road network extraction from high spatial resolution multi-spectral imagery

    Science.gov (United States)

    Zhang, Qiaoping

    For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

  1. Multi-spectral and fluorescence diffuse optical tomography of breast cancer

    Science.gov (United States)

    Corlu, Alper

    Multi-spectral and fluorescence diffuse optical tomography (DOT) techniques are explored and applied to image human breast cancer in vivo. Image reconstruction algorithms that utilize first and second order gradient information are described in detail. Breast DOT requires large computational memory and long run times. To this end, parallel computation techniques were developed appropriate to each reconstruction algorithm. A parallel plate DOT instrument developed for breast cancer imaging is described. The system relies heavily on continuous-wave (CW) transmission measurements and utilizes frequency domain (FD) measurements on the reemission side. However, traditional DOT image reconstruction methods based on CW measurements fail to separate tissue absorption and scattering uniquely. In this manuscript, multi-spectral DOT is shown to be capable of minimizing cross-talk and retrieving spectral parameters almost uniquely when the measurement wavelengths are optimized. A theoretical framework to select optimum wavelengths is provided, and tested with computer simulations. Results from phantom spectroscopy experiments and in vivo patient measurements support the notion that multi-spectral methods are superior to traditional DOT image reconstruction schemes. The same breast DOT instrument is improved and utilized to obtain the first in vivo images of human breast cancer based on fluorescence DOT (FDOT). To this end the fluorophore Indocyanine Green (ICG) is injected intravenously and fluorescence excitation and detection are accomplished in the soft-compression, parallel-plane, transmission geometry using laser sources at 786 nm and spectrally filtered CCD detection. Careful phantom and in vivo measurements are carried on to assure that the signals are due to ICG fluorescence, rather than tissue autofluorescence and excitation light leakage. An in vivo measurement protocol is designed to maximize the ICG contrast by acquiring full fluorescence tomographic scan during

  2. Image analysis

    International Nuclear Information System (INIS)

    Berman, M.; Bischof, L.M.; Breen, E.J.; Peden, G.M.

    1994-01-01

    This paper provides an overview of modern image analysis techniques pertinent to materials science. The usual approach in image analysis contains two basic steps: first, the image is segmented into its constituent components (e.g. individual grains), and second, measurement and quantitative analysis are performed. Usually, the segmentation part of the process is the harder of the two. Consequently, much of the paper concentrates on this aspect, reviewing both fundamental segmentation tools (commonly found in commercial image analysis packages) and more advanced segmentation tools. There is also a review of the most widely used quantitative analysis methods for measuring the size, shape and spatial arrangements of objects. Many of the segmentation and analysis methods are demonstrated using complex real-world examples. Finally, there is a discussion of hardware and software issues. 42 refs., 17 figs

  3. Application of principal component analysis to multispectral imaging data for evaluation of pigmented skin lesions

    Science.gov (United States)

    Jakovels, Dainis; Lihacova, Ilze; Kuzmina, Ilona; Spigulis, Janis

    2013-11-01

    Non-invasive and fast primary diagnostics of pigmented skin lesions is required due to frequent incidence of skin cancer - melanoma. Diagnostic potential of principal component analysis (PCA) for distant skin melanoma recognition is discussed. Processing of the measured clinical multi-spectral images (31 melanomas and 94 nonmalignant pigmented lesions) in the wavelength range of 450-950 nm by means of PCA resulted in 87 % sensitivity and 78 % specificity for separation between malignant melanomas and pigmented nevi.

  4. Multi-spectral CCD camera system for ocean water color and seacoast observation

    Science.gov (United States)

    Zhu, Min; Chen, Shiping; Wu, Yanlin; Huang, Qiaolin; Jin, Weiqi

    2001-10-01

    One of the earth observing instruments on HY-1 Satellite which will be launched in 2001, the multi-spectral CCD camera system, is developed by Beijing Institute of Space Mechanics & Electricity (BISME), Chinese Academy of Space Technology (CAST). In 798 km orbit, the system can provide images with 250 m ground resolution and a swath of 500 km. It is mainly used for coast zone dynamic mapping and oceanic watercolor monitoring, which include the pollution of offshore and coast zone, plant cover, watercolor, ice, terrain underwater, suspended sediment, mudflat, soil and vapor gross. The multi- spectral camera system is composed of four monocolor CCD cameras, which are line array-based, 'push-broom' scanning cameras, and responding for four spectral bands. The camera system adapts view field registration; that is, each camera scans the same region at the same moment. Each of them contains optics, focal plane assembly, electrical circuit, installation structure, calibration system, thermal control and so on. The primary features on the camera system are: (1) Offset of the central wavelength is better than 5 nm; (2) Degree of polarization is less than 0.5%; (3) Signal-to-noise ratio is about 1000; (4) Dynamic range is better than 2000:1; (5) Registration precision is better than 0.3 pixel; (6) Quantization value is 12 bit.

  5. The fabrication of a multi-spectral lens array and its application in assisting color blindness

    Science.gov (United States)

    Di, Si; Jin, Jian; Tang, Guanrong; Chen, Xianshuai; Du, Ruxu

    2016-01-01

    This article presents a compact multi-spectral lens array and describes its application in assisting color-blindness. The lens array consists of 9 microlens, and each microlens is coated with a different color filter. Thus, it can capture different light bands, including red, orange, yellow, green, cyan, blue, violet, near-infrared, and the entire visible band. First, the fabrication process is described in detail. Second, an imaging system is setup and a color blindness testing card is selected as the sample. By the system, the vision results of normal people and color blindness can be captured simultaneously. Based on the imaging results, it is possible to be used for helping color-blindness to recover normal vision.

  6. Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data

    Science.gov (United States)

    Likens, W. C.; Wrigley, R. C.

    1984-01-01

    Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.

  7. Multi-spectral pyrometer for gas turbine blade temperature measurement

    Science.gov (United States)

    Gao, Shan; Wang, Lixin; Feng, Chi

    2014-09-01

    To achieve the highest possible turbine inlet temperature requires to accurately measuring the turbine blade temperature. If the temperature of blade frequent beyond the design limits, it will seriously reduce the service life. The problem for the accuracy of the temperature measurement includes the value of the target surface emissivity is unknown and the emissivity model is variability and the thermal radiation of the high temperature environment. In this paper, the multi-spectral pyrometer is designed provided mainly for range 500-1000°, and present a model corrected in terms of the error due to the reflected radiation only base on the turbine geometry and the physical properties of the material. Under different working conditions, the method can reduce the measurement error from the reflect radiation of vanes, make measurement closer to the actual temperature of the blade and calculating the corresponding model through genetic algorithm. The experiment shows that this method has higher accuracy measurements.

  8. On multi-spectral quantitative photoacoustic tomography in diffusive regime

    International Nuclear Information System (INIS)

    Bal, Guillaume; Ren, Kui

    2012-01-01

    The objective of quantitative photoacoustic tomography (qPAT) is to reconstruct the diffusion, absorption and Grüneisen thermodynamic coefficients of heterogeneous media from knowledge of the interior absorbed radiation. It has been shown in Bal and Ren (2011 Inverse Problems 27 075003), based on diffusion theory, that with data acquired at one given wavelength, all three coefficients cannot be reconstructed uniquely. In this work, we study the multi-spectral qPAT problem and show that when multiple wavelength data are available, all coefficients can be reconstructed simultaneously under minor prior assumptions. Moreover, the reconstructions are shown to be very stable. We present some numerical simulations that support the theoretical results. (paper)

  9. The source of multi spectral energy of solar energetic electron

    Energy Technology Data Exchange (ETDEWEB)

    Herdiwijaya, Dhani [Astronomy Division and Bosscha Observatory, Faculty Mathematics and Natural Sciences, Intitute Technology of Bandung, Ganesha 10, Bandung, Indonesia 40132 dhani@as.itb.ac.id (Indonesia)

    2015-04-16

    We study the solar energetic electron distribution obtained from ACE and GOES satellites which have different altitudes and electron spectral energy during the year 1997 to 2011. The electron spectral energies were 0.038–0.315 MeV from EPAM instrument onboard ACE satellite and >2 MeV from GOES satellite. We found that the low electron energy has no correlation with high energy. In spite of we have corrected to the altitude differences. It implied that they originated from time dependent events with different sources and physical processes at the solar atmosphere. The sources of multi spectral energetic electron were related to flare and CME phenomena. However, we also found that high energetic electron comes from coronal hole.

  10. Image Analysis

    DEFF Research Database (Denmark)

    The 19th Scandinavian Conference on Image Analysis was held at the IT University of Copenhagen in Denmark during June 15-17, 2015. The SCIA conference series has been an ongoing biannual event for more than 30 years and over the years it has nurtured a world-class regional research and development...... area within the four participating Nordic countries. It is a regional meeting of the International Association for Pattern Recognition (IAPR). We would like to thank all authors who submitted works to this year’s SCIA, the invited speakers, and our Program Committee. In total 67 papers were submitted....... The topics of the accepted papers range from novel applications of vision systems, pattern recognition, machine learning, feature extraction, segmentation, 3D vision, to medical and biomedical image analysis. The papers originate from all the Scandinavian countries and several other European countries...

  11. Frequency position modulation using multi-spectral projections

    Science.gov (United States)

    Goodman, Joel; Bertoncini, Crystal; Moore, Michael; Nousain, Bryan; Cowart, Gregory

    2012-10-01

    In this paper we present an approach to harness multi-spectral projections (MSPs) to carefully shape and locate tones in the spectrum, enabling a new and robust modulation in which a signal's discrete frequency support is used to represent symbols. This method, called Frequency Position Modulation (FPM), is an innovative extension to MT-FSK and OFDM and can be non-uniformly spread over many GHz of instantaneous bandwidth (IBW), resulting in a communications system that is difficult to intercept and jam. The FPM symbols are recovered using adaptive projections that in part employ an analog polynomial nonlinearity paired with an analog-to-digital converter (ADC) sampling at a rate at that is only a fraction of the IBW of the signal. MSPs also facilitate using commercial of-the-shelf (COTS) ADCs with uniform-sampling, standing in sharp contrast to random linear projections by random sampling, which requires a full Nyquist rate sample-and-hold. Our novel communication system concept provides an order of magnitude improvement in processing gain over conventional LPI/LPD communications (e.g., FH- or DS-CDMA) and facilitates the ability to operate in interference laden environments where conventional compressed sensing receivers would fail. We quantitatively analyze the bit error rate (BER) and processing gain (PG) for a maximum likelihood based FPM demodulator and demonstrate its performance in interference laden conditions.

  12. Multi-spectral optical absorption in substrate-free nanowire arrays

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Junpeng; Chia, Andrew; Boulanger, Jonathan; LaPierre, Ray, E-mail: lapierr@mcmaster.ca [Department of Engineering Physics, McMaster University, 1280 Main St. West, Hamilton, Ontario L8S 4L7 (Canada); Dhindsa, Navneet; Khodadad, Iman; Saini, Simarjeet [Department of Electrical and Computer Engineering, University of Waterloo, 200 University Ave West, Waterloo, Ontario N2L 3G1 (Canada); Waterloo Institute of Nanotechnology, University of Waterloo, 200 University Ave West, Waterloo, Ontario N2L 3G1 (Canada)

    2014-09-22

    A method is presented of fabricating gallium arsenide (GaAs) nanowire arrays of controlled diameter and period by reactive ion etching of a GaAs substrate containing an indium gallium arsenide (InGaP) etch stop layer, allowing the precise nanowire length to be controlled. The substrate is subsequently removed by selective etching, using the same InGaP etch stop layer, to create a substrate-free GaAs nanowire array. The optical absorptance of the nanowire array was then directly measured without absorption from a substrate. We directly observe absorptance spectra that can be tuned by the nanowire diameter, as explained with rigorous coupled wave analysis. These results illustrate strong optical absorption suitable for nanowire-based solar cells and multi-spectral absorption for wavelength discriminating photodetectors. The solar-weighted absorptance above the bandgap of GaAs was 94% for a nanowire surface coverage of only 15%.

  13. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

    Science.gov (United States)

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

    2014-01-01

    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  14. Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

    Science.gov (United States)

    Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

    2018-06-01

    Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device (CCD) and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.

  15. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python

    Directory of Open Access Journals (Sweden)

    Nicolas eRey-Villamizar

    2014-04-01

    Full Text Available In this article, we describe use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis task, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral brain tissue images surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels, 6,000$times$10,000$times$500 voxels with 16 bits/voxel, implying image sizes exceeding 250GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analytics for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment consisting. Our Python script enables efficient data storage and movement between compute and storage servers, logging all processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  16. Microscopic validation of whole mouse micro-metastatic tumor imaging agents using cryo-imaging and sliding organ image registration

    OpenAIRE

    Liu, Yiqiao; Zhou, Bo; Qutaish, Mohammed; Wilson, David L.

    2016-01-01

    We created a metastasis imaging, analysis platform consisting of software and multi-spectral cryo-imaging system suitable for evaluating emerging imaging agents targeting micro-metastatic tumor. We analyzed CREKA-Gd in MRI, followed by cryo-imaging which repeatedly sectioned and tiled microscope images of the tissue block face, providing anatomical bright field and molecular fluorescence, enabling 3D microscopic imaging of the entire mouse with single metastatic cell sensitivity. To register ...

  17. Detecting early stage pressure ulcer on dark skin using multispectral imager

    Science.gov (United States)

    Kong, Linghua; Sprigle, Stephen; Yi, Dingrong; Wang, Chao; Wang, Fengtao; Liu, Fuhan; Wang, Jiwu; Zhao, Futing

    2009-10-01

    This paper introduces a novel idea, innovative technology in building multi spectral imaging based device. The benefit from them is people can have low cost, handheld and standing alone device which makes acquire multi spectral images real time with just a snapshot. The paper for the first time publishes some images got from such prototyped miniaturized multi spectral imager.

  18. The SiC hardware of the Sentinel-2 multi spectral instrument

    Science.gov (United States)

    Bougoin, Michel; Lavenac, Jérôme

    2017-11-01

    The Sentinel-2 mission is a major part of the GMES (Global Monitoring for Environment and Security) program which has been set up by the European Union, on a joint initiative with the European Space Agency. A pair of identical satellites will observe the earth from a sun-synchronous orbit at 786 km altitude. Astrium is the prime contractor of the satellites and their payload. The MultiSpectral Instrument features a "all-SiC" TMA (Three Mirror Anastygmat) telescope. MSI will provide optical images in 13 spectral bands, in the visible and also the near infra-red range, with a 10 to 60 m resolution and a 290 km wide swath. The Boostec® SiC material is used mainly for its high specific stiffness (Youngs modulus / density) and its high thermal stability (thermal conductivity / coefficient of thermal expansion) which allow to reduce the distortions induced by thermo-elastic stresses. Its high mechanical properties as well as the relevant technology enable to make not only the mirrors but also the structure which holds them and the elements of the focal plane (including some detectors packaging). Due to the required large size, accuracy and shape complexity, developing and manufacturing some of these SiC parts required innovative manufacturing approach. It is reviewed in the present paper.

  19. Spinal imaging and image analysis

    CERN Document Server

    Yao, Jianhua

    2015-01-01

    This book is instrumental to building a bridge between scientists and clinicians in the field of spine imaging by introducing state-of-the-art computational methods in the context of clinical applications.  Spine imaging via computed tomography, magnetic resonance imaging, and other radiologic imaging modalities, is essential for noninvasively visualizing and assessing spinal pathology. Computational methods support and enhance the physician’s ability to utilize these imaging techniques for diagnosis, non-invasive treatment, and intervention in clinical practice. Chapters cover a broad range of topics encompassing radiological imaging modalities, clinical imaging applications for common spine diseases, image processing, computer-aided diagnosis, quantitative analysis, data reconstruction and visualization, statistical modeling, image-guided spine intervention, and robotic surgery. This volume serves a broad audience as  contributions were written by both clinicians and researchers, which reflects the inte...

  20. Retinal Imaging and Image Analysis

    Science.gov (United States)

    Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

    2011-01-01

    Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:22275207

  1. A Cost Effective Multi-Spectral Scanner for Natural Gas Detection

    Energy Technology Data Exchange (ETDEWEB)

    Yudaya Sivathanu; Jongmook Lim; Vinoo Narayanan; Seonghyeon Park

    2005-12-07

    The objective of this project is to design, fabricate and demonstrate a cost effective, multi-spectral scanner for natural gas leak detection in transmission and distribution pipelines. During the first year of the project, a laboratory version of the multi-spectral scanner was designed, fabricated, and tested at EnUrga Inc. The multi-spectral scanner was also evaluated using a blind Department of Energy study at the Rocky Mountain Oilfield Testing Center. The performance of the scanner was inconsistent during the blind study. However, most of the leaks were outside the view of the multi-spectral scanner that was developed during the first year of the project. Therefore, a definite evaluation of the capability of the scanner was not obtained. Despite the results, sufficient number of plumes was detected fully confirming the feasibility of the multi-spectral scanner. During the second year, the optical design of the scanner was changed to improve the sensitivity of the system. Laboratory tests show that the system can reliably detect small leaks (20 SCFH) at 30 to 50 feet. A prototype scanner was built and evaluated during the second year of the project. Only laboratory evaluations were completed during the second year. The laboratory evaluations show the feasibility of using the scanner to determine natural gas pipeline leaks. Further field evaluations and optimization of the scanner are required before commercialization of the scanner can be initiated.

  2. CHANGE DETECTION OF CROPPING PATTERN IN PADDY FIELD USING MULTI SPECTRAL SATELLITE DATA FOR ESTIMATING IRRIGATION WATER NEEDS

    Directory of Open Access Journals (Sweden)

    Rizatus Shofiyati1

    2012-10-01

    Full Text Available This paper investigates the use of multi spectral satellite data for cropping pattern monitoring in paddy field. The southern coastal of Citarum watershed, West Java Province was selected as study sites. The analysis used in this study is identifying crop pattern based on growth stages of wetland paddy and other crops by investi-gating the characteristic of Normalized Differen-ce Vegetation Indices (NDVI and Wetness of Tasseled Cap Transformation (TCT derived from 14 scenes of Landsat TM date 1988 to 2001. In general, the phenological of growth stages of wetland paddy can be used to distinguish with other seasonal crops. The research results indicate that multi spectral satellite data has a great potential for identi-fication and monitoring cropping pattern in paddy field. Specific character of NDVI and Wetness can also produce a map of cropping pattern in paddy field that is useful to monitor agricultural land condition. The cropping pattern can also be used to estimate irrigation water needed of paddy field in the area. Expected implication of the information obtained from this analysis is useful for guiding more appropriate planning and better agricultural management.

  3. Skin condition measurement by using multispectral imaging system (Conference Presentation)

    Science.gov (United States)

    Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

    2017-02-01

    There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

  4. A NEW MULTI-SPECTRAL THRESHOLD NORMALIZED DIFFERENCE WATER INDEX (MST-NDWI WATER EXTRACTION METHOD – A CASE STUDY IN YANHE WATERSHED

    Directory of Open Access Journals (Sweden)

    Y. Zhou

    2018-05-01

    Full Text Available Accurate remote sensing water extraction is one of the primary tasks of watershed ecological environment study. Since the Yanhe water system has typical characteristics of a small water volume and narrow river channel, which leads to the difficulty for conventional water extraction methods such as Normalized Difference Water Index (NDWI. A new Multi-Spectral Threshold segmentation of the NDWI (MST-NDWI water extraction method is proposed to achieve the accurate water extraction in Yanhe watershed. In the MST-NDWI method, the spectral characteristics of water bodies and typical backgrounds on the Landsat/TM images have been evaluated in Yanhe watershed. The multi-spectral thresholds (TM1, TM4, TM5 based on maximum-likelihood have been utilized before NDWI water extraction to realize segmentation for a division of built-up lands and small linear rivers. With the proposed method, a water map is extracted from the Landsat/TM images in 2010 in China. An accuracy assessment is conducted to compare the proposed method with the conventional water indexes such as NDWI, Modified NDWI (MNDWI, Enhanced Water Index (EWI, and Automated Water Extraction Index (AWEI. The result shows that the MST-NDWI method generates better water extraction accuracy in Yanhe watershed and can effectively diminish the confusing background objects compared to the conventional water indexes. The MST-NDWI method integrates NDWI and Multi-Spectral Threshold segmentation algorithms, with richer valuable information and remarkable results in accurate water extraction in Yanhe watershed.

  5. Retinal imaging and image analysis

    NARCIS (Netherlands)

    Abramoff, M.D.; Garvin, Mona K.; Sonka, Milan

    2010-01-01

    Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of

  6. 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.

  7. Exploiting the capabilities of the Sentinel-2 multi spectral instrument for predicting growing stock volume in forest ecosystems

    Science.gov (United States)

    Mura, Matteo; Bottalico, Francesca; Giannetti, Francesca; Bertani, Remo; Giannini, Raffaello; Mancini, Marco; Orlandini, Simone; Travaglini, Davide; Chirici, Gherardo

    2018-04-01

    The spatial prediction of growing stock volume is one of the most frequent application of remote sensing for supporting the sustainable management of forest ecosystems. For such a purpose data from active or passive sensors are used as predictor variables in combination with measures taken in the field in sampling plots. The Sentinel-2 (S2) satellites are equipped with a Multi Spectral Instrument (MSI) capable of acquiring 13 bands in the visible and infrared domains with a spatial resolution varying between 10 and 60 m. The present study aimed at evaluating the performance of the S2-MSI imagery for estimating the growing stock volume of forest ecosystems. To do so we used 240 plots measured in two study areas in Italy. The imputation was carried out with eight k-Nearest Neighbours (k-NN) methods available in the open source YaImpute R package. In order to evaluate the S2-MSI performance we repeated the experimental protocol also with two other sets of images acquired by two well-known satellites equipped with multi spectral instruments: Landsat 8 OLI and RapidEye scanner. We found that S2 worked better than Landsat in 37.5% of the cases and in 62.5% of the cases better than RapidEye. In one study area the best performance was obtained with Landsat OLI (RMSD = 6.84%) and in the other with S2 (RMSD = 22.94%), both with the k-NN system based on a distance matrix calculated with the Random Forest algorithm. The results confirmed that S2 images are suitable for predicting growing stock volume obtaining good performances (average RMSD for both the test areas of less than 19%).

  8. Multi-spectral band selection for satellite-based systems

    International Nuclear Information System (INIS)

    Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

    1998-01-01

    The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed

  9. An improved technique for the prediction of optimal image resolution ...

    African Journals Online (AJOL)

    user

    2010-10-04

    Oct 4, 2010 ... Available online at http://www.academicjournals.org/AJEST ... robust technique for predicting optimal image resolution for the mapping of savannah ecosystems was developed. .... whether to purchase multi-spectral imagery acquired by GeoEye-2 ..... Analysis of the spectral behaviour of the pasture class in.

  10. Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

    Directory of Open Access Journals (Sweden)

    Mitch Bryson

    Full Text Available Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae and animal (e.g. gastropods assemblages at multiple spatial and temporal scales.

  11. Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

    Science.gov (United States)

    Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

    2013-01-01

    Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

  12. Oncological image analysis.

    Science.gov (United States)

    Brady, Sir Michael; Highnam, Ralph; Irving, Benjamin; Schnabel, Julia A

    2016-10-01

    Cancer is one of the world's major healthcare challenges and, as such, an important application of medical image analysis. After a brief introduction to cancer, we summarise some of the major developments in oncological image analysis over the past 20 years, but concentrating those in the authors' laboratories, and then outline opportunities and challenges for the next decade. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Gabor Analysis for Imaging

    DEFF Research Database (Denmark)

    Christensen, Ole; Feichtinger, Hans G.; Paukner, Stephan

    2015-01-01

    , it characterizes a function by its transform over phase space, which is the time–frequency plane (TF-plane) in a musical context or the location–wave-number domain in the context of image processing. Since the transition from the signal domain to the phase space domain introduces an enormous amount of data...... of the generalities relevant for an understanding of Gabor analysis of functions on Rd. We pay special attention to the case d = 2, which is the most important case for image processing and image analysis applications. The chapter is organized as follows. Section 2 presents central tools from functional analysis......, the application of Gabor expansions to image representation is considered in Sect. 6....

  14. Digital image analysis

    DEFF Research Database (Denmark)

    Riber-Hansen, Rikke; Vainer, Ben; Steiniche, Torben

    2012-01-01

    Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides...... reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques....

  15. Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

    Science.gov (United States)

    Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

    2013-06-01

    Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

  16. Using Multi-Spectral UAV Imagery to Extract Tree Crop Structural Properties and Assess Pruning Effects

    Directory of Open Access Journals (Sweden)

    Kasper Johansen

    2018-06-01

    Full Text Available Unmanned aerial vehicles (UAV provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e., tree crown perimeter, width, height, area and Plant Projective Cover (PPC, was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m2, and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV-based approach for larger orchards. The different flying heights (i.e., 30, 50 and 70 m produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

  17. MULTI-TEMPORAL ASSESSMENT OF LYCHEE TREE CROP STRUCTURE USING MULTI-SPECTRAL RPAS IMAGERY

    Directory of Open Access Journals (Sweden)

    K. Johansen

    2017-08-01

    Full Text Available The lychee tree is native to China and produce small fleshy fruit up to 5 cm in diameter. Lychee production in Australia is worth > $20 million annually. Pruning of trees encourages new growth, has a positive effect on fruiting of lychee, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. The objective of this research was to assess changes in tree structure, i.e. tree crown circumference, width, height and Plant Projective Cover (PPC using multi-spectral Remotely Piloted Aircraft System (RPAS imagery collected before and after pruning of a lychee plantation. A secondary objective was to assess any variations in the results as a function of various flying heights (30, 50 and 70 m. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in: tree crown circumference of 1.94 m; tree crown width of 0.57 m; tree crown height of 0.62 m; and PPC of 14.8 %. The different flying heights produced similar measurements of tree crown width and PPC, whereas tree crown circumference and height measurements decreased with increasing flying height. These results show that multi-spectral RPAS imagery can provide a suitable means of assessing pruning efforts undertaken by contractors based on changes in tree structure of lychee plantations and that it is important to collect imagery in a consistent manner, as varying flying heights may cause changes to tree structural measurements.

  18. Using Multi-Spectral UAV Imagery to Extract Tree Crop Structural Properties and Assess Pruning Effects

    KAUST Repository

    Johansen, Kasper

    2018-04-18

    Unmanned aerial vehicles (UAV) provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e. tree crown perimeter, width, height, area and Plant Projective Cover (PPC), was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m2, and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV based approach for larger orchards. The different flying heights (i.e. 30, 50 and 70 m) produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

  19. A linear model to predict with a multi-spectral radiometer the amount of nitrogen in winter wheat

    NARCIS (Netherlands)

    Reyniers, M.; Walvoort, D.J.J.; Baardemaaker, De J.

    2006-01-01

    The objective was to develop an optimal vegetation index (VIopt) to predict with a multi-spectral radiometer nitrogen in wheat crop (kg[N] ha-1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are

  20. Multi-Spectral Remote Sensing of Phytoplankton Pigment Absorption Properties in Cyanobacteria Bloom Waters: A Regional Example in the Western Basin of Lake Erie

    Directory of Open Access Journals (Sweden)

    Guoqing Wang

    2017-12-01

    Full Text Available Phytoplankton pigments absorb sunlight for photosynthesis, protect the chloroplast from damage caused by excess light energy, and influence the color of the water. Some pigments act as bio-markers and are important for separation of phytoplankton functional types. Among many efforts that have been made to obtain information on phytoplankton pigments from bio-optical properties, Gaussian curves decomposed from phytoplankton absorption spectrum have been used to represent the light absorption of different pigments. We incorporated the Gaussian scheme into a semi-analytical model and obtained the Gaussian curves from remote sensing reflectance. In this study, a series of sensitivity tests were conducted to explore the potential of obtaining the Gaussian curves from multi-spectral satellite remote sensing. Results showed that the Gaussian curves can be retrieved with 35% or less mean unbiased absolute percentage differences from MEdium Resolution Imaging Spectrometer (MERIS and Moderate Resolution Imaging Spectroradiometer (MODIS-like sensors. Further, using Lake Erie as an example, the spatial distribution of chlorophyll a and phycocyanin concentrations were obtained from the Gaussian curves and used as metrics for the spatial extent of an intense cyanobacterial bloom occurred in Lake Erie in 2014. The seasonal variations of Gaussian absorption properties in 2011 were further obtained from MERIS imagery. This study shows that it is feasible to obtain Gaussian curves from multi-spectral satellite remote sensing data, and the obtained chlorophyll a and phycocyanin concentrations from these Gaussian peak heights demonstrated potential application to monitor harmful algal blooms (HABs and identification of phytoplankton groups from satellite ocean color remote sensing semi-analytically.

  1. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  2. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  3. Interaction of the minocycline with extracelluar protein and intracellular protein by multi-spectral techniques and molecular docking

    Science.gov (United States)

    Fang, Qing; Wang, Yirun; Hu, Taoying; Liu, Ying

    2017-02-01

    The interaction of minocyeline (MNC) with extracelluar protein (lysozyme, LYSO) or intracellular protein (bovine hemoglobin, BHb) was investigated using multi-spectral techniques and molecular docking in vitro. Fluorescence studies suggested that MNC quenched LYSO/BHb fluorescence in a static mode with binding constants of 2.01 and 0.26 × 104 L•mol-1 at 298 K, respectively. The LYZO-MNC system was more easily influenced by temperature (298 and 310 K) than the BHb-MNC system. The thermodynamic parameters demonstrated that hydrogen bonds and van der Waals forces played the major role in the binding process. Based on the Förster theory of nonradiative energy transfer, the binding distances between MNC and the inner tryptophan residues of LYSO and BHb were calculated to be 4.34 and 3.49 nm, respectively. Furthermore, circular dichroism spectra (CD), Fourier transforms infrared (FTIR), UV-vis, and three-dimensional fluorescence spectra results indicated the secondary structures of LYSO and BHb were partially destroyed by MNC with the α-helix percentage of LYZO-MNC increased (17.8-28.6%) while that of BHb-MNC was decreased (41.6-39.6%). UV-vis spectral results showed these binding interactions could cause conformational and some micro-environmental changes of LYSO and BHb. In accordance with the results of molecular docking, In LYZO-MNC system, MNC was mainly bound in the active site hinge region where Trp-62 and Trp-63 are located, and in MNC-BHb system, MNC was close to the subunit α 1 of BHb, molecular docking analysis supported the thermodynamic results well. The work contributes to clarify the mechanism of MNC with two proteins at molecular level.

  4. The multi-spectral line-polarization MSE system on Alcator C-Mod

    International Nuclear Information System (INIS)

    Mumgaard, R. T.; Khoury, M.; Scott, S. D.

    2016-01-01

    A multi-spectral line-polarization motional Stark effect (MSE-MSLP) diagnostic has been developed for the Alcator C-Mod tokamak wherein the Stokes vector is measured in multiple wavelength bands simultaneously on the same sightline to enable better polarized background subtraction. A ten-sightline, four wavelength MSE-MSLP detector system was designed, constructed, and qualified. This system consists of a high-throughput polychromator for each sightline designed to provide large étendue and precise spectral filtering in a cost-effective manner. Each polychromator utilizes four narrow bandpass interference filters and four custom large diameter avalanche photodiode detectors. Two filters collect light to the red and blue of the MSE emission spectrum while the remaining two filters collect the beam pi and sigma emission generated at the same viewing volume. The filter wavelengths are temperature tuned using custom ovens in an automated manner. All system functions are remote controllable and the system can be easily retrofitted to existing single-wavelength line-polarization MSE systems.

  5. The multi-spectral line-polarization MSE system on Alcator C-Mod

    Energy Technology Data Exchange (ETDEWEB)

    Mumgaard, R. T., E-mail: mumgaard@psfc.mit.edu; Khoury, M. [Plasma Science and Fusion Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Scott, S. D. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08540 (United States)

    2016-11-15

    A multi-spectral line-polarization motional Stark effect (MSE-MSLP) diagnostic has been developed for the Alcator C-Mod tokamak wherein the Stokes vector is measured in multiple wavelength bands simultaneously on the same sightline to enable better polarized background subtraction. A ten-sightline, four wavelength MSE-MSLP detector system was designed, constructed, and qualified. This system consists of a high-throughput polychromator for each sightline designed to provide large étendue and precise spectral filtering in a cost-effective manner. Each polychromator utilizes four narrow bandpass interference filters and four custom large diameter avalanche photodiode detectors. Two filters collect light to the red and blue of the MSE emission spectrum while the remaining two filters collect the beam pi and sigma emission generated at the same viewing volume. The filter wavelengths are temperature tuned using custom ovens in an automated manner. All system functions are remote controllable and the system can be easily retrofitted to existing single-wavelength line-polarization MSE systems.

  6. Image sequence analysis

    CERN Document Server

    1981-01-01

    The processing of image sequences has a broad spectrum of important applica­ tions including target tracking, robot navigation, bandwidth compression of TV conferencing video signals, studying the motion of biological cells using microcinematography, cloud tracking, and highway traffic monitoring. Image sequence processing involves a large amount of data. However, because of the progress in computer, LSI, and VLSI technologies, we have now reached a stage when many useful processing tasks can be done in a reasonable amount of time. As a result, research and development activities in image sequence analysis have recently been growing at a rapid pace. An IEEE Computer Society Workshop on Computer Analysis of Time-Varying Imagery was held in Philadelphia, April 5-6, 1979. A related special issue of the IEEE Transactions on Pattern Anal­ ysis and Machine Intelligence was published in November 1980. The IEEE Com­ puter magazine has also published a special issue on the subject in 1981. The purpose of this book ...

  7. Fluorescence In Situ Hybridization (FISH Signal Analysis Using Automated Generated Projection Images

    Directory of Open Access Journals (Sweden)

    Xingwei Wang

    2012-01-01

    Full Text Available Fluorescence in situ hybridization (FISH tests provide promising molecular imaging biomarkers to more accurately and reliably detect and diagnose cancers and genetic disorders. Since current manual FISH signal analysis is low-efficient and inconsistent, which limits its clinical utility, developing automated FISH image scanning systems and computer-aided detection (CAD schemes has been attracting research interests. To acquire high-resolution FISH images in a multi-spectral scanning mode, a huge amount of image data with the stack of the multiple three-dimensional (3-D image slices is generated from a single specimen. Automated preprocessing these scanned images to eliminate the non-useful and redundant data is important to make the automated FISH tests acceptable in clinical applications. In this study, a dual-detector fluorescence image scanning system was applied to scan four specimen slides with FISH-probed chromosome X. A CAD scheme was developed to detect analyzable interphase cells and map the multiple imaging slices recorded FISH-probed signals into the 2-D projection images. CAD scheme was then applied to each projection image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm, identify FISH-probed signals using a top-hat transform, and compute the ratios between the normal and abnormal cells. To assess CAD performance, the FISH-probed signals were also independently visually detected by an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots in four testing samples. The study demonstrated the feasibility of automated FISH signal analysis that applying a CAD scheme to the automated generated 2-D projection images.

  8. 50th Anniversary Celebration: 46th Sagamore Army Materials Research Conference on Advances and Needs in Multi-Spectral Transparent Materials Technology

    National Research Council Canada - National Science Library

    Sands, James M; McCauley, James W

    2008-01-01

    ... technology issues of critical importance to the U.S. Army community. The 46th Sagamore Army Materials Research Conference continued this tradition with a focus on Advances and Needs in Multi-Spectral Transparent Materials Technology...

  9. Medical image registration for analysis

    International Nuclear Information System (INIS)

    Petrovic, V.

    2006-01-01

    Full text: Image registration techniques represent a rich family of image processing and analysis tools that aim to provide spatial correspondences across sets of medical images of similar and disparate anatomies and modalities. Image registration is a fundamental and usually the first step in medical image analysis and this paper presents a number of advanced techniques as well as demonstrates some of the advanced medical image analysis techniques they make possible. A number of both rigid and non-rigid medical image alignment algorithms of equivalent and merely consistent anatomical structures respectively are presented. The algorithms are compared in terms of their practical aims, inputs, computational complexity and level of operator (e.g. diagnostician) interaction. In particular, the focus of the methods discussion is placed on the applications and practical benefits of medical image registration. Results of medical image registration on a number of different imaging modalities and anatomies are presented demonstrating the accuracy and robustness of their application. Medical image registration is quickly becoming ubiquitous in medical imaging departments with the results of such algorithms increasingly used in complex medical image analysis and diagnostics. This paper aims to demonstrate at least part of the reason why

  10. Quantitative analysis of receptor imaging

    International Nuclear Information System (INIS)

    Fu Zhanli; Wang Rongfu

    2004-01-01

    Model-based methods for quantitative analysis of receptor imaging, including kinetic, graphical and equilibrium methods, are introduced in detail. Some technical problem facing quantitative analysis of receptor imaging, such as the correction for in vivo metabolism of the tracer and the radioactivity contribution from blood volume within ROI, and the estimation of the nondisplaceable ligand concentration, is also reviewed briefly

  11. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  12. Hyperspectral image analysis. A tutorial

    DEFF Research Database (Denmark)

    Amigo Rubio, Jose Manuel; Babamoradi, Hamid; Elcoroaristizabal Martin, Saioa

    2015-01-01

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processi...... to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case....... will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology...

  13. Hyperspectral image analysis. A tutorial

    International Nuclear Information System (INIS)

    Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa

    2015-01-01

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. - Highlights: • Comprehensive tutorial of Hyperspectral Image analysis. • Hierarchical discrimination of six classes of plastics containing flame retardant. • Step by step guidelines to perform class-modeling on hyperspectral images. • Fusion of multivariate data analysis and digital image processing methods. • Promising methodology for real-time detection of plastics containing flame retardant.

  14. Stochastic geometry for image analysis

    CERN Document Server

    Descombes, Xavier

    2013-01-01

    This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are  described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed.  Numerous applications, covering remote sensing images, biological and medical imaging, are detailed.  This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

  15. QUANTIFICATION OF BIOFILMS IN MULTI-SPECTRAL DIGITAL1 VOLUMES FROM CONFOCAL LASER-SCANNING MICROSCOPES

    Directory of Open Access Journals (Sweden)

    Karsten Rodenacker

    2011-05-01

    Full Text Available Populations of bacteria in sludge flocs and biofilm marked by fluorescence marked with fluorescent probes are digitised with a confocal laser scanning microscope. These data are used to analyse the microbial community structure, to obtain information on the localisation of specific bacterial groups and to examine gene expression. This information is urgently required for an in-depth understanding of the function and, more generally, the microbial ecology of biofilms. Methods derived from quantitative image analysis are applied to digitised data from confocal laser scanning microscopes to obtain quantitative descriptions of volumetric, topological (and topographical properties of different compartments of the components under research. In addition to free-moving flocs, also biofilms attached to a substratum in an experimental environment are analysed. Growth form as well as interaction of components are quantitatively described. Classical measurements of volume and intensity (shape, distribution and distance dependent interaction measurements using methods from mathematical morphology are performed. Mainly image (volume processing methods are outlined. Segmented volumes are globally and individually (in terms of 3Dconnected components measured and used for distance mapping transform as well as for estimation of geodesic distances from the substrate. All transformations are applied on the 3D data set. Resulting distance distributions are quantified and related to information on the identity and activity of the probe-identified bacteria.

  16. Multimodality image analysis work station

    International Nuclear Information System (INIS)

    Ratib, O.; Huang, H.K.

    1989-01-01

    The goal of this project is to design and implement a PACS (picture archiving and communication system) workstation for quantitative analysis of multimodality images. The Macintosh II personal computer was selected for its friendly user interface, its popularity among the academic and medical community, and its low cost. The Macintosh operates as a stand alone workstation where images are imported from a central PACS server through a standard Ethernet network and saved on a local magnetic or optical disk. A video digitizer board allows for direct acquisition of images from sonograms or from digitized cine angiograms. The authors have focused their project on the exploration of new means of communicating quantitative data and information through the use of an interactive and symbolic user interface. The software developed includes a variety of image analysis, algorithms for digitized angiograms, sonograms, scintigraphic images, MR images, and CT scans

  17. Using RPAS Multi-Spectral Imagery to Characterise Vigour, Leaf Development, Yield Components and Berry Composition Variability within a Vineyard

    Directory of Open Access Journals (Sweden)

    Clara Rey-Caramés

    2015-10-01

    Full Text Available Implementation of precision viticulture techniques requires the use of emerging sensing technologies to assess the vineyard spatial variability. This work shows the capability of multispectral imagery acquired from a remotely piloted aerial system (RPAS, and the derived spectral indices to assess the vegetative, productive, and berry composition spatial variability within a vineyard (Vitis vinifera L.. Multi-spectral imagery of 17 cm spatial resolution was acquired using a RPAS. Classical vegetation spectral indices and two newly defined normalised indices, NVI1 = (R802 − R531/(R802 + R531 and NVI2 = (R802 − R570/(R802 + R570, were computed. Their spatial distribution and relationships with grapevine vegetative, yield, and berry composition parameters were studied. Most of the spectral indices and field data varied spatially within the vineyard, as showed through the variogram parameters. While the correlations were significant but moderate among the spectral indices and the field variables, the kappa index showed that the spatial pattern of the spectral indices agreed with that of the vegetative variables (0.38–0.70 and mean cluster weight (0.40. These results proved the utility of the multi-spectral imagery acquired from a RPAS to delineate homogeneous zones within the vineyard, allowing the grapegrower to carry out a specific management of each subarea.

  18. CONTEXT BASED FOOD IMAGE ANALYSIS

    OpenAIRE

    He, Ye; Xu, Chang; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

    2013-01-01

    We are developing a dietary assessment system that records daily food intake through the use of food images. Recognizing food in an image is difficult due to large visual variance with respect to eating or preparation conditions. This task becomes even more challenging when different foods have similar visual appearance. In this paper we propose to incorporate two types of contextual dietary information, food co-occurrence patterns and personalized learning models, in food image analysis to r...

  19. Multispectral analysis of multimodal images

    Energy Technology Data Exchange (ETDEWEB)

    Kvinnsland, Yngve; Brekke, Njaal (Dept. of Surgical Sciences, Univ. of Bergen, Bergen (Norway)); Taxt, Torfinn M.; Gruener, Renate (Dept. of Biomedicine, Univ. of Bergen, Bergen (Norway))

    2009-02-15

    An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. Materials and methods. We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. Results. The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentation that seem to be sensible. Discussion. The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

  20. Imaging mass spectrometry statistical analysis.

    Science.gov (United States)

    Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A

    2012-08-30

    Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. UV imaging in pharmaceutical analysis

    DEFF Research Database (Denmark)

    Østergaard, Jesper

    2018-01-01

    UV imaging provides spatially and temporally resolved absorbance measurements, which are highly useful in pharmaceutical analysis. Commercial UV imaging instrumentation was originally developed as a detector for separation sciences, but the main use is in the area of in vitro dissolution...

  2. Compact Micro-Imaging Spectrometer (CMIS): Investigation of Imaging Spectroscopy and Its Application to Mars Geology and Astrobiology

    Science.gov (United States)

    Staten, Paul W.

    2005-01-01

    Future missions to Mars will attempt to answer questions about Mars' geological and biological history. The goal of the CMIS project is to design, construct, and test a capable, multi-spectral micro-imaging spectrometer use in such missions. A breadboard instrument has been constructed with a micro-imaging camera and Several multi-wavelength LED illumination rings. Test samples have been chosen for their interest to spectroscopists, geologists and astrobiologists. Preliminary analysis has demonstrated the advantages of isotropic illumination and micro-imaging spectroscopy over spot spectroscopy.

  3. Methods in quantitative image analysis.

    Science.gov (United States)

    Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

    1996-05-01

    The main steps of image analysis are image capturing, image storage (compression), correcting imaging defects (e.g. non-uniform illumination, electronic-noise, glare effect), image enhancement, segmentation of objects in the image and image measurements. Digitisation is made by a camera. The most modern types include a frame-grabber, converting the analog-to-digital signal into digital (numerical) information. The numerical information consists of the grey values describing the brightness of every point within the image, named a pixel. The information is stored in bits. Eight bits are summarised in one byte. Therefore, grey values can have a value between 0 and 256 (2(8)). The human eye seems to be quite content with a display of 5-bit images (corresponding to 64 different grey values). In a digitised image, the pixel grey values can vary within regions that are uniform in the original scene: the image is noisy. The noise is mainly manifested in the background of the image. For an optimal discrimination between different objects or features in an image, uniformity of illumination in the whole image is required. These defects can be minimised by shading correction [subtraction of a background (white) image from the original image, pixel per pixel, or division of the original image by the background image]. The brightness of an image represented by its grey values can be analysed for every single pixel or for a group of pixels. The most frequently used pixel-based image descriptors are optical density, integrated optical density, the histogram of the grey values, mean grey value and entropy. The distribution of the grey values existing within an image is one of the most important characteristics of the image. However, the histogram gives no information about the texture of the image. The simplest way to improve the contrast of an image is to expand the brightness scale by spreading the histogram out to the full available range. Rules for transforming the grey value

  4. Wide-band IR imaging in the NIR-MIR-FIR regions for in situ analysis of frescoes

    Science.gov (United States)

    Daffara, C.; Pezzati, L.; Ambrosini, D.; Paoletti, D.; Di Biase, R.; Mariotti, P. I.; Frosinini, C.

    2011-06-01

    Imaging methods offer several advantages in the field of conservation allowing to perform non-invasive inspection of works of art. In particular, non-invasive techniques based on imaging in different infrared (IR) regions are widely used for the investigation of paintings. Using radiation beyond the visible range, different characteristics of the inspected artwork may be revealed according to the bandwidth acquired. In this paper we present the recent results of a joint project among the two research institutes DIMEG and CNR-INO, and the restoration facility Opificio delle Pietre Dure, concerning the wide-band integration of IR imaging techniques, in the spectral ranges NIR 0.8-2.5 μm, MIR 3-5 μm, and FIR 8-12 μm, for in situ analysis of artworks. A joint, multi-mode use of reflection and thermal bands is proposed for the diagnostics of mural paintings, and it is demonstrated to be an effective tool in inspecting the layered structure. High resolution IR reflectography and, to a greater extent, IR imaging in the 3-5 μm band, are effectively used to characterize the superficial layer of the fresco and to analyze the stratigraphy of different pictorial layers. IR thermography in the 8-12 μm band is used to characterize the support deep structure. The integration of all the data provides a multi- layered and multi-spectral representation of the fresco that yields a comprehensive analysis.

  5. Image formation and image analysis in electron microscopy

    International Nuclear Information System (INIS)

    Heel, M. van.

    1981-01-01

    This thesis covers various aspects of image formation and image analysis in electron microscopy. The imaging of relatively strong objects in partially coherent illumination, the coherence properties of thermionic emission sources and the detection of objects in quantum noise limited images are considered. IMAGIC, a fast, flexible and friendly image analysis software package is described. Intelligent averaging of molecular images is discussed. (C.F.)

  6. Image analysis enhancement and interpretation

    International Nuclear Information System (INIS)

    Glauert, A.M.

    1978-01-01

    The necessary practical and mathematical background are provided for the analysis of an electron microscope image in order to extract the maximum amount of structural information. Instrumental methods of image enhancement are described, including the use of the energy-selecting electron microscope and the scanning transmission electron microscope. The problems of image interpretation are considered with particular reference to the limitations imposed by radiation damage and specimen thickness. A brief survey is given of the methods for producing a three-dimensional structure from a series of two-dimensional projections, although emphasis is really given on the analysis, processing and interpretation of the two-dimensional projection of a structure. (Auth.)

  7. Image Analysis of Eccentric Photorefraction

    Directory of Open Access Journals (Sweden)

    J. Dušek

    2004-01-01

    Full Text Available This article deals with image and data analysis of the recorded video-sequences of strabistic infants. It describes a unique noninvasive measuring system based on two measuring methods (position of I. Purkynje image with relation to the centre of the lens and eccentric photorefraction for infants. The whole process is divided into three steps. The aim of the first step is to obtain video sequences on our special system (Eye Movement Analyser. Image analysis of the recorded sequences is performed in order to obtain curves of basic eye reactions (accommodation and convergence. The last step is to calibrate of these curves to corresponding units (diopter and degrees of movement.

  8. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    This book is a result of a collaboration between DTU Informatics at the Technical University of Denmark and the Laboratory of Computer Vision and Media Technology at Aalborg University. It is partly based on the book ”Image and Video Processing”, second edition by Thomas Moeslund. The aim...... of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  9. Shape analysis in medical image analysis

    CERN Document Server

    Tavares, João

    2014-01-01

    This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...

  10. Artificial intelligence and medical imaging. Expert systems and image analysis

    International Nuclear Information System (INIS)

    Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

    1987-01-01

    This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

  11. Evaluation of non-invasive multispectral imaging as a tool for measuring the effect of systemic therapy in Kaposi sarcoma.

    Directory of Open Access Journals (Sweden)

    Jana M Kainerstorfer

    Full Text Available Diffuse multi-spectral imaging has been evaluated as a potential non-invasive marker of tumor response. Multi-spectral images of Kaposi sarcoma skin lesions were taken over the course of treatment, and blood volume and oxygenation concentration maps were obtained through principal component analysis (PCA of the data. These images were compared with clinical and pathological responses determined by conventional means. We demonstrate that cutaneous lesions have increased blood volume concentration and that changes in this parameter are a reliable indicator of treatment efficacy, differentiating responders and non-responders. Blood volume decreased by at least 20% in all lesions that responded by clinical criteria and increased in the two lesions that did not respond clinically. Responses as assessed by multi-spectral imaging also generally correlated with overall patient clinical response assessment, were often detectable earlier in the course of therapy, and are less subject to observer variability than conventional clinical assessment. Tissue oxygenation was more variable, with lesions often showing decreased oxygenation in the center surrounded by a zone of increased oxygenation. This technique could potentially be a clinically useful supplement to existing response assessment in KS, providing an early, quantitative, and non-invasive marker of treatment effect.

  12. Errors from Image Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wood, William Monford [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-02-23

    Presenting a systematic study of the standard analysis of rod-pinch radiographs for obtaining quantitative measurements of areal mass densities, and making suggestions for improving the methodology of obtaining quantitative information from radiographed objects.

  13. Pocket pumped image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kotov, I.V., E-mail: kotov@bnl.gov [Brookhaven National Laboratory, Upton, NY 11973 (United States); O' Connor, P. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Murray, N. [Centre for Electronic Imaging, Open University, Milton Keynes, MK7 6AA (United Kingdom)

    2015-07-01

    The pocket pumping technique is used to detect small electron trap sites. These traps, if present, degrade CCD charge transfer efficiency. To reveal traps in the active area, a CCD is illuminated with a flat field and, before image is read out, accumulated charges are moved back and forth number of times in parallel direction. As charges are moved over a trap, an electron is removed from the original pocket and re-emitted in the following pocket. As process repeats one pocket gets depleted and the neighboring pocket gets excess of charges. As a result a “dipole” signal appears on the otherwise flat background level. The amplitude of the dipole signal depends on the trap pumping efficiency. This paper is focused on trap identification technique and particularly on new methods developed for this purpose. The sensor with bad segments was deliberately chosen for algorithms development and to demonstrate sensitivity and power of new methods in uncovering sensor defects.

  14. Performance of the Multi-Spectral Solar Telescope Array. III - Optical characteristics of the Ritchey-Chretien and Cassegrain telescopes

    Science.gov (United States)

    Hoover, Richard B.; Baker, Phillip C.; Hadaway, James B.; Johnson, R. B.; Peterson, Cynthia; Gabardi, David R.; Walker, Arthur B., Jr.; Lindblom, J. F.; Deforest, Craig; O'Neal, R. H.

    1991-12-01

    The Multi-Spectral Solar Telescope Array (MSSTA), which is a sounding-rocket-borne observatory for investigating the sun in the soft X-ray/EUV and FUV regimes of the electromagnetic spectrum, utilizes single reflection multilayer coated Herschelian telescopes for wavelengths below 100 A, and five doubly reflecting multilayer coated Ritchey-Chretien and two Cassegrain telescopes for selected wavelengths in the EUV region between 100 and 1000 A. The paper discusses the interferometric alignment, testing, focusing, visible light testing, and optical performance characteristics of the Ritchey-Chretien and Cassegrain telescopes of MSSTA. A schematic diagram of the MSSTA Ritchey-Chretien telescope is presented together with diagrams of the system autocollimation testing.

  15. A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

    Science.gov (United States)

    Selkowitz, D.J.

    2010-01-01

    Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets

  16. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  17. Signal and image multiresolution analysis

    CERN Document Server

    Ouahabi, Abdelialil

    2012-01-01

    Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc.This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing

  18. Teaching image analysis at DIKU

    DEFF Research Database (Denmark)

    Johansen, Peter

    2010-01-01

    The early development of computer vision at Department of Computer Science at University of Copenhagen (DIKU) is briefly described. The different disciplines in computer vision are introduced, and the principles for teaching two courses, an image analysis course, and a robot lab class are outlined....

  19. Astronomical Image and Data Analysis

    CERN Document Server

    Starck, J.-L

    2006-01-01

    With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with to...

  20. Image analysis for material characterisation

    Science.gov (United States)

    Livens, Stefan

    In this thesis, a number of image analysis methods are presented as solutions to two applications concerning the characterisation of materials. Firstly, we deal with the characterisation of corrosion images, which is handled using a multiscale texture analysis method based on wavelets. We propose a feature transformation that deals with the problem of rotation invariance. Classification is performed with a Learning Vector Quantisation neural network and with combination of outputs. In an experiment, 86,2% of the images showing either pit formation or cracking, are correctly classified. Secondly, we develop an automatic system for the characterisation of silver halide microcrystals. These are flat crystals with a triangular or hexagonal base and a thickness in the 100 to 200 nm range. A light microscope is used to image them. A novel segmentation method is proposed, which allows to separate agglomerated crystals. For the measurement of shape, the ratio between the largest and the smallest radius yields the best results. The thickness measurement is based on the interference colours that appear for light reflected at the crystals. The mean colour of different thickness populations is determined, from which a calibration curve is derived. With this, the thickness of new populations can be determined accurately.

  1. Monitoring of Calcite Precipitation in Hardwater Lakes with Multi-Spectral Remote Sensing Archives

    Directory of Open Access Journals (Sweden)

    Iris Heine

    2017-01-01

    Full Text Available Calcite precipitation is a common phenomenon in calcium-rich hardwater lakes during spring and summer, but the number and spatial distribution of lakes with calcite precipitation is unknown. This paper presents a remote sensing based method to observe calcite precipitation over large areas, which are an important prerequisite for a systematic monitoring and evaluation of restoration measurements. We use globally archived satellite remote sensing data for a retrospective systematic assessment of past multi-temporal calcite precipitation events. The database of this study consists of 205 data sets that comprise freely available Landsat and Sentinel 2 data acquired between 1998 and 2015 covering the Northeast German Plain. Calcite precipitation is automatically identified using the green spectra and the metric BGR area, the triangular area between the blue, green and red reflectance value. The validation is based on field measurements of CaCO3 concentrations at three selected lakes, Feldberger Haussee, Breiter Luzin and Schmaler Luzin. The classification accuracy (0.88 is highest for calcite concentrations ≥0.7 mg/L. False negative results are caused by the choice of a conservative classification threshold. False positive results can be explained by already increased calcite concentrations. We successfully transferred the developed method to 21 other hardwater lakes in Northeast Germany. The average duration of lakes with regular calcite precipitation is 37 days. The frequency of calcite precipitation reaches from single time detections up to detections nearly every year. False negative classification results and gaps in Landsat time series reduce the accuracy of frequency and duration monitoring, but in future the image density will increase by acquisitions of Sentinel-2a (and 2b. Our study tested successfully the transfer of the classification approach to Sentinel-2 images. Our study shows that 15 of the 24 lakes have at least one phase of

  2. Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

    Directory of Open Access Journals (Sweden)

    D. Martynenko

    2010-11-01

    Full Text Available An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo.

    The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008 there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper.

    The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to

  3. Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN).

    Science.gov (United States)

    Iqbal, Sajid; Ghani, M Usman; Saba, Tanzila; Rehman, Amjad

    2018-04-01

    A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. © 2018 Wiley Periodicals, Inc.

  4. Planning applications in image analysis

    Science.gov (United States)

    Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.

    1994-01-01

    We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

  5. Quantitative image analysis of synovial tissue

    NARCIS (Netherlands)

    van der Hall, Pascal O.; Kraan, Maarten C.; Tak, Paul Peter

    2007-01-01

    Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the

  6. Mesh Processing in Medical Image Analysis

    DEFF Research Database (Denmark)

    The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....

  7. Automated image analysis of uterine cervical images

    Science.gov (United States)

    Li, Wenjing; Gu, Jia; Ferris, Daron; Poirson, Allen

    2007-03-01

    Cervical Cancer is the second most common cancer among women worldwide and the leading cause of cancer mortality of women in developing countries. If detected early and treated adequately, cervical cancer can be virtually prevented. Cervical precursor lesions and invasive cancer exhibit certain morphologic features that can be identified during a visual inspection exam. Digital imaging technologies allow us to assist the physician with a Computer-Aided Diagnosis (CAD) system. In colposcopy, epithelium that turns white after application of acetic acid is called acetowhite epithelium. Acetowhite epithelium is one of the major diagnostic features observed in detecting cancer and pre-cancerous regions. Automatic extraction of acetowhite regions from cervical images has been a challenging task due to specular reflection, various illumination conditions, and most importantly, large intra-patient variation. This paper presents a multi-step acetowhite region detection system to analyze the acetowhite lesions in cervical images automatically. First, the system calibrates the color of the cervical images to be independent of screening devices. Second, the anatomy of the uterine cervix is analyzed in terms of cervix region, external os region, columnar region, and squamous region. Third, the squamous region is further analyzed and subregions based on three levels of acetowhite are identified. The extracted acetowhite regions are accompanied by color scores to indicate the different levels of acetowhite. The system has been evaluated by 40 human subjects' data and demonstrates high correlation with experts' annotations.

  8. Detection of Lettuce Discoloration Using Hyperspectral Reflectance Imaging.

    Science.gov (United States)

    Mo, Changyeun; Kim, Giyoung; Lim, Jongguk; Kim, Moon S; Cho, Hyunjeong; Cho, Byoung-Kwan

    2015-11-20

    Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to discrimination between sound and discolored lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectral reflectance images obtained in the 400-1000 nm wavelength range. The optimal wavebands for discriminating between discolored and sound lettuce surfaces were determined using one-way analysis of variance. Multi-spectral imaging algorithms developed using ratio and subtraction functions resulted in enhanced classification accuracy of above 99.9% for discolored and sound areas on both adaxial and abaxial lettuce surfaces. Ratio imaging (RI) and subtraction imaging (SI) algorithms at wavelengths of 552/701 nm and 557-701 nm, respectively, exhibited better classification performances compared to results obtained for all possible two-waveband combinations. These results suggest that hyperspectral reflectance imaging techniques can potentially be used to discriminate between discolored and sound fresh-cut lettuce.

  9. Information Retrieval from SAGE II and MFRSR Multi-Spectral Extinction Measurements

    Science.gov (United States)

    Lacis, Andrew A.; Hansen, James E. (Technical Monitor)

    2001-01-01

    Direct beam spectral extinction measurements of solar radiation contain important information on atmospheric composition in a form that is essentially free from multiple scattering contributions that otherwise tend to complicate the data analysis and information retrieval. Such direct beam extinction measurements are available from the solar occultation satellite-based measurements made by the Stratospheric and Aerosol Gas Experiment (SAGE II) instrument and by ground-based Multi-Filter Shadowband Radiometers (MFRSRs). The SAGE II data provide cross-sectional slices of the atmosphere twice per orbit at seven wavelengths between 385 and 1020 nm with approximately 1 km vertical resolution, while the MFRSR data provide atmospheric column measurements at six wavelengths between 415 and 940 nm but at one minute time intervals. We apply the same retrieval technique of simultaneous least-squares fit to the observed spectral extinctions to retrieve aerosol optical depth, effective radius and variance, and ozone, nitrogen dioxide, and water vapor amounts from the SAGE II and MFRSR measurements. The retrieval technique utilizes a physical model approach based on laboratory measurements of ozone and nitrogen dioxide extinction, line-by-line and numerical k-distribution calculations for water vapor absorption, and Mie scattering constraints on aerosol spectral extinction properties. The SAGE II measurements have the advantage of being self-calibrating in that deep space provides an effective zero point for the relative spectral extinctions. The MFRSR measurements require periodic clear-day Langley regression calibration events to maintain accurate knowledge of instrument calibration.

  10. Image Analysis for X-ray Imaging of Food

    DEFF Research Database (Denmark)

    Einarsdottir, Hildur

    for quality and safety evaluation of food products. In this effort the fields of statistics, image analysis and statistical learning are combined, to provide analytical tools for determining the aforementioned food traits. The work demonstrated includes a quantitative analysis of heat induced changes......X-ray imaging systems are increasingly used for quality and safety evaluation both within food science and production. They offer non-invasive and nondestructive penetration capabilities to image the inside of food. This thesis presents applications of a novel grating-based X-ray imaging technique...... and defect detection in food. Compared to the complex three dimensional analysis of microstructure, here two dimensional images are considered, making the method applicable for an industrial setting. The advantages obtained by grating-based imaging are compared to conventional X-ray imaging, for both foreign...

  11. Ultrasonic image analysis and image-guided interventions.

    Science.gov (United States)

    Noble, J Alison; Navab, Nassir; Becher, H

    2011-08-06

    The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

  12. Vaccine Images on Twitter: Analysis of What Images are Shared.

    Science.gov (United States)

    Chen, Tao; Dredze, Mark

    2018-04-03

    Visual imagery plays a key role in health communication; however, there is little understanding of what aspects of vaccine-related images make them effective communication aids. Twitter, a popular venue for discussions related to vaccination, provides numerous images that are shared with tweets. The objectives of this study were to understand how images are used in vaccine-related tweets and provide guidance with respect to the characteristics of vaccine-related images that correlate with the higher likelihood of being retweeted. We collected more than one million vaccine image messages from Twitter and characterized various properties of these images using automated image analytics. We fit a logistic regression model to predict whether or not a vaccine image tweet was retweeted, thus identifying characteristics that correlate with a higher likelihood of being shared. For comparison, we built similar models for the sharing of vaccine news on Facebook and for general image tweets. Most vaccine-related images are duplicates (125,916/237,478; 53.02%) or taken from other sources, not necessarily created by the author of the tweet. Almost half of the images contain embedded text, and many include images of people and syringes. The visual content is highly correlated with a tweet's textual topics. Vaccine image tweets are twice as likely to be shared as nonimage tweets. The sentiment of an image and the objects shown in the image were the predictive factors in determining whether an image was retweeted. We are the first to study vaccine images on Twitter. Our findings suggest future directions for the study and use of vaccine imagery and may inform communication strategies around vaccination. Furthermore, our study demonstrates an effective study methodology for image analysis. ©Tao Chen, Mark Dredze. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.04.2018.

  13. Vaccine Images on Twitter: Analysis of What Images are Shared

    Science.gov (United States)

    Dredze, Mark

    2018-01-01

    Background Visual imagery plays a key role in health communication; however, there is little understanding of what aspects of vaccine-related images make them effective communication aids. Twitter, a popular venue for discussions related to vaccination, provides numerous images that are shared with tweets. Objective The objectives of this study were to understand how images are used in vaccine-related tweets and provide guidance with respect to the characteristics of vaccine-related images that correlate with the higher likelihood of being retweeted. Methods We collected more than one million vaccine image messages from Twitter and characterized various properties of these images using automated image analytics. We fit a logistic regression model to predict whether or not a vaccine image tweet was retweeted, thus identifying characteristics that correlate with a higher likelihood of being shared. For comparison, we built similar models for the sharing of vaccine news on Facebook and for general image tweets. Results Most vaccine-related images are duplicates (125,916/237,478; 53.02%) or taken from other sources, not necessarily created by the author of the tweet. Almost half of the images contain embedded text, and many include images of people and syringes. The visual content is highly correlated with a tweet’s textual topics. Vaccine image tweets are twice as likely to be shared as nonimage tweets. The sentiment of an image and the objects shown in the image were the predictive factors in determining whether an image was retweeted. Conclusions We are the first to study vaccine images on Twitter. Our findings suggest future directions for the study and use of vaccine imagery and may inform communication strategies around vaccination. Furthermore, our study demonstrates an effective study methodology for image analysis. PMID:29615386

  14. Introduction to the Multifractal Analysis of Images

    OpenAIRE

    Lévy Véhel , Jacques

    1998-01-01

    International audience; After a brief review of some classical approaches in image segmentation, the basics of multifractal theory and its application to image analysis are presented. Practical methods for multifractal spectrum estimation are discussed and some experimental results are given.

  15. Tolerance analysis through computational imaging simulations

    Science.gov (United States)

    Birch, Gabriel C.; LaCasse, Charles F.; Stubbs, Jaclynn J.; Dagel, Amber L.; Bradley, Jon

    2017-11-01

    The modeling and simulation of non-traditional imaging systems require holistic consideration of the end-to-end system. We demonstrate this approach through a tolerance analysis of a random scattering lensless imaging system.

  16. Classification of Astaxanthin Colouration of Salmonid Fish using Spectral Imaging and Tricolour Measurement

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht

    capturing, tricolour CIELAB measurement, and manual SalmoFan inspection. Furthermore it was tested whether the best predictions come from measurements of the steak or the fillet of the fish. Methods used for classication were linear discriminant analysis (LDA), quadratic discriminant analysis (QDA......The goal of this study was to investigate if it is possible to differentiate between rainbow trout (Oncorhynchus mykiss) having been fed with natural or synthetic astaxanthin. Three different techniques were used for visual inspection of the surface colour of the fish meat: multi-spectral image...

  17. Similarity analysis between quantum images

    Science.gov (United States)

    Zhou, Ri-Gui; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

    2018-06-01

    Similarity analyses between quantum images are so essential in quantum image processing that it provides fundamental research for the other fields, such as quantum image matching, quantum pattern recognition. In this paper, a quantum scheme based on a novel quantum image representation and quantum amplitude amplification algorithm is proposed. At the end of the paper, three examples and simulation experiments show that the measurement result must be 0 when two images are same, and the measurement result has high probability of being 1 when two images are different.

  18. Image registration with uncertainty analysis

    Science.gov (United States)

    Simonson, Katherine M [Cedar Crest, NM

    2011-03-22

    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  19. Transfer function analysis of radiographic imaging systems

    International Nuclear Information System (INIS)

    Metz, C.E.; Doi, K.

    1979-01-01

    The theoretical and experimental aspects of the techniques of transfer function analysis used in radiographic imaging systems are reviewed. The mathematical principles of transfer function analysis are developed for linear, shift-invariant imaging systems, for the relation between object and image and for the image due to a sinusoidal plane wave object. The other basic mathematical principle discussed is 'Fourier analysis' and its application to an input function. Other aspects of transfer function analysis included are alternative expressions for the 'optical transfer function' of imaging systems and expressions are derived for both serial and parallel transfer image sub-systems. The applications of transfer function analysis to radiographic imaging systems are discussed in relation to the linearisation of the radiographic imaging system, the object, the geometrical unsharpness, the screen-film system unsharpness, other unsharpness effects and finally noise analysis. It is concluded that extensive theoretical, computer simulation and experimental studies have demonstrated that the techniques of transfer function analysis provide an accurate and reliable means for predicting and understanding the effects of various radiographic imaging system components in most practical diagnostic medical imaging situations. (U.K.)

  20. Microscopy image segmentation tool: Robust image data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Valmianski, Ilya, E-mail: ivalmian@ucsd.edu; Monton, Carlos; Schuller, Ivan K. [Department of Physics and Center for Advanced Nanoscience, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093 (United States)

    2014-03-15

    We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

  1. Microscopy image segmentation tool: Robust image data analysis

    Science.gov (United States)

    Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

    2014-03-01

    We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

  2. Microscopy image segmentation tool: Robust image data analysis

    International Nuclear Information System (INIS)

    Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

    2014-01-01

    We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy

  3. Information granules in image histogram analysis.

    Science.gov (United States)

    Wieclawek, Wojciech

    2018-04-01

    A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Analysis of 3-D images

    Science.gov (United States)

    Wani, M. Arif; Batchelor, Bruce G.

    1992-03-01

    Deriving generalized representation of 3-D objects for analysis and recognition is a very difficult task. Three types of representations based on type of an object is used in this paper. Objects which have well-defined geometrical shapes are segmented by using a fast edge region based segmentation technique. The segmented image is represented by plan and elevation of each part of the object if the object parts are symmetrical about their central axis. The plan and elevation concept enables representing and analyzing such objects quickly and efficiently. The second type of representation is used for objects having parts which are not symmetrical about their central axis. The segmented surface patches of such objects are represented by the 3-D boundary and the surface features of each segmented surface. Finally, the third type of representation is used for objects which don't have well-defined geometrical shapes (for example a loaf of bread). These objects are represented and analyzed from its features which are derived using a multiscale contour based technique. Anisotropic Gaussian smoothing technique is introduced to segment the contours at various scales of smoothing. A new merging technique is used which enables getting the current best estimate of break points at each scale. This new technique enables elimination of loss of accuracy of localization effects at coarser scales without using scale space tracking approach.

  5. 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.

  6. Applications of stochastic geometry in image analysis

    NARCIS (Netherlands)

    Lieshout, van M.N.M.; Kendall, W.S.; Molchanov, I.S.

    2009-01-01

    A discussion is given of various stochastic geometry models (random fields, sequential object processes, polygonal field models) which can be used in intermediate and high-level image analysis. Two examples are presented of actual image analysis problems (motion tracking in video,

  7. Solar Image Analysis and Visualization

    CERN Document Server

    Ireland, J

    2009-01-01

    This volume presents a selection of papers on the state of the art of image enhancement, automated feature detection, machine learning, and visualization tools in support of solar physics that focus on the challenges presented by new ground-based and space-based instrumentation. The articles and topics were inspired by the Third Solar Image Processing Workshop, held at Trinity College Dublin, Ireland but contributions from other experts have been included as well. This book is mainly aimed at researchers and graduate students working on image processing and compter vision in astronomy and solar physics.

  8. Multi-Source Image Analysis.

    Science.gov (United States)

    1979-12-01

    These collections were taken to show the advantages made available to the inter- preter. In a military operation, however, often little or no in- situ ...The large body of water labeled "W" on each image represents the Agua Hedionda lagoon. East of the lagoon the area is primarily agricultural with a...power plant located in the southeast corner of the image. West of the Agua Hedionda lagoon is Carlsbad, California. Damp ground is labelled "Dg" on the

  9. Objective analysis of image quality of video image capture systems

    Science.gov (United States)

    Rowberg, Alan H.

    1990-07-01

    As Picture Archiving and Communication System (PACS) technology has matured, video image capture has become a common way of capturing digital images from many modalities. While digital interfaces, such as those which use the ACR/NEMA standard, will become more common in the future, and are preferred because of the accuracy of image transfer, video image capture will be the dominant method in the short term, and may continue to be used for some time because of the low cost and high speed often associated with such devices. Currently, virtually all installed systems use methods of digitizing the video signal that is produced for display on the scanner viewing console itself. A series of digital test images have been developed for display on either a GE CT9800 or a GE Signa MRI scanner. These images have been captured with each of five commercially available image capture systems, and the resultant images digitally transferred on floppy disk to a PC1286 computer containing Optimast' image analysis software. Here the images can be displayed in a comparative manner for visual evaluation, in addition to being analyzed statistically. Each of the images have been designed to support certain tests, including noise, accuracy, linearity, gray scale range, stability, slew rate, and pixel alignment. These image capture systems vary widely in these characteristics, in addition to the presence or absence of other artifacts, such as shading and moire pattern. Other accessories such as video distribution amplifiers and noise filters can also add or modify artifacts seen in the captured images, often giving unusual results. Each image is described, together with the tests which were performed using them. One image contains alternating black and white lines, each one pixel wide, after equilibration strips ten pixels wide. While some systems have a slew rate fast enough to track this correctly, others blur it to an average shade of gray, and do not resolve the lines, or give

  10. Forensic Analysis of Digital Image Tampering

    Science.gov (United States)

    2004-12-01

    analysis of when each method fails, which Chapter 4 discusses. Finally, a test image containing an invisible watermark using LSB steganography is...2.2 – Example of invisible watermark using Steganography Software F5 ............. 8 Figure 2.3 – Example of copy-move image forgery [12...used to embed the hidden watermark is Steganography Software F5 version 11+ discussed in Section 2.2. Original JPEG Image – 580 x 435 – 17.4

  11. Wavefront analysis for plenoptic camera imaging

    International Nuclear Information System (INIS)

    Luan Yin-Sen; Xu Bing; Yang Ping; Tang Guo-Mao

    2017-01-01

    The plenoptic camera is a single lens stereo camera which can retrieve the direction of light rays while detecting their intensity distribution. In this paper, to reveal more truths of plenoptic camera imaging, we present the wavefront analysis for the plenoptic camera imaging from the angle of physical optics but not from the ray tracing model of geometric optics. Specifically, the wavefront imaging model of a plenoptic camera is analyzed and simulated by scalar diffraction theory and the depth estimation is redescribed based on physical optics. We simulate a set of raw plenoptic images of an object scene, thereby validating the analysis and derivations and the difference between the imaging analysis methods based on geometric optics and physical optics are also shown in simulations. (paper)

  12. Breast cancer histopathology image analysis : a review

    NARCIS (Netherlands)

    Veta, M.; Pluim, J.P.W.; Diest, van P.J.; Viergever, M.A.

    2014-01-01

    This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology

  13. Multiplicative calculus in biomedical image analysis

    NARCIS (Netherlands)

    Florack, L.M.J.; Assen, van H.C.

    2011-01-01

    We advocate the use of an alternative calculus in biomedical image analysis, known as multiplicative (a.k.a. non-Newtonian) calculus. It provides a natural framework in problems in which positive images or positive definite matrix fields and positivity preserving operators are of interest. Indeed,

  14. Image analysis in x-ray cinefluorography

    Energy Technology Data Exchange (ETDEWEB)

    Ikuse, J; Yasuhara, H; Sugimoto, H [Toshiba Corp., Kawasaki, Kanagawa (Japan)

    1979-02-01

    For the cinefluorographic image in the cardiovascular diagnostic system, the image quality is evaluated by means of MTF (Modulation Transfer Function), and object contrast by introducing the concept of x-ray spectrum analysis. On the basis of these results, further investigation is made of optimum X-ray exposure factors set for cinefluorography and the cardiovascular diagnostic system.

  15. An Imaging And Graphics Workstation For Image Sequence Analysis

    Science.gov (United States)

    Mostafavi, Hassan

    1990-01-01

    This paper describes an application-specific engineering workstation designed and developed to analyze imagery sequences from a variety of sources. The system combines the software and hardware environment of the modern graphic-oriented workstations with the digital image acquisition, processing and display techniques. The objective is to achieve automation and high throughput for many data reduction tasks involving metric studies of image sequences. The applications of such an automated data reduction tool include analysis of the trajectory and attitude of aircraft, missile, stores and other flying objects in various flight regimes including launch and separation as well as regular flight maneuvers. The workstation can also be used in an on-line or off-line mode to study three-dimensional motion of aircraft models in simulated flight conditions such as wind tunnels. The system's key features are: 1) Acquisition and storage of image sequences by digitizing real-time video or frames from a film strip; 2) computer-controlled movie loop playback, slow motion and freeze frame display combined with digital image sharpening, noise reduction, contrast enhancement and interactive image magnification; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored image sequence; 4) automatic and manual field-of-view and spatial calibration; 5) image sequence data base generation and management, including the measurement data products; 6) off-line analysis software for trajectory plotting and statistical analysis; 7) model-based estimation and tracking of object attitude angles; and 8) interface to a variety of video players and film transport sub-systems.

  16. Multichannel imager for littoral zone characterization

    Science.gov (United States)

    Podobna, Yuliya; Schoonmaker, Jon; Dirbas, Joe; Sofianos, James; Boucher, Cynthia; Gilbert, Gary

    2010-04-01

    This paper describes an approach to utilize a multi-channel, multi-spectral electro-optic (EO) system for littoral zone characterization. Advanced Coherent Technologies, LLC (ACT) presents their EO sensor systems for the surf zone environmental assessment and potential surf zone target detection. Specifically, an approach is presented to determine a Surf Zone Index (SZI) from the multi-spectral EO sensor system. SZI provides a single quantitative value of the surf zone conditions delivering an immediate understanding of the area and an assessment as to how well an airborne optical system might perform in a mine countermeasures (MCM) operation. Utilizing consecutive frames of SZI images, ACT is able to measure variability over time. A surf zone nomograph, which incorporates targets, sensor, and environmental data, including the SZI to determine the environmental impact on system performance, is reviewed in this work. ACT's electro-optical multi-channel, multi-spectral imaging system and test results are presented and discussed.

  17. Facial Image Analysis in Anthropology: A Review

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 49, č. 2 (2011), s. 141-153 ISSN 0323-1119 Institutional support: RVO:67985807 Keywords : face * computer-assisted methods * template matching * geometric morphopetrics * robust image analysis Subject RIV: IN - Informatics, Computer Science

  18. Optimization of shearography image quality analysis

    International Nuclear Information System (INIS)

    Rafhayudi Jamro

    2005-01-01

    Shearography is an optical technique based on speckle pattern to measure the deformation of the object surface in which the fringe pattern is obtained through the correlation analysis from the speckle pattern. Analysis of fringe pattern for engineering application is limited for qualitative measurement. Therefore, for further analysis that lead to qualitative data, series of image processing mechanism are involved. In this paper, the fringe pattern for qualitative analysis is discussed. In principal field of applications is qualitative non-destructive testing such as detecting discontinuity, defect in the material structure, locating fatigue zones and etc and all these required image processing application. In order to performed image optimisation successfully, the noise in the fringe pattern must be minimised and the fringe pattern itself must be maximise. This can be achieved by applying a filtering method with a kernel size ranging from 2 X 2 to 7 X 7 pixels size and also applying equalizer in the image processing. (Author)

  19. Vegetation index analysis of multi-source remote sensing data in coal mine wasteland

    Energy Technology Data Exchange (ETDEWEB)

    Han, Y.X.; Li, M.Z.; Li, D.L. [China Agricultural University, Beijing (China)

    2007-12-15

    Thirty-six soil samples were collected and their hyperspectral data used to calculate vegetation indices such as a normalised difference vegetation index (NDVI) and a difference vegetation index (DVI). These were evaluated for typical surface object features within the wastelands around Haizhou Opencast Coal Mine in Fuxin city. A principal component analysis to the hyperspectral data was performed, and the result showed that the first and the second principal components satisfactorily accounted for the multi-spectral image information. The panchromatic and multi-spectral images of SPOT5 were then merged. The panchromatic image replaced the first principal component to improve spatial resolution of the image. In addition, the multispectral images and the NDVI image were classified into six types using the unsupervised classification method. The linear quantitative models were built up and the highest correlation coefficients were obtained between the hyperspectral vegetation index and the vegetation index data from the SPOT5 image. The results show that the hyperspectral data and remote sensing images can be used for quantitative estimation of soil nutrients in coal mine wasteland. They can also provide large area surface information for fast and effective decision making regarding revegetation and the monitoring of dynamic change.

  20. Structural analysis in medical imaging

    International Nuclear Information System (INIS)

    Dellepiane, S.; Serpico, S.B.; Venzano, L.; Vernazza, G.

    1987-01-01

    The conventional techniques in Pattern Recognition (PR) have been greatly improved by the introduction of Artificial Intelligence (AI) approaches, in particular for knowledge representation, inference mechanism and control structure. The purpose of this paper is to describe an image understanding system, based on the integrated approach (AI - PR), developed in the author's Department to interpret Nuclear Magnetic Resonance (NMR) images. The system is characterized by a heterarchical control structure and a blackboard model for the global data-base. The major aspects of the system are pointed out, with particular reference to segmentation, knowledge representation and error recovery (backtracking). The eye slices obtained in the case of two patients have been analyzed and the related results are discussed

  1. Malware Analysis Using Visualized Image Matrices

    Directory of Open Access Journals (Sweden)

    KyoungSoo Han

    2014-01-01

    Full Text Available This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

  2. Malware analysis using visualized image matrices.

    Science.gov (United States)

    Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

  3. Analysis of Variance in Statistical Image Processing

    Science.gov (United States)

    Kurz, Ludwik; Hafed Benteftifa, M.

    1997-04-01

    A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

  4. Image processing and analysis software development

    International Nuclear Information System (INIS)

    Shahnaz, R.

    1999-01-01

    The work presented in this project is aimed at developing a software 'IMAGE GALLERY' to investigate various image processing and analysis techniques. The work was divided into two parts namely the image processing techniques and pattern recognition, which further comprised of character and face recognition. Various image enhancement techniques including negative imaging, contrast stretching, compression of dynamic, neon, diffuse, emboss etc. have been studied. Segmentation techniques including point detection, line detection, edge detection have been studied. Also some of the smoothing and sharpening filters have been investigated. All these imaging techniques have been implemented in a window based computer program written in Visual Basic Neural network techniques based on Perception model have been applied for face and character recognition. (author)

  5. Breast cancer histopathology image analysis: a review.

    Science.gov (United States)

    Veta, Mitko; Pluim, Josien P W; van Diest, Paul J; Viergever, Max A

    2014-05-01

    This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

  6. Some developments in multivariate image analysis

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    be up to several million. The main MIA tool for exploratory analysis is score density plot – all pixels are projected into principal component space and on the corresponding scores plots are colorized according to their density (how many pixels are crowded in the unit area of the plot). Looking...... for and analyzing patterns on these plots and the original image allow to do interactive analysis, to get some hidden information, build a supervised classification model, and much more. In the present work several alternative methods to original principal component analysis (PCA) for building the projection......Multivariate image analysis (MIA), one of the successful chemometric applications, now is used widely in different areas of science and industry. Introduced in late 80s it has became very popular with hyperspectral imaging, where MIA is one of the most efficient tools for exploratory analysis...

  7. Document image analysis: A primer

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    (1) Typical documents in today's office are computer-generated, but even so, inevitably by different computers and ... different sizes, from a business card to a large engineering drawing. Document analysis ... Whether global or adaptive ...

  8. Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

    Science.gov (United States)

    McClatchy, David M., III; Rizzo, Elizabeth J.; Meganck, Jeff; Kempner, Josh; Vicory, Jared; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.

    2017-12-01

    A multimodal micro-computed tomography (CT) and multi-spectral structured light imaging (SLI) system is introduced and systematically analyzed to test its feasibility to aid in margin delineation during breast conserving surgery (BCS). Phantom analysis of the micro-CT yielded a signal-to-noise ratio of 34, a contrast of 1.64, and a minimum detectable resolution of 240 μm for a 1.2 min scan. The SLI system, spanning wavelengths 490 nm to 800 nm and spatial frequencies up to 1.37 mm-1 , was evaluated with aqueous tissue simulating phantoms having variations in particle size distribution, scatter density, and blood volume fraction. The reduced scattering coefficient, μs\\prime and phase function parameter, γ, were accurately recovered over all wavelengths independent of blood volume fractions from 0% to 4%, assuming a flat sample geometry perpendicular to the imaging plane. The resolution of the optical system was tested with a step phantom, from which the modulation transfer function was calculated yielding a maximum resolution of 3.78 cycles per mm. The three dimensional spatial co-registration between the CT and optical imaging space was tested and shown to be accurate within 0.7 mm. A freshly resected breast specimen, with lobular carcinoma, fibrocystic disease, and adipose, was imaged with the system. The micro-CT provided visualization of the tumor mass and its spiculations, and SLI yielded superficial quantification of light scattering parameters for the malignant and benign tissue types. These results appear to be the first demonstration of SLI combined with standard medical tomography for imaging excised tumor specimens. While further investigations are needed to determine and test the spectral, spatial, and CT features required to classify tissue, this study demonstrates the ability of multimodal CT/SLI to quantify, visualize, and spatially navigate breast tumor specimens, which could potentially aid in the assessment of tumor margin status during

  9. Tasked-based quantification of measurement utility for ex vivo multi-spectral Mueller polarimetry of the uterine cervix

    Science.gov (United States)

    Kupinski, Meredith; Rehbinder, Jean; Haddad, Huda; Deby, Stanislas; Vizet, Jérémy; Teig, Benjamin; Nazac, André; Pierangelo, Angelo; Moreau, François; Novikova, Tatiana

    2017-07-01

    Significant contrast in visible wavelength Mueller matrix images for healthy and pre-cancerous regions of excised cervical tissue is shown. A novel classification algorithm is used to compute a test statistic from a small patient population.

  10. Traffic analysis and control using image processing

    Science.gov (United States)

    Senthilkumar, K.; Ellappan, Vijayan; Arun, A. R.

    2017-11-01

    This paper shows the work on traffic analysis and control till date. It shows an approach to regulate traffic the use of image processing and MATLAB systems. This concept uses computational images that are to be compared with original images of the street taken in order to determine the traffic level percentage and set the timing for the traffic signal accordingly which are used to reduce the traffic stoppage on traffic lights. They concept proposes to solve real life scenarios in the streets, thus enriching the traffic lights by adding image receivers like HD cameras and image processors. The input is then imported into MATLAB to be used. as a method for calculating the traffic on roads. Their results would be computed in order to adjust the traffic light timings on a particular street, and also with respect to other similar proposals but with the added value of solving a real, big instance.

  11. Development of Image Analysis Software of MAXI

    Science.gov (United States)

    Eguchi, S.; Ueda, Y.; Hiroi, K.; Isobe, N.; Sugizaki, M.; Suzuki, M.; Tomida, H.; Maxi Team

    2010-12-01

    Monitor of All-sky X-ray Image (MAXI) is an X-ray all-sky monitor, attached to the Japanese experiment module Kibo on the International Space Station. The main scientific goals of the MAXI mission include the discovery of X-ray novae followed by prompt alerts to the community (Negoro et al., in this conference), and production of X-ray all-sky maps and new source catalogs with unprecedented sensitivities. To extract the best capabilities of the MAXI mission, we are working on the development of detailed image analysis tools. We utilize maximum likelihood fitting to a projected sky image, where we take account of the complicated detector responses, such as the background and point spread functions (PSFs). The modeling of PSFs, which strongly depend on the orbit and attitude of MAXI, is a key element in the image analysis. In this paper, we present the status of our software development.

  12. Digital image analysis of NDT radiographs

    International Nuclear Information System (INIS)

    Graeme, W.A. Jr.; Eizember, A.C.; Douglass, J.

    1989-01-01

    Prior to the introduction of Charge Coupled Device (CCD) detectors the majority of image analysis performed on NDT radiographic images was done visually in the analog domain. While some film digitization was being performed, the process was often unable to capture all the usable information on the radiograph or was too time consuming. CCD technology now provides a method to digitize radiographic film images without losing the useful information captured in the original radiograph in a timely process. Incorporating that technology into a complete digital radiographic workstation allows analog radiographic information to be processed, providing additional information to the radiographer. Once in the digital domain, that data can be stored, and fused with radioscopic and other forms of digital data. The result is more productive analysis and management of radiographic inspection data. The principal function of the NDT Scan IV digital radiography system is the digitization, enhancement and storage of radiographic images

  13. Mathematical foundations of image processing and analysis

    CERN Document Server

    Pinoli, Jean-Charles

    2014-01-01

    Mathematical Imaging is currently a rapidly growing field in applied mathematics, with an increasing need for theoretical mathematics. This book, the second of two volumes, emphasizes the role of mathematics as a rigorous basis for imaging sciences. It provides a comprehensive and convenient overview of the key mathematical concepts, notions, tools and frameworks involved in the various fields of gray-tone and binary image processing and analysis, by proposing a large, but coherent, set of symbols and notations, a complete list of subjects and a detailed bibliography. It establishes a bridg

  14. Chromatic Image Analysis For Quantitative Thermal Mapping

    Science.gov (United States)

    Buck, Gregory M.

    1995-01-01

    Chromatic image analysis system (CIAS) developed for use in noncontact measurements of temperatures on aerothermodynamic models in hypersonic wind tunnels. Based on concept of temperature coupled to shift in color spectrum for optical measurement. Video camera images fluorescence emitted by phosphor-coated model at two wavelengths. Temperature map of model then computed from relative brightnesses in video images of model at those wavelengths. Eliminates need for intrusive, time-consuming, contact temperature measurements by gauges, making it possible to map temperatures on complex surfaces in timely manner and at reduced cost.

  15. Laue image analysis. Pt. 2

    International Nuclear Information System (INIS)

    Greenhough, T.J.; Shrive, A.K.

    1994-01-01

    Many Laue diffraction patterns from crystals of particular biological or chemical interest are of insufficient quality for their analysis to be feasible. In many cases, this is because of pronounced streaking of the spots owing to either large mosaic spread or disorder introduced during reactions in the crystal. Methods for the analysis of exposures exhibiting radial or near-radial streaking are described, along with their application in Laue diffraction studies of form-II crystals of Met-tRNA synthetase and a photosynthetic reaction centre from Rhodobacter sphaeroides. In both cases, variable elliptical radial masking has led to significant improvements in data quality and quantity and exposures that previously were too streaked to process may now be analysed. These masks can also provide circular profiles as a special case for processing high-quality Laue exposures and spatial-overlap deconvolution may be performed using the elliptical or circular masks. (orig.)

  16. Multisource Images Analysis Using Collaborative Clustering

    Directory of Open Access Journals (Sweden)

    Pierre Gançarski

    2008-04-01

    Full Text Available The development of very high-resolution (VHR satellite imagery has produced a huge amount of data. The multiplication of satellites which embed different types of sensors provides a lot of heterogeneous images. Consequently, the image analyst has often many different images available, representing the same area of the Earth surface. These images can be from different dates, produced by different sensors, or even at different resolutions. The lack of machine learning tools using all these representations in an overall process constraints to a sequential analysis of these various images. In order to use all the information available simultaneously, we propose a framework where different algorithms can use different views of the scene. Each one works on a different remotely sensed image and, thus, produces different and useful information. These algorithms work together in a collaborative way through an automatic and mutual refinement of their results, so that all the results have almost the same number of clusters, which are statistically similar. Finally, a unique result is produced, representing a consensus among the information obtained by each clustering method on its own image. The unified result and the complementarity of the single results (i.e., the agreement between the clustering methods as well as the disagreement lead to a better understanding of the scene. The experiments carried out on multispectral remote sensing images have shown that this method is efficient to extract relevant information and to improve the scene understanding.

  17. Applications Of Binary Image Analysis Techniques

    Science.gov (United States)

    Tropf, H.; Enderle, E.; Kammerer, H. P.

    1983-10-01

    After discussing the conditions where binary image analysis techniques can be used, three new applications of the fast binary image analysis system S.A.M. (Sensorsystem for Automation and Measurement) are reported: (1) The human view direction is measured at TV frame rate while the subject's head is free movable. (2) Industrial parts hanging on a moving conveyor are classified prior to spray painting by robot. (3) In automotive wheel assembly, the eccentricity of the wheel is minimized by turning the tyre relative to the rim in order to balance the eccentricity of the components.

  18. Fourier analysis: from cloaking to imaging

    Science.gov (United States)

    Wu, Kedi; Cheng, Qiluan; Wang, Guo Ping

    2016-04-01

    Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers.

  19. Fourier analysis: from cloaking to imaging

    International Nuclear Information System (INIS)

    Wu, Kedi; Ping Wang, Guo; Cheng, Qiluan

    2016-01-01

    Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers. (review)

  20. Quantitative Image Simulation and Analysis of Nanoparticles

    DEFF Research Database (Denmark)

    Madsen, Jacob; Hansen, Thomas Willum

    Microscopy (HRTEM) has become a routine analysis tool for structural characterization at atomic resolution, and with the recent development of in-situ TEMs, it is now possible to study catalytic nanoparticles under reaction conditions. However, the connection between an experimental image, and the underlying...... physical phenomena or structure is not always straightforward. The aim of this thesis is to use image simulation to better understand observations from HRTEM images. Surface strain is known to be important for the performance of nanoparticles. Using simulation, we estimate of the precision and accuracy...... of strain measurements from TEM images, and investigate the stability of these measurements to microscope parameters. This is followed by our efforts toward simulating metal nanoparticles on a metal-oxide support using the Charge Optimized Many Body (COMB) interatomic potential. The simulated interface...

  1. Hyperspectral Image Analysis of Food Quality

    DEFF Research Database (Denmark)

    Arngren, Morten

    inspection.Near-infrared spectroscopy can address these issues by offering a fast and objectiveanalysis of the food quality. A natural extension to these single spectrumNIR systems is to include image information such that each pixel holds a NIRspectrum. This augmented image information offers several......Assessing the quality of food is a vital step in any food processing line to ensurethe best food quality and maximum profit for the farmer and food manufacturer.Traditional quality evaluation methods are often destructive and labourintensive procedures relying on wet chemistry or subjective human...... extensions to the analysis offood quality. This dissertation is concerned with hyperspectral image analysisused to assess the quality of single grain kernels. The focus is to highlight thebenefits and challenges of using hyperspectral imaging for food quality presentedin two research directions. Initially...

  2. Deep Learning in Medical Image Analysis.

    Science.gov (United States)

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

    2017-06-21

    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

  3. Data Analysis Strategies in Medical Imaging.

    Science.gov (United States)

    Parmar, Chintan; Barry, Joseph D; Hosny, Ahmed; Quackenbush, John; Aerts, Hugo Jwl

    2018-03-26

    Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence (AI) has allowed for detailed quantification of radiographic characteristics of tissues using predefined engineered algorithms or deep learning methods. Precedents in radiology as well as a wealth of research studies hint at the clinical relevance of these characteristics. However, there are critical challenges associated with the analysis of medical imaging data. While some of these challenges are specific to the imaging field, many others like reproducibility and batch effects are generic and have already been addressed in other quantitative fields such as genomics. Here, we identify these pitfalls and provide recommendations for analysis strategies of medical imaging data including data normalization, development of robust models, and rigorous statistical analyses. Adhering to these recommendations will not only improve analysis quality, but will also enhance precision medicine by allowing better integration of imaging data with other biomedical data sources. Copyright ©2018, American Association for Cancer Research.

  4. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2012-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. The pellets were divided into two groups: one with pellets coated using synthetic astaxanthin in fish oil and the other with pellets coated...

  5. A virtual laboratory for medical image analysis

    NARCIS (Netherlands)

    Olabarriaga, Sílvia D.; Glatard, Tristan; de Boer, Piter T.

    2010-01-01

    This paper presents the design, implementation, and usage of a virtual laboratory for medical image analysis. It is fully based on the Dutch grid, which is part of the Enabling Grids for E-sciencE (EGEE) production infrastructure and driven by the gLite middleware. The adopted service-oriented

  6. Scanning transmission electron microscopy imaging and analysis

    CERN Document Server

    Pennycook, Stephen J

    2011-01-01

    Provides the first comprehensive treatment of the physics and applications of this mainstream technique for imaging and analysis at the atomic level Presents applications of STEM in condensed matter physics, materials science, catalysis, and nanoscience Suitable for graduate students learning microscopy, researchers wishing to utilize STEM, as well as for specialists in other areas of microscopy Edited and written by leading researchers and practitioners

  7. Flame analysis using image processing techniques

    Science.gov (United States)

    Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

    2018-04-01

    This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

  8. Frequency domain analysis of knock images

    Science.gov (United States)

    Qi, Yunliang; He, Xin; Wang, Zhi; Wang, Jianxin

    2014-12-01

    High speed imaging-based knock analysis has mainly focused on time domain information, e.g. the spark triggered flame speed, the time when end gas auto-ignition occurs and the end gas flame speed after auto-ignition. This study presents a frequency domain analysis on the knock images recorded using a high speed camera with direct photography in a rapid compression machine (RCM). To clearly visualize the pressure wave oscillation in the combustion chamber, the images were high-pass-filtered to extract the luminosity oscillation. The luminosity spectrum was then obtained by applying fast Fourier transform (FFT) to three basic colour components (red, green and blue) of the high-pass-filtered images. Compared to the pressure spectrum, the luminosity spectra better identify the resonant modes of pressure wave oscillation. More importantly, the resonant mode shapes can be clearly visualized by reconstructing the images based on the amplitudes of luminosity spectra at the corresponding resonant frequencies, which agree well with the analytical solutions for mode shapes of gas vibration in a cylindrical cavity.

  9. SPECIES-SPECIFIC FOREST VARIABLE ESTIMATION USING NON-PARAMETRIC MODELING OF MULTI-SPECTRAL PHOTOGRAMMETRIC POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    J. Bohlin

    2012-07-01

    Full Text Available The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E. Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean, stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean, with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet showed RMSEs (in percent of the surveyed stand mean of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.

  10. Computed image analysis of neutron radiographs

    International Nuclear Information System (INIS)

    Dinca, M.; Anghel, E.; Preda, M.; Pavelescu, M.

    2008-01-01

    Similar with X-radiography, using neutron like penetrating particle, there is in practice a nondestructive technique named neutron radiology. When the registration of information is done on a film with the help of a conversion foil (with high cross section for neutrons) that emits secondary radiation (β,γ) that creates a latent image, the technique is named neutron radiography. A radiographic industrial film that contains the image of the internal structure of an object, obtained by neutron radiography, must be subsequently analyzed to obtain qualitative and quantitative information about the structural integrity of that object. There is possible to do a computed analysis of a film using a facility with next main components: an illuminator for film, a CCD video camera and a computer (PC) with suitable software. The qualitative analysis intends to put in evidence possibly anomalies of the structure due to manufacturing processes or induced by working processes (for example, the irradiation activity in the case of the nuclear fuel). The quantitative determination is based on measurements of some image parameters: dimensions, optical densities. The illuminator has been built specially to perform this application but can be used for simple visual observation. The illuminated area is 9x40 cm. The frame of the system is a comparer of Abbe Carl Zeiss Jena type, which has been adapted to achieve this application. The video camera assures the capture of image that is stored and processed by computer. A special program SIMAG-NG has been developed at INR Pitesti that beside of the program SMTV II of the special acquisition module SM 5010 can analyze the images of a film. The major application of the system was the quantitative analysis of a film that contains the images of some nuclear fuel pins beside a dimensional standard. The system was used to measure the length of the pellets of the TRIGA nuclear fuel. (authors)

  11. Web Based Distributed Coastal Image Analysis System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This project develops Web based distributed image analysis system processing the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide decision...

  12. Digital image sequence processing, compression, and analysis

    CERN Document Server

    Reed, Todd R

    2004-01-01

    IntroductionTodd R. ReedCONTENT-BASED IMAGE SEQUENCE REPRESENTATIONPedro M. Q. Aguiar, Radu S. Jasinschi, José M. F. Moura, andCharnchai PluempitiwiriyawejTHE COMPUTATION OF MOTIONChristoph Stiller, Sören Kammel, Jan Horn, and Thao DangMOTION ANALYSIS AND DISPLACEMENT ESTIMATION IN THE FREQUENCY DOMAINLuca Lucchese and Guido Maria CortelazzoQUALITY OF SERVICE ASSESSMENT IN NEW GENERATION WIRELESS VIDEO COMMUNICATIONSGaetano GiuntaERROR CONCEALMENT IN DIGITAL VIDEOFrancesco G.B. De NataleIMAGE SEQUENCE RESTORATION: A WIDER PERSPECTIVEAnil KokaramVIDEO SUMMARIZATIONCuneyt M. Taskiran and Edward

  13. Study of TCP densification via image analysis

    International Nuclear Information System (INIS)

    Silva, R.C.; Alencastro, F.S.; Oliveira, R.N.; Soares, G.A.

    2011-01-01

    Among ceramic materials that mimic human bone, β-type tri-calcium phosphate (β-TCP) has shown appropriate chemical stability and superior resorption rate when compared to hydroxyapatite. In order to increase its mechanical strength, the material is sintered, under controlled time and temperature conditions, to obtain densification without phase change. In the present work, tablets were produced via uniaxial compression and then sintered at 1150°C for 2h. The analysis via XRD and FTIR showed that the sintered tablets were composed only by β-TCP. The SEM images were used for quantification of grain size and volume fraction of pores, via digital image analysis. The tablets showed small pore fraction (between 0,67% and 6,38%) and homogeneous grain size distribution (∼2μm). Therefore, the analysis method seems viable to quantify porosity and grain size. (author)

  14. Analysis of renal nuclear medicine images

    International Nuclear Information System (INIS)

    Jose, R.M.J.

    2000-01-01

    Nuclear medicine imaging of the renal system involves producing time-sequential images showing the distribution of a radiopharmaceutical in the renal system. Producing numerical and graphical data from nuclear medicine studies requires defining regions of interest (ROIs) around various organs within the field of view, such as the left kidney, right kidney and bladder. Automating this process has several advantages: a saving of a clinician's time; enhanced objectivity and reproducibility. This thesis describes the design, implementation and assessment of an automatic ROI generation system. The performance of the system described in this work is assessed by comparing the results to those obtained using manual techniques. Since nuclear medicine images are inherently noisy, the sequence of images is reconstructed using the first few components of a principal components analysis in order to reduce the noise in the images. An image of the summed reconstructed sequence is then formed. This summed image is segmented by using an edge co-occurrence matrix as a feature space for simultaneously classifying regions and locating boundaries. Two methods for assigning the regions of a segmented image to organ class labels are assessed. The first method is based on using Dempster-Shafer theory to combine uncertain evidence from several sources into a single evidence; the second method makes use of a neural network classifier. The use of each technique in classifying the regions of a segmented image are assessed in separate experiments using 40 real patient-studies. A comparative assessment of the two techniques shows that the neural network produces more accurate region labels for the kidneys. The optimum neural system is determined experimentally. Results indicate that combining temporal and spatial information with a priori clinical knowledge produces reasonable ROIs. Consistency in the neural network assignment of regions is enhanced by taking account of the contextual

  15. Rapid Analysis and Exploration of Fluorescence Microscopy Images

    OpenAIRE

    Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason; Steininger, Robert J; Wu, Lani; Altschuler, Steven

    2014-01-01

    Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.

  16. Image analysis for ophthalmological diagnosis image processing of Corvis ST images using Matlab

    CERN Document Server

    Koprowski, Robert

    2016-01-01

    This monograph focuses on the use of analysis and processing methods for images from the Corvis® ST tonometer. The presented analysis is associated with the quantitative, repeatable and fully automatic evaluation of the response of the eye, eyeball and cornea to an air-puff. All the described algorithms were practically implemented in MATLAB®. The monograph also describes and provides the full source code designed to perform the discussed calculations. As a result, this monograph is intended for scientists, graduate students and students of computer science and bioengineering as well as doctors wishing to expand their knowledge of modern diagnostic methods assisted by various image analysis and processing methods.

  17. Image sequence analysis workstation for multipoint motion analysis

    Science.gov (United States)

    Mostafavi, Hassan

    1990-08-01

    This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.

  18. Quantitative Analysis in Nuclear Medicine Imaging

    CERN Document Server

    2006-01-01

    This book provides a review of image analysis techniques as they are applied in the field of diagnostic and therapeutic nuclear medicine. Driven in part by the remarkable increase in computing power and its ready and inexpensive availability, this is a relatively new yet rapidly expanding field. Likewise, although the use of radionuclides for diagnosis and therapy has origins dating back almost to the discovery of natural radioactivity itself, radionuclide therapy and, in particular, targeted radionuclide therapy has only recently emerged as a promising approach for therapy of cancer and, to a lesser extent, other diseases. As effort has, therefore, been made to place the reviews provided in this book in a broader context. The effort to do this is reflected by the inclusion of introductory chapters that address basic principles of nuclear medicine imaging, followed by overview of issues that are closely related to quantitative nuclear imaging and its potential role in diagnostic and therapeutic applications. ...

  19. Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox

    Directory of Open Access Journals (Sweden)

    Andre Santos Ribeiro

    2015-07-01

    Full Text Available Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity.Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI and positron emission tomography (PET. It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also.Results. It was observed both a high inter

  20. Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China Using Multi-Spectral Phenological Metrics from MODIS Time Series

    Directory of Open Access Journals (Sweden)

    Sebastian van der Linden

    2013-05-01

    Full Text Available We developed and evaluated a new approach for mapping rubber plantations and natural forests in one of Southeast Asia’s biodiversity hot spots, Xishuangbanna in China. We used a one-year annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS, Enhanced Vegetation Index (EVI and short-wave infrared (SWIR reflectance data to develop phenological metrics. These phenological metrics were used to classify rubber plantations and forests with the Random Forest classification algorithm. We evaluated which key phenological characteristics were important to discriminate rubber plantations and natural forests by estimating the influence of each metric on the classification accuracy. As a benchmark, we compared the best classification with a classification based on the full, fitted time series data. Overall classification accuracies derived from EVI and SWIR time series alone were 64.4% and 67.9%, respectively. Combining the phenological metrics from EVI and SWIR time series improved the accuracy to 73.5%. Using the full, smoothed time series data instead of metrics derived from the time series improved the overall accuracy only slightly (1.3%, indicating that the phenological metrics were sufficient to explain the seasonal changes captured by the MODIS time series. The results demonstrate a promising utility of phenological metrics for mapping and monitoring rubber expansion with MODIS.

  1. Semiautomatic digital imaging system for cytogenetic analysis

    International Nuclear Information System (INIS)

    Chaubey, R.C.; Chauhan, P.C.; Bannur, S.V.; Kulgod, S.V.; Chadda, V.K.; Nigam, R.K.

    1999-08-01

    The paper describes a digital image processing system, developed indigenously at BARC for size measurement of microscopic biological objects such as cell, nucleus and micronucleus in mouse bone marrow; cytochalasin-B blocked human lymphocytes in-vitro; numerical counting and karyotyping of metaphase chromosomes of human lymphocytes. Errors in karyotyping of chromosomes by the imaging system may creep in due to lack of well-defined position of centromere or extensive bending of chromosomes, which may result due to poor quality of preparation. Good metaphase preparations are mandatory for precise and accurate analysis by the system. Additional new morphological parameters about each chromosome have to be incorporated to improve the accuracy of karyotyping. Though the experienced cytogenetisist is the final judge; however, the system assists him/her to carryout analysis much faster as compared to manual scoring. Further, experimental studies are in progress to validate different software packages developed for various cytogenetic applications. (author)

  2. Morphometric image analysis of giant vesicles

    DEFF Research Database (Denmark)

    Husen, Peter Rasmussen; Arriaga, Laura; Monroy, Francisco

    2012-01-01

    We have developed a strategy to determine lengths and orientations of tie lines in the coexistence region of liquid-ordered and liquid-disordered phases of cholesterol containing ternary lipid mixtures. The method combines confocal-fluorescence-microscopy image stacks of giant unilamellar vesicles...... (GUVs), a dedicated 3D-image analysis, and a quantitative analysis based in equilibrium thermodynamic considerations. This approach was tested in GUVs composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine/1,2-palmitoyl-sn-glycero-3-phosphocholine/cholesterol. In general, our results show a reasonable...... agreement with previously reported data obtained by other methods. For example, our computed tie lines were found to be nonhorizontal, indicating a difference in cholesterol content in the coexisting phases. This new, to our knowledge, analytical strategy offers a way to further exploit fluorescence...

  3. Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar’s Tanintharyi Region

    Directory of Open Access Journals (Sweden)

    Grant Connette

    2016-10-01

    Full Text Available We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while considering scenarios with all natural forest classes grouped into a single intact or degraded category. Overall, classification accuracy increased for the multivariate Gaussian model with the partitioning of intact and degraded forest into separate forest cover classes but slightly decreased based on the Random Forest classifier. Natural forest cover was estimated to be 80.7% of total area in Tanintharyi. The most prevalent forest types are upland evergreen forest (42.3% of area and lowland evergreen forest (21.6%. However, while just 27.1% of upland evergreen forest was classified as degraded (on the basis of canopy cover <80%, 66.0% of mangrove forest and 47.5% of the region’s biologically-rich lowland evergreen forest were classified as degraded. This information on the current status of Tanintharyi’s unique forest ecosystems and patterns of human land use is critical to effective conservation strategies and land-use planning.

  4. Image Analysis for Nail-fold Capillaroscopy

    OpenAIRE

    Vucic, Vladimir

    2015-01-01

    Detection of diseases in an early stage is very important since it can make the treatment of patients easier, safer and more ecient. For the detection of rheumatic diseases, and even prediction of tendencies towards such diseases, capillaroscopy is becoming an increasingly recognized method. Nail-fold capillaroscopy is a non-invasive imaging technique that is used for analysis of microcirculation abnormalities that may lead todisease like systematic sclerosis, Reynauds phenomenon and others. ...

  5. Computerized analysis of brain perfusion parameter images

    International Nuclear Information System (INIS)

    Turowski, B.; Haenggi, D.; Wittsack, H.J.; Beck, A.; Aurich, V.

    2007-01-01

    Purpose: The development of a computerized method which allows a direct quantitative comparison of perfusion parameters. The display should allow a clear direct comparison of brain perfusion parameters in different vascular territories and over the course of time. The analysis is intended to be the basis for further evaluation of cerebral vasospasm after subarachnoid hemorrhage (SAH). The method should permit early diagnosis of cerebral vasospasm. Materials and Methods: The Angiotux 2D-ECCET software was developed with a close cooperation between computer scientists and clinicians. Starting from parameter images of brain perfusion, the cortex was marked, segmented and assigned to definite vascular territories. The underlying values were averages for each segment and were displayed in a graph. If a follow-up was available, the mean values of the perfusion parameters were displayed in relation to time. The method was developed under consideration of CT perfusion values but is applicable for other methods of perfusion imaging. Results: Computerized analysis of brain perfusion parameter images allows an immediate comparison of these parameters and follow-up of mean values in a clear and concise manner. Values are related to definite vascular territories. The tabular output facilitates further statistic evaluations. The computerized analysis is precisely reproducible, i. e., repetitions result in exactly the same output. (orig.)

  6. Considerations and methods for the changes detection using satellite images in the Municipality of Paipa

    International Nuclear Information System (INIS)

    Riano M, Orlando

    2002-01-01

    In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality

  7. 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.

  8. Image analysis and modeling in medical image computing. Recent developments and advances.

    Science.gov (United States)

    Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

    2012-01-01

    Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

  9. The Digital Image Processing And Quantitative Analysis In Microscopic Image Characterization

    International Nuclear Information System (INIS)

    Ardisasmita, M. Syamsa

    2000-01-01

    Many electron microscopes although have produced digital images, but not all of them are equipped with a supporting unit to process and analyse image data quantitatively. Generally the analysis of image has to be made visually and the measurement is realized manually. The development of mathematical method for geometric analysis and pattern recognition, allows automatic microscopic image analysis with computer. Image processing program can be used for image texture and structure periodic analysis by the application of Fourier transform. Because the development of composite materials. Fourier analysis in frequency domain become important for measure the crystallography orientation. The periodic structure analysis and crystal orientation are the key to understand many material properties like mechanical strength. stress, heat conductivity, resistance, capacitance and other material electric and magnetic properties. In this paper will be shown the application of digital image processing in microscopic image characterization and analysis in microscopic image

  10. Multi-spectral remote sensing of the vortex formerly known as White Oval BA: Temperature structure and cloud properties

    Science.gov (United States)

    Orton, G.; Parrish, P.; Yanamandra-Fisher, P.; Baines, K.; Mousis, O.; Pantin, E.; Fujiyoshi, T.; Fuse, T.; Simon-Miller, A.

    White Oval BA: Temperature structure and cloud properties G. Orton, P. Parrish, P. Yanamandra-Fisher, K. Baines (1), O. Mousis (2), E. Pantin (3), T. Fuse, T. Fujiyoshi (4), A. Simon-Miller (5) (1) Jet Propulsion Laboratory, Calif. Inst. of Technology, USA, (2) Obs. de Besancon, France, (3) C.E.A., France, (4) Subaru National Astron. Obs., Japan, (5) NASA Goddard Space Flight Center, USA. (Glenn.Orton@jpl.nasa.gov) White Oval BA, constituted from 3 predecessor vortices (known as Jupiter's "classical" White Ovals) after successive mergers in 1998 and 2000, became second-largest vortex in the atmosphere of Jupiter (and possibly the solar system) at the time of its formation. While it continues in this distinction, it required a name change after a 2005 December through 2006 February transformation which made it appear visually the same color as the Great Red Spot. Our campaign to understand the changes involved examination of the detailed color and wind field using Hubble Space Telescope instrumentation on several orbits in April. The field of temperatures, ammonia distribution and clouds were also examined using the mid-infrared VISIR camera/spectrometer on ESO's 8.2-m Very Large Telescope (3), the NASA Infrared telescope with the mid-infrared MIRSI instrument and the refurbished near-infrared facility camera NSFCam2. High-resolution images of the Oval were made before the color change with the COMICS mid-infrared facility on the Subaru telescope. We are using these data, and possibly others to be acquired during the summer, to characterize the extent to which changes in storm strength (vorticity, positive vertical motion) influenced (i) the depth from which colored cloud particles may have been "dredged up" from depth or (ii) the altitude to which particles may have been lofted and subject to high-energy UV radiation which caused a color change, as alternative explanations for the phenomenon. Clues to this will provide clues to the chemistry of Jupiter's cloud

  11. Retrieval of Cloud Properties from the Multi-spectral, Multi-viewing and Polarized Measurements of the Airborne Polarimeter OSIRIS

    Science.gov (United States)

    Matar, C.; Cornet, C.; Parol, F.; C-Labonnote, L.; Auriol, F.; Nicolas, J. M.

    2017-12-01

    Clouds are recognized as a major source of uncertainty in forecasting the evolution of climate change. One way to improve our knowledge is to obtain accurate cloud properties and variabilities at high spatial resolution. Airborne remote sensing measurements are very suitable to achieve these targets with a tens of meters resolution. In this context, we exploit multi-viewing measurements of the new airborne radiometer OSIRIS (Observing System Including Polarization in the Solar Infrared Spectrum), developed in the Laboratoire d'Optique Atmosphérique (LOA). It is based on POLDER concept as a prototype of the future spacecraft 3MI (Multi-Viewing Multi-Channel Multi-Polarisation Imaging Mission) that will be part of the EPS-SG Eumetsat-ESA mission. Currently, most operational remote sensing algorithms used to retrieve cloud properties from passive measurements, are based on the construction of pre-calculated Look-Up Tables (LUT) under the hypothesis of a single plane-parallel cloud layer. This assumption leads to certain limitations and possible large errors.We developed an optimal estimation method to retrieve cloud optical thickness and effective radius of cloud droplets. This inversion method is more flexible than the LUT method and allows to take into account uncertainties on both observations and the physical model leading to a direct estimation of the retrievals uncertainties in a well-established formalism. For example, we include uncertainties on retrieved cloud parameters due to an incorrect estimation of the ocean surface winds speed, the cloud vertical profiles and the 3D radiative transfer effects.OSIRIS has two separate optical sensors, one for the visible and near infrared range and the other one for the shortwave infrared (SWIR). Consequently, the developed algorithms are based on two different types of information: (1) the total and polarized multi-viewing reflectances from the visible range and (2) the multi-viewing total reflectances from two SWIR

  12. Automatic dirt trail analysis in dermoscopy images.

    Science.gov (United States)

    Cheng, Beibei; Joe Stanley, R; Stoecker, William V; Osterwise, Christopher T P; Stricklin, Sherea M; Hinton, Kristen A; Moss, Randy H; Oliviero, Margaret; Rabinovitz, Harold S

    2013-02-01

    Basal cell carcinoma (BCC) is the most common cancer in the US. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails. In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions. For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 are under a receiver operating characteristic curve using a leave-one-out approach. Results obtained from this study show that automatic detection of dirt trails in dermoscopic images of BCC is feasible. This is important because of the large number of these skin cancers seen every year and the challenge of discovering these earlier with instrumentation. © 2011 John Wiley & Sons A/S.

  13. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A

    2013-01-01

    Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

  14. [Imaging Mass Spectrometry in Histopathologic Analysis].

    Science.gov (United States)

    Yamazaki, Fumiyoshi; Seto, Mitsutoshi

    2015-04-01

    Matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) enables visualization of the distribution of a range of biomolecules by integrating biochemical information from mass spectrometry with positional information from microscopy. IMS identifies a target molecule. In addition, IMS enables global analysis of biomolecules containing unknown molecules by detecting the ratio of the molecular weight to electric charge without any target, which makes it possible to identify novel molecules. IMS generates data on the distribution of lipids and small molecules in tissues, which is difficult to visualize with either conventional counter-staining or immunohistochemistry. In this review, we firstly introduce the principle of imaging mass spectrometry and recent advances in the sample preparation method. Secondly, we present findings regarding biological samples, especially pathological ones. Finally, we discuss the limitations and problems of the IMS technique and clinical application, such as in drug development.

  15. Machine Learning Interface for Medical Image Analysis.

    Science.gov (United States)

    Zhang, Yi C; Kagen, Alexander C

    2017-10-01

    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  16. Phase Image Analysis in Conduction Disturbance Patients

    International Nuclear Information System (INIS)

    Kwark, Byeng Su; Choi, Si Wan; Kang, Seung Sik; Park, Ki Nam; Lee, Kang Wook; Jeon, Eun Seok; Park, Chong Hun

    1994-01-01

    It is known that the normal His-Purkinje system provides for nearly synchronous activation of right (RV) and left (LV) ventricles. When His-Purkinje conduction is abnormal, the resulting sequence of ventricular contraction must be correspondingly abnormal. These abnormal mechanical consequences were difficult to demonstrate because of the complexity and the rapidity of its events. To determine the relationship of the phase changes and the abnormalities of ventricular conduction, we performed phase image analysis of Tc-RBC gated blood pool scintigrams in patients with intraventricular conduction disturbances (24 complete left bundle branch block (C-LBBB), 15 complete right bundle branch block (C-RBBB), 13 Wolff-Parkinson-White syndrome (WPW), 10 controls). The results were as follows; 1) The ejection fraction (EF), peak ejection rate (PER), and peak filling rate (PFR) of LV in gated blood pool scintigraphy (GBPS) were significantly lower in patients with C-LBBB than in controls (44.4 ± 13.9% vs 69.9 ± 4.2%, 2.48 ± 0.98 vs 3.51 ± 0,62, 1.76 ± 0.71 vs 3.38 ± 0.92, respectively, p<0.05). 2) In the phase angle analysis of LV, Standard deviation (SD), width of half maximum of phase angle (FWHM), and range of phase angle were significantly increased in patients with C-LBBB than in controls (20.6 + 18.1 vs S.6 + I.8, 22. 5 + 9.2 vs 16.0 + 3.9, 95.7 + 31.7 vs 51.3 + 5.4, respectively, p<0.05). 3) There was no significant difference in EF, PER, PFR between patients with the WolffParkinson-White syndrome and controls. 4) Standard deviation and range of phase angle were significantly higher in patients with WPW syndrome than in controls (10.6 + 2.6 vs 8.6 + 1.8, p<0.05, 69.8 + 11.7 vs 51.3 + 5 4, p<0.001, respectively), however, there was no difference between the two groups in full width of half maximum. 5) Phase image analysis revealed relatively uniform phase across the both ventriles in patients with normal conduction, but markedly delayed phase in the left ventricle

  17. Phase Image Analysis in Conduction Disturbance Patients

    Energy Technology Data Exchange (ETDEWEB)

    Kwark, Byeng Su; Choi, Si Wan; Kang, Seung Sik; Park, Ki Nam; Lee, Kang Wook; Jeon, Eun Seok; Park, Chong Hun [Chung Nam University Hospital, Daejeon (Korea, Republic of)

    1994-03-15

    It is known that the normal His-Purkinje system provides for nearly synchronous activation of right (RV) and left (LV) ventricles. When His-Purkinje conduction is abnormal, the resulting sequence of ventricular contraction must be correspondingly abnormal. These abnormal mechanical consequences were difficult to demonstrate because of the complexity and the rapidity of its events. To determine the relationship of the phase changes and the abnormalities of ventricular conduction, we performed phase image analysis of Tc-RBC gated blood pool scintigrams in patients with intraventricular conduction disturbances (24 complete left bundle branch block (C-LBBB), 15 complete right bundle branch block (C-RBBB), 13 Wolff-Parkinson-White syndrome (WPW), 10 controls). The results were as follows; 1) The ejection fraction (EF), peak ejection rate (PER), and peak filling rate (PFR) of LV in gated blood pool scintigraphy (GBPS) were significantly lower in patients with C-LBBB than in controls (44.4 +- 13.9% vs 69.9 +- 4.2%, 2.48 +- 0.98 vs 3.51 +- 0,62, 1.76 +- 0.71 vs 3.38 +- 0.92, respectively, p<0.05). 2) In the phase angle analysis of LV, Standard deviation (SD), width of half maximum of phase angle (FWHM), and range of phase angle were significantly increased in patients with C-LBBB than in controls (20.6 + 18.1 vs S.6 + I.8, 22. 5 + 9.2 vs 16.0 + 3.9, 95.7 + 31.7 vs 51.3 + 5.4, respectively, p<0.05). 3) There was no significant difference in EF, PER, PFR between patients with the WolffParkinson-White syndrome and controls. 4) Standard deviation and range of phase angle were significantly higher in patients with WPW syndrome than in controls (10.6 + 2.6 vs 8.6 + 1.8, p<0.05, 69.8 + 11.7 vs 51.3 + 5 4, p<0.001, respectively), however, there was no difference between the two groups in full width of half maximum. 5) Phase image analysis revealed relatively uniform phase across the both ventriles in patients with normal conduction, but markedly delayed phase in the left ventricle

  18. A report on digital image processing and analysis

    International Nuclear Information System (INIS)

    Singh, B.; Alex, J.; Haridasan, G.

    1989-01-01

    This report presents developments in software, connected with digital image processing and analysis in the Centre. In image processing, one resorts to either alteration of grey level values so as to enhance features in the image or resorts to transform domain operations for restoration or filtering. Typical transform domain operations like Karhunen-Loeve transforms are statistical in nature and are used for a good registration of images or template - matching. Image analysis procedures segment grey level images into images contained within selectable windows, for the purpose of estimating geometrical features in the image, like area, perimeter, projections etc. In short, in image processing both the input and output are images, whereas in image analyses, the input is an image whereas the output is a set of numbers and graphs. (author). 19 refs

  19. Uses of software in digital image analysis: a forensic report

    Science.gov (United States)

    Sharma, Mukesh; Jha, Shailendra

    2010-02-01

    Forensic image analysis is required an expertise to interpret the content of an image or the image itself in legal matters. Major sub-disciplines of forensic image analysis with law enforcement applications include photo-grammetry, photographic comparison, content analysis and image authentication. It has wide applications in forensic science range from documenting crime scenes to enhancing faint or indistinct patterns such as partial fingerprints. The process of forensic image analysis can involve several different tasks, regardless of the type of image analysis performed. Through this paper authors have tried to explain these tasks, which are described in to three categories: Image Compression, Image Enhancement & Restoration and Measurement Extraction. With the help of examples like signature comparison, counterfeit currency comparison and foot-wear sole impression using the software Canvas and Corel Draw.

  20. Analysis of image plane's Illumination in Image-forming System

    International Nuclear Information System (INIS)

    Duan Lihua; Zeng Yan'an; Zhang Nanyangsheng; Wang Zhiguo; Yin Shiliang

    2011-01-01

    In the detection of optical radiation, the detecting accuracy is affected by optic power distribution of the detector's surface to a large extent. In addition, in the image-forming system, the quality of the image is greatly determined by the uniformity of the image's illumination distribution. However, in the practical optical system, affected by the factors such as field of view, false light and off axis and so on, the distribution of the image's illumination tends to be non uniform, so it is necessary to discuss the image plane's illumination in image-forming systems. In order to analyze the characteristics of the image-forming system at a full range, on the basis of photometry, the formulas to calculate the illumination of the imaging plane have been summarized by the numbers. Moreover, the relationship between the horizontal offset of the light source and the illumination of the image has been discussed in detail. After that, the influence of some key factors such as aperture angle, off-axis distance and horizontal offset on illumination of the image has been brought forward. Through numerical simulation, various theoretical curves of those key factors have been given. The results of the numerical simulation show that it is recommended to aggrandize the diameter of the exit pupil to increase the illumination of the image. The angle of view plays a negative role in the illumination distribution of the image, that is, the uniformity of the illumination distribution can be enhanced by compressing the angle of view. Lastly, it is proved that telecentric optical design is an effective way to advance the uniformity of the illumination distribution.

  1. Microscopic validation of whole mouse micro-metastatic tumor imaging agents using cryo-imaging and sliding organ image registration

    Science.gov (United States)

    Liu, Yiqiao; Zhou, Bo; Qutaish, Mohammed; Wilson, David L.

    2016-03-01

    We created a metastasis imaging, analysis platform consisting of software and multi-spectral cryo-imaging system suitable for evaluating emerging imaging agents targeting micro-metastatic tumor. We analyzed CREKA-Gd in MRI, followed by cryo-imaging which repeatedly sectioned and tiled microscope images of the tissue block face, providing anatomical bright field and molecular fluorescence, enabling 3D microscopic imaging of the entire mouse with single metastatic cell sensitivity. To register MRI volumes to the cryo bright field reference, we used our standard mutual information, non-rigid registration which proceeded: preprocess --> affine --> B-spline non-rigid 3D registration. In this report, we created two modified approaches: mask where we registered locally over a smaller rectangular solid, and sliding organ. Briefly, in sliding organ, we segmented the organ, registered the organ and body volumes separately and combined results. Though sliding organ required manual annotation, it provided the best result as a standard to measure other registration methods. Regularization parameters for standard and mask methods were optimized in a grid search. Evaluations consisted of DICE, and visual scoring of a checkerboard display. Standard had accuracy of 2 voxels in all regions except near the kidney, where there were 5 voxels sliding. After mask and sliding organ correction, kidneys sliding were within 2 voxels, and Dice overlap increased 4%-10% in mask compared to standard. Mask generated comparable results with sliding organ and allowed a semi-automatic process.

  2. Multi-spectral camera development

    CSIR Research Space (South Africa)

    Holloway, M

    2012-10-01

    Full Text Available and Evaluation Bertus Theron Evaluation rational ? Data-sheets for COTS optical systems have limited performance data ? Optronic Sensor Systems (OSS) has the facility, Optronics Test and Evaluation Laboratory (OTEL), to benchmark and verify conformance... to the manufacturer?s data-sheet One measured parameter, namely cut-off frequency, of the lens was compared to the manufacturer?s data-sheet Hardware evaluation - COTS lens ? CSIR 2012 Slide 9 Hardware Design ? Sensor Unit ? CSIR 2012 Slide 10 Key design...

  3. Difference Image Analysis of Galactic Microlensing. I. Data Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Alcock, C.; Allsman, R. A.; Alves, D.; Axelrod, T. S.; Becker, A. C.; Bennett, D. P.; Cook, K. H.; Drake, A. J.; Freeman, K. C.; Griest, K. (and others)

    1999-08-20

    This is a preliminary report on the application of Difference Image Analysis (DIA) to Galactic bulge images. The aim of this analysis is to increase the sensitivity to the detection of gravitational microlensing. We discuss how the DIA technique simplifies the process of discovering microlensing events by detecting only objects that have variable flux. We illustrate how the DIA technique is not limited to detection of so-called ''pixel lensing'' events but can also be used to improve photometry for classical microlensing events by removing the effects of blending. We will present a method whereby DIA can be used to reveal the true unblended colors, positions, and light curves of microlensing events. We discuss the need for a technique to obtain the accurate microlensing timescales from blended sources and present a possible solution to this problem using the existing Hubble Space Telescope color-magnitude diagrams of the Galactic bulge and LMC. The use of such a solution with both classical and pixel microlensing searches is discussed. We show that one of the major causes of systematic noise in DIA is differential refraction. A technique for removing this systematic by effectively registering images to a common air mass is presented. Improvements to commonly used image differencing techniques are discussed. (c) 1999 The American Astronomical Society.

  4. Detection and Monitoring of E-Waste Contamination through Remote Sensing and Image Analysis

    Science.gov (United States)

    Garb, Yaakov; Friedlander, Lonia

    2015-04-01

    Electronic waste (e-waste) is one of today's fastest growing waste streams, and also one of the more problematic, as this end-of-life product contains precious metals mixed with and embedded in a variety of low value and potentially harmful plastic and other materials. This combination creates a powerful incentive for informal value chains that transport, extract from, and dispose of e-waste materials in far-ranging and unregulated ways, and especially in settings where regulation and livelihood alternatives are sparse, most notably in areas of India, China, and Africa. E-waste processing is known to release a variety of contaminants, such as heavy metals and persistent organic pollutants, including flame retardants, dioxins and furans. In several sites, where the livelihoods of entire communities are dependent on e-waste processing, the resulting contaminants have been demonstrated to enter the hydrological system and food chain and have serious health and ecological effects. In this paper we demonstrate for the first time the usefulness of multi-spectral remote sensing imagery to detect and monitor the release and possibly the dispersal of heavy metal contaminants released in e-waste processing. While similar techniques have been used for prospecting or for studying heavy metal contamination from mining and large industrial facilities, we suggest that these techniques are of particular value in detecting contamination from the more dispersed, shifting, and ad-hoc kinds of release typical of e-waste processing. Given the increased resolution and decreased price of multi-spectral imagery, such techniques may offer a remarkably cost-effective and rapidly responsive means of assessing and monitoring this kind of contamination. We will describe the geochemical and multi-spectral image-processing principles underlying our approach, and show how we have applied these to an area in which we have a detailed, multi-temporal, spatially referenced, and ground

  5. An expert image analysis system for chromosome analysis application

    International Nuclear Information System (INIS)

    Wu, Q.; Suetens, P.; Oosterlinck, A.; Van den Berghe, H.

    1987-01-01

    This paper reports a recent study on applying a knowledge-based system approach as a new attempt to solve the problem of chromosome classification. A theoretical framework of an expert image analysis system is proposed, based on such a study. In this scheme, chromosome classification can be carried out under a hypothesize-and-verify paradigm, by integrating a rule-based component, in which the expertise of chromosome karyotyping is formulated with an existing image analysis system which uses conventional pattern recognition techniques. Results from the existing system can be used to bring in hypotheses, and with the rule-based verification and modification procedures, improvement of the classification performance can be excepted

  6. The Scientific Image in Behavior Analysis.

    Science.gov (United States)

    Keenan, Mickey

    2016-05-01

    Throughout the history of science, the scientific image has played a significant role in communication. With recent developments in computing technology, there has been an increase in the kinds of opportunities now available for scientists to communicate in more sophisticated ways. Within behavior analysis, though, we are only just beginning to appreciate the importance of going beyond the printing press to elucidate basic principles of behavior. The aim of this manuscript is to stimulate appreciation of both the role of the scientific image and the opportunities provided by a quick response code (QR code) for enhancing the functionality of the printed page. I discuss the limitations of imagery in behavior analysis ("Introduction"), and I show examples of what can be done with animations and multimedia for teaching philosophical issues that arise when teaching about private events ("Private Events 1 and 2"). Animations are also useful for bypassing ethical issues when showing examples of challenging behavior ("Challenging Behavior"). Each of these topics can be accessed only by scanning the QR code provided. This contingency has been arranged to help the reader embrace this new technology. In so doing, I hope to show its potential for going beyond the limitations of the printing press.

  7. Etching and image analysis of the microstructure in marble

    DEFF Research Database (Denmark)

    Alm, Ditte; Brix, Susanne; Howe-Rasmussen, Helle

    2005-01-01

    of grains exposed on that surface are measured on the microscope images using image analysis by the program Adobe Photoshop 7.0 with Image Processing Toolkit 4.0. The parameters measured by the program on microscope images of thin sections of two marble types are used for calculation of the coefficient...

  8. UAS-based soil carbon mapping using VIS-NIR (480–1000 nm) multi-spectral imaging: Potential and limitations

    DEFF Research Database (Denmark)

    Aldana Jague, Emilien; Heckrath, Goswin; Macdonald, Andy

    2016-01-01

    .g. shadows, tillage andwheels marks). After a projection in newdimensions by a PCA, we calibrated a support vector machine regression using observations fromconventional soil sampling and SOC measurements. The performance of the calibration had a R2 of 0.98 and a RMSE of 0.17%C. A crossvalidation showed...... that the model was robust, with an average R2 of 0.95 and a RMSE of 0.21%. An external validation dataset was used to evaluate the predicted spatial patterns of SOC content and a good fit with an RMSE 0.26%C was obtained. Although this study shows that the methodology has a clear potential for use in precision...

  9. Application of automatic image analysis in wood science

    Science.gov (United States)

    Charles W. McMillin

    1982-01-01

    In this paper I describe an image analysis system and illustrate with examples the application of automatic quantitative measurement to wood science. Automatic image analysis, a powerful and relatively new technology, uses optical, video, electronic, and computer components to rapidly derive information from images with minimal operator interaction. Such instruments...

  10. Brain-inspired algorithms for retinal image analysis

    NARCIS (Netherlands)

    ter Haar Romeny, B.M.; Bekkers, E.J.; Zhang, J.; Abbasi-Sureshjani, S.; Huang, F.; Duits, R.; Dasht Bozorg, Behdad; Berendschot, T.T.J.M.; Smit-Ockeloen, I.; Eppenhof, K.A.J.; Feng, J.; Hannink, J.; Schouten, J.; Tong, M.; Wu, H.; van Triest, J.W.; Zhu, S.; Chen, D.; He, W.; Xu, L.; Han, P.; Kang, Y.

    2016-01-01

    Retinal image analysis is a challenging problem due to the precise quantification required and the huge numbers of images produced in screening programs. This paper describes a series of innovative brain-inspired algorithms for automated retinal image analysis, recently developed for the RetinaCheck

  11. From Pixels to Geographic Objects in Remote Sensing Image Analysis

    NARCIS (Netherlands)

    Addink, E.A.; Van Coillie, Frieke M.B.; Jong, Steven M. de

    Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received

  12. An image scanner for real time analysis of spark chamber images

    International Nuclear Information System (INIS)

    Cesaroni, F.; Penso, G.; Locci, A.M.; Spano, M.A.

    1975-01-01

    The notes describes the semiautomatic scanning system at LNF for the analysis of spark chamber images. From the projection of the images on the scanner table, the trajectory in the real space is reconstructed

  13. Textural features for radar image analysis

    Science.gov (United States)

    Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

    1981-01-01

    Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

  14. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir; Tsvankin, Ilya; Alkhalifah, Tariq Ali

    2015-01-01

    velocity analysis remain generally valid in the extended image space for complex media. The dependence of RMO on errors in the anisotropy parameters provides essential insights for anisotropic wavefield tomography using extended images.

  15. Direct identification of fungi using image analysis

    DEFF Research Database (Denmark)

    Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian

    1999-01-01

    Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because of the sub......Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because...... of the subjectivity in the visual evaluation and quantification (if any)of such characters and the apparent large variability of the features. We present an image analysis approach for objective identification and classification of fungi. The approach is exemplified by several isolates of nine different species...... of the genus Penicillium, known to be very difficult to identify correctly. The fungi were incubated on YES and CYA for one week at 25 C (3 point inoculation) in 9 cm Petri dishes. The cultures are placed under a camera where a digital image of the front of the colonies is acquired under optimal illumination...

  16. Image sequence analysis in nuclear medicine: (1) Parametric imaging using statistical modelling

    International Nuclear Information System (INIS)

    Liehn, J.C.; Hannequin, P.; Valeyre, J.

    1989-01-01

    This is a review of parametric imaging methods on Nuclear Medicine. A Parametric Image is an image in which each pixel value is a function of the value of the same pixel of an image sequence. The Local Model Method is the fitting of each pixel time activity curve by a model which parameter values form the Parametric Images. The Global Model Method is the modelling of the changes between two images. It is applied to image comparison. For both methods, the different models, the identification criterion, the optimization methods and the statistical properties of the images are discussed. The analysis of one or more Parametric Images is performed using 1D or 2D histograms. The statistically significant Parametric Images, (Images of significant Variances, Amplitudes and Differences) are also proposed [fr

  17. Biostatistical analysis of quantitative immunofluorescence microscopy images.

    Science.gov (United States)

    Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

    2016-12-01

    Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

  18. Computerised image analysis of biocrystallograms originating from agricultural products

    DEFF Research Database (Denmark)

    Andersen, Jens-Otto; Henriksen, Christian B.; Laursen, J.

    1999-01-01

    Procedures are presented for computerised image analysis of iocrystallogram images, originating from biocrystallization investigations of agricultural products. The biocrystallization method is based on the crystallographic phenomenon that when adding biological substances, such as plant extracts...... on up to eight parameters indicated strong relationships, with R2 up to 0.98. It is concluded that the procedures were able to discriminate the seven groups of images, and are applicable for biocrystallization investigations of agricultural products. Perspectives for the application of image analysis...

  19. Image analysis and microscopy: a useful combination

    Directory of Open Access Journals (Sweden)

    Pinotti L.

    2009-01-01

    Full Text Available The TSE Roadmap published in 2005 (DG for Health and Consumer Protection, 2005 suggests that short and medium term (2005-2009 amendments to control BSE policy should include “a relaxation of certain measures of the current total feed ban when certain conditions are met”. The same document noted “the starting point when revising the current feed ban provisions should be risk-based but at the same time taking into account the control tools in place to evaluate and ensure the proper implementation of this feed ban”. The clear implication is that adequate analytical methods to detect constituents of animal origin in feedstuffs are required. The official analytical method for the detection of constituents of animal origin in feedstuffs is the microscopic examination technique as described in Commission Directive 2003/126/EC of 23 December 2003 [OJ L 339, 24.12.2003, 78]. Although the microscopic method is usually able to distinguish fish from land animal material, it is often unable to distinguish between different terrestrial animals. Fulfillments of the requirements of Regulation 1774/2002/EC laying down health rules concerning animal by-products not intended for human consumption, clearly implies that it must be possible to identify the origin animal materials, at higher taxonomic levels than in the past. Thus improvements in all methods of detecting constituents of animal origin are required, including the microscopic method. This article will examine the problem of meat and bone meal in animal feeds, and the use of microscopic methods in association with computer image analysis to identify the source species of these feedstuff contaminants. Image processing, integrated with morphometric measurements can provide accurate and reliable results and can be a very useful aid to the analyst in the characterization, analysis and control of feedstuffs.

  20. Forensic image analysis - CCTV distortion and artefacts.

    Science.gov (United States)

    Seckiner, Dilan; Mallett, Xanthé; Roux, Claude; Meuwly, Didier; Maynard, Philip

    2018-04-01

    As a result of the worldwide deployment of surveillance cameras, authorities have gained a powerful tool that captures footage of activities of people in public areas. Surveillance cameras allow continuous monitoring of the area and allow footage to be obtained for later use, if a criminal or other act of interest occurs. Following this, a forensic practitioner, or expert witness can be required to analyse the footage of the Person of Interest. The examination ultimately aims at evaluating the strength of evidence at source and activity levels. In this paper, both source and activity levels are inferred from the trace, obtained in the form of CCTV footage. The source level alludes to features observed within the anatomy and gait of an individual, whilst the activity level relates to activity undertaken by the individual within the footage. The strength of evidence depends on the value of the information recorded, where the activity level is robust, yet source level requires further development. It is therefore suggested that the camera and the associated distortions should be assessed first and foremost and, where possible, quantified, to determine the level of each type of distortion present within the footage. A review of the 'forensic image analysis' review is presented here. It will outline the image distortion types and detail the limitations of differing surveillance camera systems. The aim is to highlight various types of distortion present particularly from surveillance footage, as well as address gaps in current literature in relation to assessment of CCTV distortions in tandem with gait analysis. Future work will consider the anatomical assessment from surveillance footage. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Quantifying spatial variability of depth of peat burn in wetlands in relation to antecedent characteristics using field data, multi-temporal and multi-spectral LiDAR

    Science.gov (United States)

    Chasmer, L.; Flade, L.; Virk, R.; Montgomery, J. S.; Hopkinson, C.; Thompson, D. K.; Petrone, R. M.; Devito, K.

    2017-12-01

    Landscape changes in the hydrological characteristics of wetlands in some parts of the Boreal region of Canada are occurring as a result of climate-induced feedbacks and anthropogenic disturbance. Wetlands are largely resilient to wildfire, however, natural, climatic and anthropogenic disturbances can change surface water regimes and predispose wetlands to greater depth of peat burn. Over broad areas, peat loss contributes to significant pollution emissions, which can affect community health. In this study, we a) quantify depth of peat burn and relationships to antecedent conditions (species type, topography, surficial geology) within three classified wetlands found in the Boreal Plains ecoregion of western Canada; and b) examine the impacts of wildfire on post-fire ground surface energy balance to determine how peat loss might affect local hydro-climatology and surface water feedbacks. High-resolution optical imagery, pre- and post-burn multi-spectral Light Detection And Ranging (LiDAR), airborne thermal infrared imagery, and field validation data products are integrated to identify multiple complex interactions within the study wetlands. LiDAR-derived depth of peat burn is within 1 cm (average) compared with measured (RMSE = 9 cm over the control surface), demonstrating the utility of LiDAR with high point return density. Depth of burn also correlates strongly with variations in Normalised Burn Ratio (NBR) determined for ground surfaces only. Antecedent conditions including topographic position, soil moisture, soil type and wetland species also have complex interactions with depth of peat loss within wetlands observed in other studies. However, while field measurements are important for validation and understanding eco-hydrological processes, results from remote sensing are spatially continuous. Temporal LiDAR data illustrate the full range of variability in depth of burn and wetland characteristics following fire. Finally, measurements of instantaneous surface

  2. APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO RELAXOGRAPHIC IMAGES

    International Nuclear Information System (INIS)

    STOYANOVA, R.S.; OCHS, M.F.; BROWN, T.R.; ROONEY, W.D.; LI, X.; LEE, J.H.; SPRINGER, C.S.

    1999-01-01

    Standard analysis methods for processing inversion recovery MR images traditionally have used single pixel techniques. In these techniques each pixel is independently fit to an exponential recovery, and spatial correlations in the data set are ignored. By analyzing the image as a complete dataset, improved error analysis and automatic segmentation can be achieved. Here, the authors apply principal component analysis (PCA) to a series of relaxographic images. This procedure decomposes the 3-dimensional data set into three separate images and corresponding recovery times. They attribute the 3 images to be spatial representations of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) content

  3. Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

    Directory of Open Access Journals (Sweden)

    Kiuru Aaro

    2003-01-01

    Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

  4. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  5. Machine learning based analysis of cardiovascular images

    NARCIS (Netherlands)

    Wolterink, JM

    2017-01-01

    Cardiovascular diseases (CVDs), including coronary artery disease (CAD) and congenital heart disease (CHD) are the global leading cause of death. Computed tomography (CT) and magnetic resonance imaging (MRI) allow non-invasive imaging of cardiovascular structures. This thesis presents machine

  6. Analysis of Pregerminated Barley Using Hyperspectral Image Analysis

    DEFF Research Database (Denmark)

    Arngren, Morten; Hansen, Per Waaben; Eriksen, Birger

    2011-01-01

    imaging system in a mathematical modeling framework to identify pregerminated barley at an early stage of approximately 12 h of pregermination. Our model only assigns pregermination as the cause for a single kernel’s lack of germination and is unable to identify dormancy, kernel damage etc. The analysis...... is based on more than 750 Rosalina barley kernels being pregerminated at 8 different durations between 0 and 60 h based on the BRF method. Regerminating the kernels reveals a grouping of the pregerminated kernels into three categories: normal, delayed and limited germination. Our model employs a supervised...

  7. Image quality analysis of digital mammographic equipments

    Energy Technology Data Exchange (ETDEWEB)

    Mayo, P.; Pascual, A.; Verdu, G. [Valencia Univ. Politecnica, Chemical and Nuclear Engineering Dept. (Spain); Rodenas, F. [Valencia Univ. Politecnica, Applied Mathematical Dept. (Spain); Campayo, J.M. [Valencia Univ. Hospital Clinico, Servicio de Radiofisica y Proteccion Radiologica (Spain); Villaescusa, J.I. [Hospital Clinico La Fe, Servicio de Proteccion Radiologica, Valencia (Spain)

    2006-07-01

    The image quality assessment of a radiographic phantom image is one of the fundamental points in a complete quality control programme. The good functioning result of all the process must be an image with an appropriate quality to carry out a suitable diagnostic. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. Contrast-detail phantoms are applied to digital radiography to study the threshold contrast detail sensitivity at operation conditions of the equipment. The phantom that is studied in this work is C.D.M.A.M. 3.4, which facilitates the evaluation of image contrast and detail resolution. One of the most extended indexes to measure the image quality in an objective way is the Image Quality Figure (I.Q.F.). This parameter is useful to calculate the image quality taking into account the contrast and detail resolution of the image analysed. The contrast-detail curve is useful as a measure of the image quality too, because it is a graphical representation in which the hole thickness and diameter are plotted for each contrast-detail combination detected in the radiographic image of the phantom. It is useful for the comparison of the functioning of different radiographic image systems, for phantom images under the same exposition conditions. The aim of this work is to study the image quality of different images contrast-detail phantom C.D.M.A.M. 3.4, carrying out the automatic detection of the contrast-detail combination and to establish a parameter which characterize in an objective way the mammographic image quality. This is useful to compare images obtained at different digital mammographic equipments to study the functioning of the equipments. (authors)

  8. Image quality analysis of digital mammographic equipments

    International Nuclear Information System (INIS)

    Mayo, P.; Pascual, A.; Verdu, G.; Rodenas, F.; Campayo, J.M.; Villaescusa, J.I.

    2006-01-01

    The image quality assessment of a radiographic phantom image is one of the fundamental points in a complete quality control programme. The good functioning result of all the process must be an image with an appropriate quality to carry out a suitable diagnostic. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. Contrast-detail phantoms are applied to digital radiography to study the threshold contrast detail sensitivity at operation conditions of the equipment. The phantom that is studied in this work is C.D.M.A.M. 3.4, which facilitates the evaluation of image contrast and detail resolution. One of the most extended indexes to measure the image quality in an objective way is the Image Quality Figure (I.Q.F.). This parameter is useful to calculate the image quality taking into account the contrast and detail resolution of the image analysed. The contrast-detail curve is useful as a measure of the image quality too, because it is a graphical representation in which the hole thickness and diameter are plotted for each contrast-detail combination detected in the radiographic image of the phantom. It is useful for the comparison of the functioning of different radiographic image systems, for phantom images under the same exposition conditions. The aim of this work is to study the image quality of different images contrast-detail phantom C.D.M.A.M. 3.4, carrying out the automatic detection of the contrast-detail combination and to establish a parameter which characterize in an objective way the mammographic image quality. This is useful to compare images obtained at different digital mammographic equipments to study the functioning of the equipments. (authors)

  9. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen

    2016-01-01

    Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

  10. Principal component analysis of psoriasis lesions images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    A set of RGB images of psoriasis lesions is used. By visual examination of these images, there seem to be no common pattern that could be used to find and align the lesions within and between sessions. It is expected that the principal components of the original images could be useful during future...

  11. An application of image processing techniques in computed tomography image analysis

    DEFF Research Database (Denmark)

    McEvoy, Fintan

    2007-01-01

    number of animals and image slices, automation of the process was desirable. The open-source and free image analysis program ImageJ was used. A macro procedure was created that provided the required functionality. The macro performs a number of basic image processing procedures. These include an initial...... process designed to remove the scanning table from the image and to center the animal in the image. This is followed by placement of a vertical line segment from the mid point of the upper border of the image to the image center. Measurements are made between automatically detected outer and inner...... boundaries of subcutaneous adipose tissue along this line segment. This process was repeated as the image was rotated (with the line position remaining unchanged) so that measurements around the complete circumference were obtained. Additionally, an image was created showing all detected boundary points so...

  12. Towards real-time non contact spatial resolved oxygenation monitoring using a multi spectral filter array camera in various light conditions

    Science.gov (United States)

    Bauer, Jacob R.; van Beekum, Karlijn; Klaessens, John; Noordmans, Herke Jan; Boer, Christa; Hardeberg, Jon Y.; Verdaasdonk, Rudolf M.

    2018-02-01

    Non contact spatial resolved oxygenation measurements remain an open challenge in the biomedical field and non contact patient monitoring. Although point measurements are the clinical standard till this day, regional differences in the oxygenation will improve the quality and safety of care. Recent developments in spectral imaging resulted in spectral filter array cameras (SFA). These provide the means to acquire spatial spectral videos in real-time and allow a spatial approach to spectroscopy. In this study, the performance of a 25 channel near infrared SFA camera was studied to obtain spatial oxygenation maps of hands during an occlusion of the left upper arm in 7 healthy volunteers. For comparison a clinical oxygenation monitoring system, INVOS, was used as a reference. In case of the NIRS SFA camera, oxygenation curves were derived from 2-3 wavelength bands with a custom made fast analysis software using a basic algorithm. Dynamic oxygenation changes were determined with the NIR SFA camera and INVOS system at different regional locations of the occluded versus non-occluded hands and showed to be in good agreement. To increase the signal to noise ratio, algorithm and image acquisition were optimised. The measurement were robust to different illumination conditions with NIR light sources. This study shows that imaging of relative oxygenation changes over larger body areas is potentially possible in real time.

  13. An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

    Science.gov (United States)

    Kim, Yongmin; Alexander, Thomas

    1986-06-01

    In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

  14. Towards automatic quantitative analysis of cardiac MR perfusion images

    NARCIS (Netherlands)

    Breeuwer, M.; Quist, M.; Spreeuwers, Lieuwe Jan; Paetsch, I.; Al-Saadi, N.; Nagel, E.

    2001-01-01

    Magnetic Resonance Imaging (MRI) is a powerful technique for imaging cardiovascular diseases. The introduction of cardiovascular MRI into clinical practice is however hampered by the lack of efficient and reliable automatic image analysis methods. This paper focuses on the automatic evaluation of

  15. Subsurface offset behaviour in velocity analysis with extended reflectivity images

    NARCIS (Netherlands)

    Mulder, W.A.

    2013-01-01

    Migration velocity analysis with the constant-density acoustic wave equation can be accomplished by the focusing of extended migration images, obtained by introducing a subsurface shift in the imaging condition. A reflector in a wrong velocity model will show up as a curve in the extended image. In

  16. Visual Analytics Applied to Image Analysis : From Segmentation to Classification

    NARCIS (Netherlands)

    Rauber, Paulo

    2017-01-01

    Image analysis is the field of study concerned with extracting information from images. This field is immensely important for commercial and scientific applications, from identifying people in photographs to recognizing diseases in medical images. The goal behind the work presented in this thesis is

  17. Mesh Processing in Medical-Image Analysis-a Tutorial

    DEFF Research Database (Denmark)

    Levine, Joshua A.; Paulsen, Rasmus Reinhold; Zhang, Yongjie

    2012-01-01

    Medical-image analysis requires an understanding of sophisticated scanning modalities, constructing geometric models, building meshes to represent domains, and downstream biological applications. These four steps form an image-to-mesh pipeline. For research in this field to progress, the imaging...

  18. Intrasubject registration for change analysis in medical imaging

    NARCIS (Netherlands)

    Staring, M.

    2008-01-01

    Image matching is important for the comparison of medical images. Comparison is of clinical relevance for the analysis of differences due to changes in the health of a patient. For example, when a disease is imaged at two time points, then one wants to know if it is stable, has regressed, or

  19. The use of a multilayer perceptron for detecting new human settlements from a time series of MODIS images

    CSIR Research Space (South Africa)

    Salmon, BP

    2011-12-01

    Full Text Available This paper presents a novel land cover change detection method that employs a sliding window over hyper-temporal multi-spectral images acquired from the 7 bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance...

  20. Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data

    Science.gov (United States)

    Ghrefat, Habes A.; Goodell, Philip C.

    2011-08-01

    The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen

  1. Image quality preferences among radiographers and radiologists. A conjoint analysis

    International Nuclear Information System (INIS)

    Ween, Borgny; Kristoffersen, Doris Tove; Hamilton, Glenys A.; Olsen, Dag Rune

    2005-01-01

    Purpose: The aim of this study was to investigate the image quality preferences among radiographers and radiologists. The radiographers' preferences are mainly related to technical parameters, whereas radiologists assess image quality based on diagnostic value. Methods: A conjoint analysis was undertaken to survey image quality preferences; the study included 37 respondents: 19 radiographers and 18 radiologists. Digital urograms were post-processed into 8 images with different properties of image quality for 3 different patients. The respondents were asked to rank the images according to their personally perceived subjective image quality. Results: Nearly half of the radiographers and radiologists were consistent in their ranking of the image characterised as 'very best image quality'. The analysis showed, moreover, that chosen filtration level and image intensity were responsible for 72% and 28% of the preferences, respectively. The corresponding figures for each of the two professions were 76% and 24% for the radiographers, and 68% and 32% for the radiologists. In addition, there were larger variations in image preferences among the radiologists, as compared to the radiographers. Conclusions: Radiographers revealed a more consistent preference than the radiologists with respect to image quality. There is a potential for image quality improvement by developing sets of image property criteria

  2. Convergence analysis in near-field imaging

    International Nuclear Information System (INIS)

    Bao, Gang; Li, Peijun

    2014-01-01

    This paper is devoted to the mathematical analysis of the direct and inverse modeling of the diffraction by a perfectly conducting grating surface in the near-field regime. It is motivated by our effort to analyze recent significant numerical results, in order to solve a class of inverse rough surface scattering problems in near-field imaging. In a model problem, the diffractive grating surface is assumed to be a small and smooth deformation of a plane surface. On the basis of the variational method, the direct problem is shown to have a unique weak solution. An analytical solution is introduced as a convergent power series in the deformation parameter by using the transformed field and Fourier series expansions. A local uniqueness result is proved for the inverse problem where only a single incident field is needed. On the basis of the analytic solution of the direct problem, an explicit reconstruction formula is presented for recovering the grating surface function with resolution beyond the Rayleigh criterion. Error estimates for the reconstructed grating surface are established with fully revealed dependence on such quantities as the surface deformation parameter, measurement distance, noise level of the scattering data, and regularity of the exact grating surface function. (paper)

  3. IMAGE ANALYSIS FOR MODELLING SHEAR BEHAVIOUR

    Directory of Open Access Journals (Sweden)

    Philippe Lopez

    2011-05-01

    Full Text Available Through laboratory research performed over the past ten years, many of the critical links between fracture characteristics and hydromechanical and mechanical behaviour have been made for individual fractures. One of the remaining challenges at the laboratory scale is to directly link fracture morphology of shear behaviour with changes in stress and shear direction. A series of laboratory experiments were performed on cement mortar replicas of a granite sample with a natural fracture perpendicular to the axis of the core. Results show that there is a strong relationship between the fracture's geometry and its mechanical behaviour under shear stress and the resulting damage. Image analysis, geostatistical, stereological and directional data techniques are applied in combination to experimental data. The results highlight the role of geometric characteristics of the fracture surfaces (surface roughness, size, shape, locations and orientations of asperities to be damaged in shear behaviour. A notable improvement in shear understanding is that shear behaviour is controlled by the apparent dip in the shear direction of elementary facets forming the fracture.

  4. Adjustment of Sentinel-2 Multi-Spectral Instrument (MSI) Red-Edge Band Reflectance to Nadir BRDF Adjusted Reflectance (NBAR) and Quantification of Red-Edge Band BRDF Effects

    OpenAIRE

    David P. Roy; Zhongbin Li; Hankui K. Zhang

    2017-01-01

    Optical wavelength satellite data have directional reflectance effects over non-Lambertian surfaces, described by the bidirectional reflectance distribution function (BRDF). The Sentinel-2 multi-spectral instrument (MSI) acquires data over a 20.6° field of view that have been shown to have non-negligible BRDF effects in the visible, near-infrared, and short wave infrared bands. MSI red-edge BRDF effects have not been investigated. In this study, they are quantified by an examination of 6.6 mi...

  5. Measure by image analysis of industrial radiographs

    International Nuclear Information System (INIS)

    Brillault, B.

    1988-01-01

    A digital radiographic picture processing system for non destructive testing intends to provide the expert with computer tool, to precisely quantify radiographic images. The author describes the main problems, from the image formation to its characterization. She also insists on the necessity to define a precise process in order to automatize the system. Some examples illustrate the efficiency of digital processing for radiographic images [fr

  6. MORPHOLOGY BY IMAGE ANALYSIS K. Belaroui and M. N Pons ...

    African Journals Online (AJOL)

    31 déc. 2012 ... Keywords: Characterization; particle size; morphology; image analysis; porous media. 1. INTRODUCTION. La puissance de l'analyse d'images comme ... en une image numérique au moyen d'un convertisseur analogique digital (A/D). Les points de l'image sont disposés suivant une grille en réseau carré, ...

  7. PIZZARO: Forensic analysis and restoration of image and video data

    Czech Academy of Sciences Publication Activity Database

    Kamenický, Jan; Bartoš, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozámský, Adam; Saic, Stanislav; Šroubek, Filip; Šorel, Michal; Zita, Aleš; Zitová, Barbara; Šíma, Z.; Švarc, P.; Hořínek, J.

    2016-01-01

    Roč. 264, č. 1 (2016), s. 153-166 ISSN 0379-0738 R&D Projects: GA MV VG20102013064; GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Image forensic analysis * Image restoration * Image tampering detection * Image source identification Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.989, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/kamenicky-0459504.pdf

  8. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi

    2016-01-01

    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  9. Analysis of engineering drawings and raster map images

    CERN Document Server

    Henderson, Thomas C

    2013-01-01

    Presents up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps Discusses automatic engineering drawing and map analysis techniques Covers detailed accounts of the use of unsupervised segmentation algorithms to map images

  10. 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 ...

  11. An introduction to diffusion tensor image analysis.

    Science.gov (United States)

    O'Donnell, Lauren J; Westin, Carl-Fredrik

    2011-04-01

    Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. Biomedical Image Analysis: Rapid prototyping with Mathematica

    NARCIS (Netherlands)

    Haar Romenij, ter B.M.; Almsick, van M.A.

    2004-01-01

    Digital acquisition techniques have caused an explosion in the production of medical images, especially with the advent of multi-slice CT and volume MRI. One third of the financial investments in a modern hospital's equipment are dedicated to imaging. Emerging screening programs add to this flood of

  13. Geographic Object-Based Image Analysis: Towards a new paradigm

    NARCIS (Netherlands)

    Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.A.|info:eu-repo/dai/nl/224281216; Queiroz Feitosa, R.; van der Meer, F.D.|info:eu-repo/dai/nl/138940908; van der Werff, H.M.A.; van Coillie, F.; Tiede, A.

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature

  14. A short introduction to image analysis - Matlab exercises

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg

    2000-01-01

    This document contain a short introduction to Image analysis. In addition small exercises has been prepared in order to support the theoretical understanding.......This document contain a short introduction to Image analysis. In addition small exercises has been prepared in order to support the theoretical understanding....

  15. Analysis of licensed South African diagnostic imaging equipment ...

    African Journals Online (AJOL)

    Analysis of licensed South African diagnostic imaging equipment. ... Pan African Medical Journal ... Introduction: Objective: To conduct an analysis of all registered South Africa (SA) diagnostic radiology equipment, assess the number of equipment units per capita by imaging modality, and compare SA figures with published ...

  16. Vision communications based on LED array and imaging sensor

    Science.gov (United States)

    Yoo, Jong-Ho; Jung, Sung-Yoon

    2012-11-01

    In this paper, we propose a brand new communication concept, called as "vision communication" based on LED array and image sensor. This system consists of LED array as a transmitter and digital device which include image sensor such as CCD and CMOS as receiver. In order to transmit data, the proposed communication scheme simultaneously uses the digital image processing and optical wireless communication scheme. Therefore, the cognitive communication scheme is possible with the help of recognition techniques used in vision system. By increasing data rate, our scheme can use LED array consisting of several multi-spectral LEDs. Because arranged each LED can emit multi-spectral optical signal such as visible, infrared and ultraviolet light, the increase of data rate is possible similar to WDM and MIMO skills used in traditional optical and wireless communications. In addition, this multi-spectral capability also makes it possible to avoid the optical noises in communication environment. In our vision communication scheme, the data packet is composed of Sync. data and information data. Sync. data is used to detect the transmitter area and calibrate the distorted image snapshots obtained by image sensor. By making the optical rate of LED array be same with the frame rate (frames per second) of image sensor, we can decode the information data included in each image snapshot based on image processing and optical wireless communication techniques. Through experiment based on practical test bed system, we confirm the feasibility of the proposed vision communications based on LED array and image sensor.

  17. Analysis of sharpness increase by image noise

    Science.gov (United States)

    Kurihara, Takehito; Aoki, Naokazu; Kobayashi, Hiroyuki

    2009-02-01

    Motivated by the reported increase in sharpness by image noise, we investigated how noise affects sharpness perception. We first used natural images of tree bark with different amounts of noise to see whether noise enhances sharpness. Although the result showed sharpness decreased as noise amount increased, some observers seemed to perceive more sharpness with increasing noise, while the others did not. We next used 1D and 2D uni-frequency patterns as stimuli in an attempt to reduce such variability in the judgment. The result showed, for higher frequency stimuli, sharpness decreased as the noise amount increased, while sharpness of the lower frequency stimuli increased at a certain noise level. From this result, we thought image noise might reduce sharpness at edges, but be able to improve sharpness of lower frequency component or texture in image. To prove this prediction, we experimented again with the natural image used in the first experiment. Stimuli were made by applying noise separately to edge or to texture part of the image. The result showed noise, when added to edge region, only decreased sharpness, whereas when added to texture, could improve sharpness. We think it is the interaction between noise and texture that sharpens image.

  18. IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆

    2002-01-01

    A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.

  19. Photoacoustic image reconstruction: a quantitative analysis

    Science.gov (United States)

    Sperl, Jonathan I.; Zell, Karin; Menzenbach, Peter; Haisch, Christoph; Ketzer, Stephan; Marquart, Markus; Koenig, Hartmut; Vogel, Mika W.

    2007-07-01

    Photoacoustic imaging is a promising new way to generate unprecedented contrast in ultrasound diagnostic imaging. It differs from other medical imaging approaches, in that it provides spatially resolved information about optical absorption of targeted tissue structures. Because the data acquisition process deviates from standard clinical ultrasound, choice of the proper image reconstruction method is crucial for successful application of the technique. In the literature, multiple approaches have been advocated, and the purpose of this paper is to compare four reconstruction techniques. Thereby, we focused on resolution limits, stability, reconstruction speed, and SNR. We generated experimental and simulated data and reconstructed images of the pressure distribution using four different methods: delay-and-sum (DnS), circular backprojection (CBP), generalized 2D Hough transform (HTA), and Fourier transform (FTA). All methods were able to depict the point sources properly. DnS and CBP produce blurred images containing typical superposition artifacts. The HTA provides excellent SNR and allows a good point source separation. The FTA is the fastest and shows the best FWHM. In our study, we found the FTA to show the best overall performance. It allows a very fast and theoretically exact reconstruction. Only a hardware-implemented DnS might be faster and enable real-time imaging. A commercial system may also perform several methods to fully utilize the new contrast mechanism and guarantee optimal resolution and fidelity.

  20. Rapid, low-cost, image analysis through video processing

    International Nuclear Information System (INIS)

    Levinson, R.A.; Marrs, R.W.; Grantham, D.G.

    1976-01-01

    Remote Sensing now provides the data necessary to solve many resource problems. However, many of the complex image processing and analysis functions used in analysis of remotely-sensed data are accomplished using sophisticated image analysis equipment. High cost of this equipment places many of these techniques beyond the means of most users. A new, more economical, video system capable of performing complex image analysis has now been developed. This report describes the functions, components, and operation of that system. Processing capability of the new video image analysis system includes many of the tasks previously accomplished with optical projectors and digital computers. Video capabilities include: color separation, color addition/subtraction, contrast stretch, dark level adjustment, density analysis, edge enhancement, scale matching, image mixing (addition and subtraction), image ratioing, and construction of false-color composite images. Rapid input of non-digital image data, instantaneous processing and display, relatively low initial cost, and low operating cost gives the video system a competitive advantage over digital equipment. Complex pre-processing, pattern recognition, and statistical analyses must still be handled through digital computer systems. The video system at the University of Wyoming has undergone extensive testing, comparison to other systems, and has been used successfully in practical applications ranging from analysis of x-rays and thin sections to production of color composite ratios of multispectral imagery. Potential applications are discussed including uranium exploration, petroleum exploration, tectonic studies, geologic mapping, hydrology sedimentology and petrography, anthropology, and studies on vegetation and wildlife habitat

  1. Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis

    Science.gov (United States)

    Vest, Joshua R.; Jung, Hye-Young; Ostrovsky, Aaron; Das, Lala Tanmoy; McGinty, Geraldine B.

    2016-01-01

    Introduction Image sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization. Methods Quantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004–2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models. Results A total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = −0.17; 95% confidence interval [CI] = [−0.25, −0.09]; P utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias. Conclusions Image sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings. PMID:26614882

  2. Vector sparse representation of color image using quaternion matrix analysis.

    Science.gov (United States)

    Xu, Yi; Yu, Licheng; Xu, Hongteng; Zhang, Hao; Nguyen, Truong

    2015-04-01

    Traditional sparse image models treat color image pixel as a scalar, which represents color channels separately or concatenate color channels as a monochrome image. In this paper, we propose a vector sparse representation model for color images using quaternion matrix analysis. As a new tool for color image representation, its potential applications in several image-processing tasks are presented, including color image reconstruction, denoising, inpainting, and super-resolution. The proposed model represents the color image as a quaternion matrix, where a quaternion-based dictionary learning algorithm is presented using the K-quaternion singular value decomposition (QSVD) (generalized K-means clustering for QSVD) method. It conducts the sparse basis selection in quaternion space, which uniformly transforms the channel images to an orthogonal color space. In this new color space, it is significant that the inherent color structures can be completely preserved during vector reconstruction. Moreover, the proposed sparse model is more efficient comparing with the current sparse models for image restoration tasks due to lower redundancy between the atoms of different color channels. The experimental results demonstrate that the proposed sparse image model avoids the hue bias issue successfully and shows its potential as a general and powerful tool in color image analysis and processing domain.

  3. Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

    Science.gov (United States)

    Navarro, Gabriel; Vicent, Jorge; Caballero, Isabel; Gómez-Enri, Jesús; Morris, Edward P.; Sabater, Neus; Macías, Diego; Bolado-Penagos, Marina; Gomiz, Juan Jesús; Bruno, Miguel; Caldeira, Rui; Vázquez, Águeda

    2018-05-01

    High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the aim of examining the influence of HAIWs on biogeochemical processes. We used hyperspectral images from the Hyperspectral Imager for the Coastal Ocean (HICO) and high spatial resolution (10 m) images from the MultiSpectral Instrument (MSI) onboard the Sentinel-2A satellite. This work represents the first attempt to examine the relation between internal wave generation and the water constituents of the Camarinal Sill using hyperspectral and high spatial resolution remote sensing images. This enhanced spatial and spectral resolution revealed the detailed biogeochemical patterns associated with the internal waves and suggests local enhancements of productivity associated with internal waves trains.

  4. Interpretation of medical images by model guided analysis

    International Nuclear Information System (INIS)

    Karssemeijer, N.

    1989-01-01

    Progress in the development of digital pictorial information systems stimulates a growing interest in the use of image analysis techniques in medicine. Especially when precise quantitative information is required the use of fast and reproducable computer analysis may be more appropriate than relying on visual judgement only. Such quantitative information can be valuable, for instance, in diagnostics or in irradiation therapy planning. As medical images are mostly recorded in a prescribed way, human anatomy guarantees a common image structure for each particular type of exam. In this thesis it is investigated how to make use of this a priori knowledge to guide image analysis. For that purpose models are developed which are suited to capture common image structure. The first part of this study is devoted to an analysis of nuclear medicine images of myocardial perfusion. In ch. 2 a model of these images is designed in order to represent characteristic image properties. It is shown that for these relatively simple images a compact symbolic description can be achieved, without significant loss of diagnostically importance of several image properties. Possibilities for automatic interpretation of more complex images is investigated in the following chapters. The central topic is segmentation of organs. Two methods are proposed and tested on a set of abdominal X-ray CT scans. Ch. 3 describes a serial approach based on a semantic network and the use of search areas. Relational constraints are used to guide the image processing and to classify detected image segments. In teh ch.'s 4 and 5 a more general parallel approach is utilized, based on a markov random field image model. A stochastic model used to represent prior knowledge about the spatial arrangement of organs is implemented as an external field. (author). 66 refs.; 27 figs.; 6 tabs

  5. Multifractal analysis of three-dimensional histogram from color images

    International Nuclear Information System (INIS)

    Chauveau, Julien; Rousseau, David; Richard, Paul; Chapeau-Blondeau, Francois

    2010-01-01

    Natural images, especially color or multicomponent images, are complex information-carrying signals. To contribute to the characterization of this complexity, we investigate the possibility of multiscale organization in the colorimetric structure of natural images. This is realized by means of a multifractal analysis applied to the three-dimensional histogram from natural color images. The observed behaviors are confronted to those of reference models with known multifractal properties. We use for this purpose synthetic random images with trivial monofractal behavior, and multidimensional multiplicative cascades known for their actual multifractal behavior. The behaviors observed on natural images exhibit similarities with those of the multifractal multiplicative cascades and display the signature of elaborate multiscale organizations stemming from the histograms of natural color images. This type of characterization of colorimetric properties can be helpful to various tasks of digital image processing, as for instance modeling, classification, indexing.

  6. Knowledge-based image analysis: some aspects on the analysis of images using other types of information

    Energy Technology Data Exchange (ETDEWEB)

    Eklundh, J O

    1982-01-01

    The computer vision approach to image analysis is discussed from two aspects. First, this approach is constrasted to the pattern recognition approach. Second, how external knowledge and information and models from other fields of science and engineering can be used for image and scene analysis is discussed. In particular, the connections between computer vision and computer graphics are pointed out.

  7. Introducing PLIA: Planetary Laboratory for Image Analysis

    Science.gov (United States)

    Peralta, J.; Hueso, R.; Barrado, N.; Sánchez-Lavega, A.

    2005-08-01

    We present a graphical software tool developed under IDL software to navigate, process and analyze planetary images. The software has a complete Graphical User Interface and is cross-platform. It can also run under the IDL Virtual Machine without the need to own an IDL license. The set of tools included allow image navigation (orientation, centring and automatic limb determination), dynamical and photometric atmospheric measurements (winds and cloud albedos), cylindrical and polar projections, as well as image treatment under several procedures. Being written in IDL, it is modular and easy to modify and grow for adding new capabilities. We show several examples of the software capabilities with Galileo-Venus observations: Image navigation, photometrical corrections, wind profiles obtained by cloud tracking, cylindrical projections and cloud photometric measurements. Acknowledgements: This work has been funded by Spanish MCYT PNAYA2003-03216, fondos FEDER and Grupos UPV 15946/2004. R. Hueso acknowledges a post-doc fellowship from Gobierno Vasco.

  8. Applying Image Matching to Video Analysis

    Science.gov (United States)

    2010-09-01

    image groups, classified by the background scene, are the flag, the kitchen, the telephone, the bookshelf , the title screen, the...Kitchen 136 Telephone 3 Bookshelf 81 Title Screen 10 Map 1 24 Map 2 16 command line. This implementation of a Bloom filter uses two arbitrary...with the Bookshelf images. This scene is a much closer shot than the Kitchen scene so the host occupies much of the background. Algorithms for face

  9. Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

    Science.gov (United States)

    Perez-Sanz, Fernando; Navarro, Pedro J; Egea-Cortines, Marcos

    2017-11-01

    The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. © The Author 2017. Published by Oxford University Press.

  10. Diagnostic imaging analysis of the impacted mesiodens

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Jeong Jun; Choi, Bo Ram; Jeong, Hwan Seok; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul [School of Dentistry, Seoul National University, Seoul (Korea, Republic of)

    2010-06-15

    The research was performed to predict the three dimensional relationship between the impacted mesiodens and the maxillary central incisors and the proximity with the anatomic structures by comparing their panoramic images with the CT images. Among the patients visiting Seoul National University Dental Hospital from April 2003 to July 2007, those with mesiodens were selected (154 mesiodens of 120 patients). The numbers, shapes, orientation and positional relationship of mesiodens with maxillary central incisors were investigated in the panoramic images. The proximity with the anatomical structures and complications were investigated in the CT images as well. The sex ratio (M : F) was 2.28 : 1 and the mean number of mesiodens per one patient was 1.28. Conical shape was 84.4% and inverted orientation was 51.9%. There were more cases of anatomical structures encroachment, especially on the nasal floor and nasopalatine duct, when the mesiodens was not superimposed with the central incisor. There were, however, many cases of the nasopalatine duct encroachment when the mesiodens was superimpoised with the apical 1/3 of central incisor (52.6%). Delayed eruption (55.6%), crown rotation (66.7%) and crown resorption (100%) were observed when the mesiodens was superimposed with the crown of the central incisor. It is possible to predict three dimensional relationship between the impacted mesiodens and the maxillary central incisors in the panoramic images, but more details should be confirmed by the CT images when necessary.

  11. An image analysis system for near-infrared (NIR) fluorescence lymph imaging

    Science.gov (United States)

    Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

    2011-03-01

    Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

  12. Theoretical analysis of radiographic images by nonstationary Poisson processes

    International Nuclear Information System (INIS)

    Tanaka, Kazuo; Uchida, Suguru; Yamada, Isao.

    1980-01-01

    This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process. (author)

  13. Automated thermal mapping techniques using chromatic image analysis

    Science.gov (United States)

    Buck, Gregory M.

    1989-01-01

    Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

  14. Quantitative methods for the analysis of electron microscope images

    DEFF Research Database (Denmark)

    Skands, Peter Ulrik Vallø

    1996-01-01

    The topic of this thesis is an general introduction to quantitative methods for the analysis of digital microscope images. The images presented are primarily been acquired from Scanning Electron Microscopes (SEM) and interfermeter microscopes (IFM). The topic is approached though several examples...... foundation of the thesis fall in the areas of: 1) Mathematical Morphology; 2) Distance transforms and applications; and 3) Fractal geometry. Image analysis opens in general the possibility of a quantitative and statistical well founded measurement of digital microscope images. Herein lies also the conditions...

  15. Methods for processing and analysis functional and anatomical brain images: computerized tomography, emission tomography and nuclear resonance imaging

    International Nuclear Information System (INIS)

    Mazoyer, B.M.

    1988-01-01

    The various methods for brain image processing and analysis are presented and compared. The following topics are developed: the physical basis of brain image comparison (nature and formation of signals intrinsic performance of the methods image characteristics); mathematical methods for image processing and analysis (filtering, functional parameter extraction, morphological analysis, robotics and artificial intelligence); methods for anatomical localization (neuro-anatomy atlas, proportional stereotaxic atlas, numerized atlas); methodology of cerebral image superposition (normalization, retiming); image networks [fr

  16. Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

    Science.gov (United States)

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

    2016-05-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  17. Image Harvest: an open-source platform for high-throughput plant image processing and analysis

    Science.gov (United States)

    Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

    2016-01-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

  18. 5-ALA induced fluorescent image analysis of actinic keratosis

    Science.gov (United States)

    Cho, Yong-Jin; Bae, Youngwoo; Choi, Eung-Ho; Jung, Byungjo

    2010-02-01

    In this study, we quantitatively analyzed 5-ALA induced fluorescent images of actinic keratosis using digital fluorescent color and hyperspectral imaging modalities. UV-A was utilized to induce fluorescent images and actinic keratosis (AK) lesions were demarcated from surrounding the normal region with different methods. Eight subjects with AK lesion were participated in this study. In the hyperspectral imaging modality, spectral analysis method was utilized for hyperspectral cube image and AK lesions were demarcated from the normal region. Before image acquisition, we designated biopsy position for histopathology of AK lesion and surrounding normal region. Erythema index (E.I.) values on both regions were calculated from the spectral cube data. Image analysis of subjects resulted in two different groups: the first group with the higher fluorescence signal and E.I. on AK lesion than the normal region; the second group with lower fluorescence signal and without big difference in E.I. between two regions. In fluorescent color image analysis of facial AK, E.I. images were calculated on both normal and AK lesions and compared with the results of hyperspectral imaging modality. The results might indicate that the different intensity of fluorescence and E.I. among the subjects with AK might be interpreted as different phases of morphological and metabolic changes of AK lesions.

  19. Rapid analysis and exploration of fluorescence microscopy images.

    Science.gov (United States)

    Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

    2014-03-19

    Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

  20. Research of second harmonic generation images based on texture analysis

    Science.gov (United States)

    Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan

    2014-09-01

    Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

  1. Multi-spectral and thermodynamic analysis of the interaction mechanism between Cu2+ and α-amylase and impact on sludge hydrolysis.

    Science.gov (United States)

    Zhou, Ruiqi; Liu, Hong; Hou, Guangying; Ju, Lei; Liu, Chunguang

    2017-04-01

    An increasing amount of heavy metals (e.g., Cu 2+ ) is being discharged into sewage treatment plants and is accumulating in sludge, which is toxic to the enzyme in sludge or soil when the sludge is used as fertilizer, resulting in unfavorable effect on the biological treatment of sludge and the circulation and conversion of materials in soil. In this research, effect of Cu 2+ on sludge hydrolysis by α-amylase is studied from the respect of concentration and components of soluble organic matter in sludge, using three-dimensional fluorescence spectra. Results show that Cu 2+ exposure not only inhibits the hydrolysis of sludge due to the denaturation of α-amylase but also affects the components of soluble organic matter in sludge. In order to illuminate the interaction mechanism between Cu 2+ and α-amylase (a model of hydrolase in sludge), multi-spectra and isothermal titration microcalorimetry techniques are applied. Results show that the secondary structure of α-amylase is changed as that the α-helical content increases and the structure loosens. The microenvironment of amino acid residue in α-amylase is changed that the hydrophobicity decreases and the polarity increases with Cu 2+ exposure. Isothermal titration calorimetry results show that Van der Waals force and hydrogen bond exist in the interaction between Cu 2+ and α-amylase. Results from this research would favor the development of advanced process for the biological treatment of sludge containing heavy metals.

  2. Uncooled LWIR imaging: applications and market analysis

    Science.gov (United States)

    Takasawa, Satomi

    2015-05-01

    The evolution of infrared (IR) imaging sensor technology for defense market has played an important role in developing commercial market, as dual use of the technology has expanded. In particular, technologies of both reduction in pixel pitch and vacuum package have drastically evolved in the area of uncooled Long-Wave IR (LWIR; 8-14 μm wavelength region) imaging sensor, increasing opportunity to create new applications. From the macroscopic point of view, the uncooled LWIR imaging market is divided into two areas. One is a high-end market where uncooled LWIR imaging sensor with sensitivity as close to that of cooled one as possible is required, while the other is a low-end market which is promoted by miniaturization and reduction in price. Especially, in the latter case, approaches towards consumer market have recently appeared, such as applications of uncooled LWIR imaging sensors to night visions for automobiles and smart phones. The appearance of such a kind of commodity surely changes existing business models. Further technological innovation is necessary for creating consumer market, and there will be a room for other companies treating components and materials such as lens materials and getter materials and so on to enter into the consumer market.

  3. Digital image processing and analysis human and computer vision applications with CVIPtools

    CERN Document Server

    Umbaugh, Scott E

    2010-01-01

    Section I Introduction to Digital Image Processing and AnalysisDigital Image Processing and AnalysisOverviewImage Analysis and Computer VisionImage Processing and Human VisionKey PointsExercisesReferencesFurther ReadingComputer Imaging SystemsImaging Systems OverviewImage Formation and SensingCVIPtools SoftwareImage RepresentationKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSection II Digital Image Analysis and Computer VisionIntroduction to Digital Image AnalysisIntroductionPreprocessingBinary Image AnalysisKey PointsExercisesSupplementary ExercisesReferencesFurther Read

  4. Analysis of live cell images: Methods, tools and opportunities.

    Science.gov (United States)

    Nketia, Thomas A; Sailem, Heba; Rohde, Gustavo; Machiraju, Raghu; Rittscher, Jens

    2017-02-15

    Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug development. Image analysis methods are needed to extract quantitative information from these vast and complex data sets. The aim of this review is to provide an overview of available image analysis methods for live cell imaging, in particular required preprocessing image segmentation, cell tracking and data visualisation methods. The potential opportunities recent advances in machine learning, especially deep learning, and computer vision provide are being discussed. This review includes overview of the different available software packages and toolkits. Copyright © 2017. Published by Elsevier Inc.

  5. Analysis of the gammaholographic image formation

    International Nuclear Information System (INIS)

    Fonroget, J.; Roucayrol, J.C.; Perrin, J.; Belvaux, Y.; Paris-11 Univ., 91 - Orsay

    1975-01-01

    Gammaholography, or coded opening gammagraphy, is a new gammagraphic method in which the standard collimators are replaced by one or more modulator screens placed between the detector and the radioactive object. The recording obtained is a coded image or incoherent hologram which contains three-dimensional information on the object and can be decoded analogically in a very short time. The formation of the image has been analyzed in the coding and optical decoding phases in the case of a single coding screen modulated according to a Fresnel zoned lattice. The analytical expression established for the modulation transfer function (MTF) of the system can be used to study, by computerized simulation, the influence of the number of zones on the quality of the image [fr

  6. Imaging analysis of dedifferentiated chondrosarcoma of bone

    International Nuclear Information System (INIS)

    Xie Yuanzhong; Kong Qingkui; Wang Xia; Li Changqing

    2004-01-01

    Objective: To analyze the radiological findings of dedifferentiated chondrosarcoma, and to explore the imaging features of dedifferentiated tissue. Methods: The X-ray and CT findings of 13 cases with dedifferentiated chondrosarcoma of bone were analyzed retrospectively, and studied with clinic and corresponding histological changes. Results: The dedifferentiated chondrosarcoma not only had the radiological findings of typical chondrosarcoma but also had the imaging features of dedifferentiated tissues. In 13 patients, periosteal reactions were found in 11 cases, ossifications in 8 cases, soft tissue masses in 12 cases, calcifications in 10 cases, and the site of calcifications in 8 cases was in the center of the focus. Conclusion: The dedifferentiated chondrosarcoma showed special imaging features, which includes ossification, calcification, periosteal reaction, and soft tissue mass. These features were not found in typical chondrosarcoma. Recognizing these specific features is helpful to the diagnosis of dedifferentiated chondrosarcoma. (author)

  7. System Matrix Analysis for Computed Tomography Imaging

    Science.gov (United States)

    Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

    2015-01-01

    In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482

  8. Analysis of Non Local Image Denoising Methods

    Science.gov (United States)

    Pardo, Álvaro

    Image denoising is probably one of the most studied problems in the image processing community. Recently a new paradigm on non local denoising was introduced. The Non Local Means method proposed by Buades, Morel and Coll attracted the attention of other researches who proposed improvements and modifications to their proposal. In this work we analyze those methods trying to understand their properties while connecting them to segmentation based on spectral graph properties. We also propose some improvements to automatically estimate the parameters used on these methods.

  9. Analysis of PETT images in psychiatric disorders

    International Nuclear Information System (INIS)

    Brodie, J.D.; Gomez-Mont, F.; Volkow, N.D.; Corona, J.F.; Wolf, A.P.; Wolkin, A.; Russell, J.A.G.; Christman, D.; Jaeger, J.

    1983-01-01

    A quantitative method is presented for studying the pattern of metabolic activity in a set of Positron Emission Transaxial Tomography (PETT) images. Using complex Fourier coefficients as a feature vector for each image, cluster, principal components, and discriminant function analyses are used to empirically describe metabolic differences between control subjects and patients with DSM III diagnosis for schizophrenia or endogenous depression. We also present data on the effects of neuroleptic treatment on the local cerebral metabolic rate of glucose utilization (LCMRGI) in a group of chronic schizophrenics using the region of interest approach. 15 references, 4 figures, 3 tables

  10. Analysis of PETT images in psychiatric disorders

    Energy Technology Data Exchange (ETDEWEB)

    Brodie, J.D.; Gomez-Mont, F.; Volkow, N.D.; Corona, J.F.; Wolf, A.P.; Wolkin, A.; Russell, J.A.G.; Christman, D.; Jaeger, J.

    1983-01-01

    A quantitative method is presented for studying the pattern of metabolic activity in a set of Positron Emission Transaxial Tomography (PETT) images. Using complex Fourier coefficients as a feature vector for each image, cluster, principal components, and discriminant function analyses are used to empirically describe metabolic differences between control subjects and patients with DSM III diagnosis for schizophrenia or endogenous depression. We also present data on the effects of neuroleptic treatment on the local cerebral metabolic rate of glucose utilization (LCMRGI) in a group of chronic schizophrenics using the region of interest approach. 15 references, 4 figures, 3 tables.

  11. Independent component analysis based filtering for penumbral imaging

    International Nuclear Information System (INIS)

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-01-01

    We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters

  12. Architectural design and analysis of a programmable image processor

    International Nuclear Information System (INIS)

    Siyal, M.Y.; Chowdhry, B.S.; Rajput, A.Q.K.

    2003-01-01

    In this paper we present an architectural design and analysis of a programmable image processor, nicknamed Snake. The processor was designed with a high degree of parallelism to speed up a range of image processing operations. Data parallelism found in array processors has been included into the architecture of the proposed processor. The implementation of commonly used image processing algorithms and their performance evaluation are also discussed. The performance of Snake is also compared with other types of processor architectures. (author)

  13. GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

    Directory of Open Access Journals (Sweden)

    K. Di

    2016-06-01

    Full Text Available This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC Narrow Angle Camera (NAC images at the Chang’e-3(CE-3 landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

  14. Some selected quantitative methods of thermal image analysis in Matlab.

    Science.gov (United States)

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Precision Statistical Analysis of Images Based on Brightness Distribution

    Directory of Open Access Journals (Sweden)

    Muzhir Shaban Al-Ani

    2017-07-01

    Full Text Available Study the content of images is considered an important topic in which reasonable and accurate analysis of images are generated. Recently image analysis becomes a vital field because of huge number of images transferred via transmission media in our daily life. These crowded media with images lead to highlight in research area of image analysis. In this paper, the implemented system is passed into many steps to perform the statistical measures of standard deviation and mean values of both color and grey images. Whereas the last step of the proposed method concerns to compare the obtained results in different cases of the test phase. In this paper, the statistical parameters are implemented to characterize the content of an image and its texture. Standard deviation, mean and correlation values are used to study the intensity distribution of the tested images. Reasonable results are obtained for both standard deviation and mean value via the implementation of the system. The major issue addressed in the work is concentrated on brightness distribution via statistical measures applying different types of lighting.

  16. On two methods of statistical image analysis

    NARCIS (Netherlands)

    Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.

    1999-01-01

    The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,

  17. Complications of Whipple surgery: imaging analysis.

    Science.gov (United States)

    Bhosale, Priya; Fleming, Jason; Balachandran, Aparna; Charnsangavej, Chuslip; Tamm, Eric P

    2013-04-01

    The purpose of this article is to describe and illustrate anatomic findings after the Whipple procedure, and the appearance of its complications, on imaging. Knowledge of the cross-sectional anatomy following the Whipple procedure, and clinical findings for associated complications, are essential to rapidly and accurately diagnose such complications on postoperative studies in order to optimize treatment.

  18. The cumulative verification image analysis tool for offline evaluation of portal images

    International Nuclear Information System (INIS)

    Wong, John; Yan Di; Michalski, Jeff; Graham, Mary; Halverson, Karen; Harms, William; Purdy, James

    1995-01-01

    Purpose: Daily portal images acquired using electronic portal imaging devices contain important information about the setup variation of the individual patient. The data can be used to evaluate the treatment and to derive correction for the individual patient. The large volume of images also require software tools for efficient analysis. This article describes the approach of cumulative verification image analysis (CVIA) specifically designed as an offline tool to extract quantitative information from daily portal images. Methods and Materials: The user interface, image and graphics display, and algorithms of the CVIA tool have been implemented in ANSCI C using the X Window graphics standards. The tool consists of three major components: (a) definition of treatment geometry and anatomical information; (b) registration of portal images with a reference image to determine setup variation; and (c) quantitative analysis of all setup variation measurements. The CVIA tool is not automated. User interaction is required and preferred. Successful alignment of anatomies on portal images at present remains mostly dependent on clinical judgment. Predefined templates of block shapes and anatomies are used for image registration to enhance efficiency, taking advantage of the fact that much of the tool's operation is repeated in the analysis of daily portal images. Results: The CVIA tool is portable and has been implemented on workstations with different operating systems. Analysis of 20 sequential daily portal images can be completed in less than 1 h. The temporal information is used to characterize setup variation in terms of its systematic, random and time-dependent components. The cumulative information is used to derive block overlap isofrequency distributions (BOIDs), which quantify the effective coverage of the prescribed treatment area throughout the course of treatment. Finally, a set of software utilities is available to facilitate feedback of the information for

  19. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. W. Zhao

    2016-06-01

    Full Text Available As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings and the physical parameters of the surface (roughness, correlation length, permittivitywhich determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  20. Direct identification of pure penicillium species using image analysis

    DEFF Research Database (Denmark)

    Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian

    2000-01-01

    This paper presents a method for direct identification of fungal species solely by means of digital image analysis of colonies as seen after growth on a standard medium. The method described is completely automated and hence objective once digital images of the reference fungi have been establish...

  1. Automated image analysis for quantification of filamentous bacteria

    DEFF Research Database (Denmark)

    Fredborg, Marlene; Rosenvinge, Flemming Schønning; Spillum, Erik

    2015-01-01

    in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying...

  2. [Evaluation of dental plaque by quantitative digital image analysis system].

    Science.gov (United States)

    Huang, Z; Luan, Q X

    2016-04-18

    To analyze the plaque staining image by using image analysis software, to verify the maneuverability, practicability and repeatability of this technique, and to evaluate the influence of different plaque stains. In the study, 30 volunteers were enrolled from the new dental students of Peking University Health Science Center in accordance with the inclusion criteria. The digital images of the anterior teeth were acquired after plaque stained according to filming standardization.The image analysis was performed using Image Pro Plus 7.0, and the Quigley-Hein plaque indexes of the anterior teeth were evaluated. The plaque stain area percentage and the corresponding dental plaque index were highly correlated,and the Spearman correlation coefficient was 0.776 (Pchart showed only a few spots outside the 95% consistency boundaries. The different plaque stains image analysis results showed that the difference of the tooth area measurements was not significant, while the difference of the plaque area measurements significant (P<0.01). This method is easy in operation and control,highly related to the calculated percentage of plaque area and traditional plaque index, and has good reproducibility.The different plaque staining method has little effect on image segmentation results.The sensitive plaque stain for image analysis is suggested.

  3. Basic strategies for valid cytometry using image analysis

    NARCIS (Netherlands)

    Jonker, A.; Geerts, W. J.; Chieco, P.; Moorman, A. F.; Lamers, W. H.; van Noorden, C. J.

    1997-01-01

    The present review provides a starting point for setting up an image analysis system for quantitative densitometry and absorbance or fluorescence measurements in cell preparations, tissue sections or gels. Guidelines for instrumental settings that are essential for the valid application of image

  4. Subsurface offset behaviour in velocity analysis with extended reflectivity images

    NARCIS (Netherlands)

    Mulder, W.A.

    2012-01-01

    Migration velocity analysis with the wave equation can be accomplished by focusing of extended migration images, obtained by introducing a subsurface offset or shift. A reflector in the wrong velocity model will show up as a curve in the extended image. In the correct model, it should collapse to a

  5. A Survey on Deep Learning in Medical Image Analysis

    NARCIS (Netherlands)

    Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.

    2017-01-01

    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

  6. Analysis of Two-Dimensional Electrophoresis Gel Images

    DEFF Research Database (Denmark)

    Pedersen, Lars

    2002-01-01

    This thesis describes and proposes solutions to some of the currently most important problems in pattern recognition and image analysis of two-dimensional gel electrophoresis (2DGE) images. 2DGE is the leading technique to separate individual proteins in biological samples with many biological...

  7. Occupancy Analysis of Sports Arenas Using Thermal Imaging

    DEFF Research Database (Denmark)

    Gade, Rikke; Jørgensen, Anders; Moeslund, Thomas B.

    2012-01-01

    This paper presents a system for automatic analysis of the occupancy of sports arenas. By using a thermal camera for image capturing the number of persons and their location on the court are found without violating any privacy issues. The images are binarised with an automatic threshold method...

  8. Principal component analysis of image gradient orientations for face recognition

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data

  9. Automated Image Analysis Corrosion Working Group Update: February 1, 2018

    Energy Technology Data Exchange (ETDEWEB)

    Wendelberger, James G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-01

    These are slides for the automated image analysis corrosion working group update. The overall goals were: automate the detection and quantification of features in images (faster, more accurate), how to do this (obtain data, analyze data), focus on Laser Scanning Confocal Microscope (LCM) data (laser intensity, laser height/depth, optical RGB, optical plus laser RGB).

  10. On the applicability of numerical image mapping for PIV image analysis near curved interfaces

    International Nuclear Information System (INIS)

    Masullo, Alessandro; Theunissen, Raf

    2017-01-01

    This paper scrutinises the general suitability of image mapping for particle image velocimetry (PIV) applications. Image mapping can improve PIV measurement accuracy by eliminating overlap between the PIV interrogation windows and an interface, as illustrated by some examples in the literature. Image mapping transforms the PIV images using a curvilinear interface-fitted mesh prior to performing the PIV cross correlation. However, degrading effects due to particle image deformation and the Jacobian transformation inherent in the mapping along curvilinear grid lines have never been deeply investigated. Here, the implementation of image mapping from mesh generation to image resampling is presented in detail, and related error sources are analysed. Systematic comparison with standard PIV approaches shows that image mapping is effective only in a very limited set of flow conditions and geometries, and depends strongly on a priori knowledge of the boundary shape and streamlines. In particular, with strongly curved geometries or streamlines that are not parallel to the interface, the image-mapping approach is easily outperformed by more traditional image analysis methodologies invoking suitable spatial relocation of the obtained displacement vector. (paper)

  11. The ImageJ ecosystem: An open platform for biomedical image analysis.

    Science.gov (United States)

    Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W

    2015-01-01

    Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. © 2015 Wiley Periodicals, Inc.

  12. Determination of fish gender using fractal analysis of ultrasound images

    DEFF Research Database (Denmark)

    McEvoy, Fintan J.; Tomkiewicz, Jonna; Støttrup, Josianne

    2009-01-01

    The gender of cod Gadus morhua can be determined by considering the complexity in their gonadal ultrasonographic appearance. The fractal dimension (DB) can be used to describe this feature in images. B-mode gonadal ultrasound images in 32 cod, where gender was known, were collected. Fractal...... by subjective analysis alone. The mean (and standard deviation) of the fractal dimension DB for male fish was 1.554 (0.073) while for female fish it was 1.468 (0.061); the difference was statistically significant (P=0.001). The area under the ROC curve was 0.84 indicating the value of fractal analysis in gender...... result. Fractal analysis is useful for gender determination in cod. This or a similar form of analysis may have wide application in veterinary imaging as a tool for quantification of complexity in images...

  13. Analysis of PET hypoxia imaging in the quantitative imaging for personalized cancer medicine program

    International Nuclear Information System (INIS)

    Yeung, Ivan; Driscoll, Brandon; Keller, Harald; Shek, Tina; Jaffray, David; Hedley, David

    2014-01-01

    Quantitative imaging is an important tool in clinical trials of testing novel agents and strategies for cancer treatment. The Quantitative Imaging Personalized Cancer Medicine Program (QIPCM) provides clinicians and researchers participating in multi-center clinical trials with a central repository for their imaging data. In addition, a set of tools provide standards of practice (SOP) in end-to-end quality assurance of scanners and image analysis. The four components for data archiving and analysis are the Clinical Trials Patient Database, the Clinical Trials PACS, the data analysis engine(s) and the high-speed networks that connect them. The program provides a suite of software which is able to perform RECIST, dynamic MRI, CT and PET analysis. The imaging data can be assessed securely from remote and analyzed by researchers with these software tools, or with tools provided by the users and installed at the server. Alternatively, QIPCM provides a service for data analysis on the imaging data according developed SOP. An example of a clinical study in which patients with unresectable pancreatic adenocarcinoma were studied with dynamic PET-FAZA for hypoxia measurement will be discussed. We successfully quantified the degree of hypoxia as well as tumor perfusion in a group of 20 patients in terms of SUV and hypoxic fraction. It was found that there is no correlation between bulk tumor perfusion and hypoxia status in this cohort. QIPCM also provides end-to-end QA testing of scanners used in multi-center clinical trials. Based on quality assurance data from multiple CT-PET scanners, we concluded that quality control of imaging was vital in the success in multi-center trials as different imaging and reconstruction parameters in PET imaging could lead to very different results in hypoxia imaging. (author)

  14. Digital image analysis of X-ray television with an image digitizer

    International Nuclear Information System (INIS)

    Mochizuki, Yasuo; Akaike, Hisahiko; Ogawa, Hitoshi; Kyuma, Yukishige

    1995-01-01

    When video signals of X-ray fluoroscopy were transformed from analog-to-digital ones with an image digitizer, their digital characteristic curves, pre-sampling MTF's and digital Wiener spectral could be measured. This method was advant ageous in that it was able to carry out data sampling because the pixel values inputted could be verified on a CRT. The system of image analysis by this method is inexpensive and effective in evaluating the image quality of digital system. Also, it is expected that this method can be used as a tool for learning the measurement techniques and physical characteristics of digital image quality effectively. (author)

  15. Analysis and clinical usefullness of cardiac ECT images

    International Nuclear Information System (INIS)

    Hayashi, Makoto; Kagawa, Masaaki; Yamada, Yukinori

    1983-01-01

    We estimated basically and clinically myocardial ECT image and ECG gated cardiac blood-pool ECT image. ROC curve is used for the evaluation of the accuracy in diagnostic myocardial infarction. The accuracy in diagnostic of MI is superior in myocardial ECT image and ECT estimation is unnecessary skillfulness and experience. We can absene the whole defect of MI than planar image by using ECT. LVEDV between estimated volume and contrast volume is according to it and get one step for automatic analysis of cardiac volume. (author)

  16. Multivariate statistical analysis for x-ray photoelectron spectroscopy spectral imaging: Effect of image acquisition time

    International Nuclear Information System (INIS)

    Peebles, D.E.; Ohlhausen, J.A.; Kotula, P.G.; Hutton, S.; Blomfield, C.

    2004-01-01

    The acquisition of spectral images for x-ray photoelectron spectroscopy (XPS) is a relatively new approach, although it has been used with other analytical spectroscopy tools for some time. This technique provides full spectral information at every pixel of an image, in order to provide a complete chemical mapping of the imaged surface area. Multivariate statistical analysis techniques applied to the spectral image data allow the determination of chemical component species, and their distribution and concentrations, with minimal data acquisition and processing times. Some of these statistical techniques have proven to be very robust and efficient methods for deriving physically realistic chemical components without input by the user other than the spectral matrix itself. The benefits of multivariate analysis of the spectral image data include significantly improved signal to noise, improved image contrast and intensity uniformity, and improved spatial resolution - which are achieved due to the effective statistical aggregation of the large number of often noisy data points in the image. This work demonstrates the improvements in chemical component determination and contrast, signal-to-noise level, and spatial resolution that can be obtained by the application of multivariate statistical analysis to XPS spectral images

  17. Developments in Dynamic Analysis for quantitative PIXE true elemental imaging

    International Nuclear Information System (INIS)

    Ryan, C.G.

    2001-01-01

    Dynamic Analysis (DA) is a method for projecting quantitative major and trace element images from PIXE event data-streams (off-line or on-line) obtained using the Nuclear Microprobe. The method separates full elemental spectral signatures to produce images that strongly reject artifacts due to overlapping elements, detector effects (such as escape peaks and tailing) and background. The images are also quantitative, stored in ppm-charge units, enabling images to be directly interrogated for the concentrations of all elements in areas of the images. Recent advances in the method include the correction for changing X-ray yields due to varying sample compositions across the image area and the construction of statistical variance images. The resulting accuracy of major element concentrations extracted directly from these images is better than 3% relative as determined from comparisons with electron microprobe point analysis. These results are complemented by error estimates derived from the variance images together with detection limits. This paper provides an update of research on these issues, introduces new software designed to make DA more accessible, and illustrates the application of the method to selected geological problems.

  18. ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability.

    Science.gov (United States)

    Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W

    2017-02-15

    ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks. Freely available extension to ImageJ2 ( http://imagej.net/Downloads ). Installation and use instructions available at http://imagej.net/MATLAB_Scripting. Tested with ImageJ 2.0.0-rc-54 , Java 1.8.0_66 and MATLAB R2015b. eliceiri@wisc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  19. Chemical imaging and solid state analysis at compact surfaces using UV imaging

    DEFF Research Database (Denmark)

    Wu, Jian X.; Rehder, Sönke; van den Berg, Frans

    2014-01-01

    and excipients in a non-invasive way, as well as mapping the glibenclamide solid state form. An exploratory data analysis supported the critical evaluation of the mapping results and the selection of model parameters for the chemical mapping. The present study demonstrated that the multi-wavelength UV imaging......Fast non-destructive multi-wavelength UV imaging together with multivariate image analysis was utilized to visualize distribution of chemical components and their solid state form at compact surfaces. Amorphous and crystalline solid forms of the antidiabetic compound glibenclamide...

  20. Textural Analysis of Fatique Crack Surfaces: Image Pre-processing

    Directory of Open Access Journals (Sweden)

    H. Lauschmann

    2000-01-01

    Full Text Available For the fatique crack history reconstitution, new methods of quantitative microfractography are beeing developed based on the image processing and textural analysis. SEM magnifications between micro- and macrofractography are used. Two image pre-processing operatins were suggested and proved to prepare the crack surface images for analytical treatment: 1. Normalization is used to transform the image to a stationary form. Compared to the generally used equalization, it conserves the shape of brightness distribution and saves the character of the texture. 2. Binarization is used to transform the grayscale image to a system of thick fibres. An objective criterion for the threshold brightness value was found as that resulting into the maximum number of objects. Both methods were succesfully applied together with the following textural analysis.

  1. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  2. Development of motion image prediction method using principal component analysis

    International Nuclear Information System (INIS)

    Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Kamiaka, Kazuma

    2012-01-01

    Respiratory motion can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to minimize the impact of healthy tissue irradiation due to the lung tumor motion. The purpose of this research is to develop an algorithm for the improvement of image guided radiation therapy by the prediction of motion images. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. The images/movies were successfully predicted and verified using the developed algorithm. With the proposed prediction method it is possible to forecast the tumor images over the next breathing period. The implementation of this method in real time is believed to be significant for higher level of tumor tracking including the detection of sudden abdominal changes during radiation therapy. (author)

  3. A software platform for the analysis of dermatology images

    Science.gov (United States)

    Vlassi, Maria; Mavraganis, Vlasios; Asvestas, Panteleimon

    2017-11-01

    The purpose of this paper is to present a software platform developed in Python programming environment that can be used for the processing and analysis of dermatology images. The platform provides the capability for reading a file that contains a dermatology image. The platform supports image formats such as Windows bitmaps, JPEG, JPEG2000, portable network graphics, TIFF. Furthermore, it provides suitable tools for selecting, either manually or automatically, a region of interest (ROI) on the image. The automated selection of a ROI includes filtering for smoothing the image and thresholding. The proposed software platform has a friendly and clear graphical user interface and could be a useful second-opinion tool to a dermatologist. Furthermore, it could be used to classify images including from other anatomical parts such as breast or lung, after proper re-training of the classification algorithms.

  4. Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

    Science.gov (United States)

    Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

    2018-01-01

    To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

  5. SPECTRUM analysis of multispectral imagery in conjunction with wavelet/KLT data compression

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, J.N.; Brislawn, C.M.

    1993-12-01

    The data analysis program, SPECTRUM, is used for fusion, visualization, and classification of multi-spectral imagery. The raw data used in this study is Landsat Thematic Mapper (TM) 7-channel imagery, with 8 bits of dynamic range per channel. To facilitate data transmission and storage, a compression algorithm is proposed based on spatial wavelet transform coding and KLT decomposition of interchannel spectral vectors, followed by adaptive optimal multiband scalar quantization. The performance of SPECTRUM clustering and visualization is evaluated on compressed multispectral data. 8-bit visualizations of 56-bit data show little visible distortion at 50:1 compression and graceful degradation at higher compression ratios. Two TM images were processed in this experiment: a 1024 x 1024-pixel scene of the region surrounding the Chernobyl power plant, taken a few months before the reactor malfunction, and a 2048 x 2048 image of Moscow and surrounding countryside.

  6. An approach for quantitative image quality analysis for CT

    Science.gov (United States)

    Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

    2016-03-01

    An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

  7. [Quantitative data analysis for live imaging of bone.

    Science.gov (United States)

    Seno, Shigeto

    Bone tissue is a hard tissue, it was difficult to observe the interior of the bone tissue alive. With the progress of microscopic technology and fluorescent probe technology in recent years, it becomes possible to observe various activities of various cells forming bone society. On the other hand, the quantitative increase in data and the diversification and complexity of the images makes it difficult to perform quantitative analysis by visual inspection. It has been expected to develop a methodology for processing microscopic images and data analysis. In this article, we introduce the research field of bioimage informatics which is the boundary area of biology and information science, and then outline the basic image processing technology for quantitative analysis of live imaging data of bone.

  8. Image analysis of multiple moving wood pieces in real time

    Science.gov (United States)

    Wang, Weixing

    2006-02-01

    This paper presents algorithms for image processing and image analysis of wood piece materials. The algorithms were designed for auto-detection of wood piece materials on a moving conveyor belt or a truck. When wood objects on moving, the hard task is to trace the contours of the objects in n optimal way. To make the algorithms work efficiently in the plant, a flexible online system was designed and developed, which mainly consists of image acquisition, image processing, object delineation and analysis. A number of newly-developed algorithms can delineate wood objects with high accuracy and high speed, and in the wood piece analysis part, each wood piece can be characterized by a number of visual parameters which can also be used for constructing experimental models directly in the system.

  9. New approach to gallbladder ultrasonic images analysis and lesions recognition.

    Science.gov (United States)

    Bodzioch, Sławomir; Ogiela, Marek R

    2009-03-01

    This paper presents a new approach to gallbladder ultrasonic image processing and analysis towards detection of disease symptoms on processed images. First, in this paper, there is presented a new method of filtering gallbladder contours from USG images. A major stage in this filtration is to segment and section off areas occupied by the said organ. In most cases this procedure is based on filtration that plays a key role in the process of diagnosing pathological changes. Unfortunately ultrasound images present among the most troublesome methods of analysis owing to the echogenic inconsistency of structures under observation. This paper provides for an inventive algorithm for the holistic extraction of gallbladder image contours. The algorithm is based on rank filtration, as well as on the analysis of histogram sections on tested organs. The second part concerns detecting lesion symptoms of the gallbladder. Automating a process of diagnosis always comes down to developing algorithms used to analyze the object of such diagnosis and verify the occurrence of symptoms related to given affection. Usually the final stage is to make a diagnosis based on the detected symptoms. This last stage can be carried out through either dedicated expert systems or more classic pattern analysis approach like using rules to determine illness basing on detected symptoms. This paper discusses the pattern analysis algorithms for gallbladder image interpretation towards classification of the most frequent illness symptoms of this organ.

  10. Advanced Color Image Processing and Analysis

    CERN Document Server

    2013-01-01

    This volume does much more than survey modern advanced color processing. Starting with a historical perspective on ways we have classified color, it sets out the latest numerical techniques for analyzing and processing colors, the leading edge in our search to accurately record and print what we see. The human eye perceives only a fraction of available light wavelengths, yet we live in a multicolor world of myriad shining hues. Colors rich in metaphorical associations make us “purple with rage” or “green with envy” and cause us to “see red.” Defining colors has been the work of centuries, culminating in today’s complex mathematical coding that nonetheless remains a work in progress: only recently have we possessed the computing capacity to process the algebraic matrices that reproduce color more accurately. With chapters on dihedral color and image spectrometers, this book provides technicians and researchers with the knowledge they need to grasp the intricacies of today’s color imaging.

  11. Automated image analysis of atomic force microscopy images of rotavirus particles

    International Nuclear Information System (INIS)

    Venkataraman, S.; Allison, D.P.; Qi, H.; Morrell-Falvey, J.L.; Kallewaard, N.L.; Crowe, J.E.; Doktycz, M.J.

    2006-01-01

    A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM

  12. Automated image analysis of atomic force microscopy images of rotavirus particles

    Energy Technology Data Exchange (ETDEWEB)

    Venkataraman, S. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Allison, D.P. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Biochemistry, Cellular, and Molecular Biology, University of Tennessee, Knoxville, TN 37996 (United States); Molecular Imaging Inc. Tempe, AZ, 85282 (United States); Qi, H. [Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Morrell-Falvey, J.L. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Kallewaard, N.L. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Crowe, J.E. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Doktycz, M.J. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States)]. E-mail: doktyczmj@ornl.gov

    2006-06-15

    A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM.

  13. Fractal-Based Image Analysis In Radiological Applications

    Science.gov (United States)

    Dellepiane, S.; Serpico, S. B.; Vernazza, G.; Viviani, R.

    1987-10-01

    We present some preliminary results of a study aimed to assess the actual effectiveness of fractal theory and to define its limitations in the area of medical image analysis for texture description, in particular, in radiological applications. A general analysis to select appropriate parameters (mask size, tolerance on fractal dimension estimation, etc.) has been performed on synthetically generated images of known fractal dimensions. Moreover, we analyzed some radiological images of human organs in which pathological areas can be observed. Input images were subdivided into blocks of 6x6 pixels; then, for each block, the fractal dimension was computed in order to create fractal images whose intensity was related to the D value, i.e., texture behaviour. Results revealed that the fractal images could point out the differences between normal and pathological tissues. By applying histogram-splitting segmentation to the fractal images, pathological areas were isolated. Two different techniques (i.e., the method developed by Pentland and the "blanket" method) were employed to obtain fractal dimension values, and the results were compared; in both cases, the appropriateness of the fractal description of the original images was verified.

  14. Cnn Based Retinal Image Upscaling Using Zero Component Analysis

    Science.gov (United States)

    Nasonov, A.; Chesnakov, K.; Krylov, A.

    2017-05-01

    The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

  15. NEPR Principle Component Analysis - NOAA TIFF Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a representation of seafloor topography in Northeast Puerto Rico derived from a bathymetry model with a principle component analysis (PCA). The area...

  16. A parallel solution for high resolution histological image analysis.

    Science.gov (United States)

    Bueno, G; González, R; Déniz, O; García-Rojo, M; González-García, J; Fernández-Carrobles, M M; Vállez, N; Salido, J

    2012-10-01

    This paper describes a general methodology for developing parallel image processing algorithms based on message passing for high resolution images (on the order of several Gigabytes). These algorithms have been applied to histological images and must be executed on massively parallel processing architectures. Advances in new technologies for complete slide digitalization in pathology have been combined with developments in biomedical informatics. However, the efficient use of these digital slide systems is still a challenge. The image processing that these slides are subject to is still limited both in terms of data processed and processing methods. The work presented here focuses on the need to design and develop parallel image processing tools capable of obtaining and analyzing the entire gamut of information included in digital slides. Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images. Code portability, reusability and scalability have been tested by using the following parallel computing architectures: distributed memory with massive parallel processors and two networks, INFINIBAND and Myrinet, composed of 17 and 1024 nodes respectively. The parallel framework proposed is flexible, high performance solution and it shows that the efficient processing of digital microscopic images is possible and may offer important benefits to pathology laboratories. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  17. Acne image analysis: lesion localization and classification

    Science.gov (United States)

    Abas, Fazly Salleh; Kaffenberger, Benjamin; Bikowski, Joseph; Gurcan, Metin N.

    2016-03-01

    Acne is a common skin condition present predominantly in the adolescent population, but may continue into adulthood. Scarring occurs commonly as a sequel to severe inflammatory acne. The presence of acne and resultant scars are more than cosmetic, with a significant potential to alter quality of life and even job prospects. The psychosocial effects of acne and scars can be disturbing and may be a risk factor for serious psychological concerns. Treatment efficacy is generally determined based on an invalidated gestalt by the physician and patient. However, the validated assessment of acne can be challenging and time consuming. Acne can be classified into several morphologies including closed comedones (whiteheads), open comedones (blackheads), papules, pustules, cysts (nodules) and scars. For a validated assessment, the different morphologies need to be counted independently, a method that is far too time consuming considering the limited time available for a consultation. However, it is practical to record and analyze images since dermatologists can validate the severity of acne within seconds after uploading an image. This paper covers the processes of region-ofinterest determination using entropy-based filtering and thresholding as well acne lesion feature extraction. Feature extraction methods using discrete wavelet frames and gray-level co-occurence matrix were presented and their effectiveness in separating the six major acne lesion classes were discussed. Several classifiers were used to test the extracted features. Correct classification accuracy as high as 85.5% was achieved using the binary classification tree with fourteen principle components used as descriptors. Further studies are underway to further improve the algorithm performance and validate it on a larger database.

  18. Quantitative analysis and classification of AFM images of human hair.

    Science.gov (United States)

    Gurden, S P; Monteiro, V F; Longo, E; Ferreira, M M C

    2004-07-01

    The surface topography of human hair, as defined by the outer layer of cellular sheets, termed cuticles, largely determines the cosmetic properties of the hair. The condition of the cuticles is of great cosmetic importance, but also has the potential to aid diagnosis in the medical and forensic sciences. Atomic force microscopy (AFM) has been demonstrated to offer unique advantages for analysis of the hair surface, mainly due to the high image resolution and the ease of sample preparation. This article presents an algorithm for the automatic analysis of AFM images of human hair. The cuticular structure is characterized using a series of descriptors, such as step height, tilt angle and cuticle density, allowing quantitative analysis and comparison of different images. The usefulness of this approach is demonstrated by a classification study. Thirty-eight AFM images were measured, consisting of hair samples from (a) untreated and bleached hair samples, and (b) the root and distal ends of the hair fibre. The multivariate classification technique partial least squares discriminant analysis is used to test the ability of the algorithm to characterize the images according to the properties of the hair samples. Most of the images (86%) were found to be classified correctly.

  19. Utilizing Minkowski functionals for image analysis: a marching square algorithm

    International Nuclear Information System (INIS)

    Mantz, Hubert; Jacobs, Karin; Mecke, Klaus

    2008-01-01

    Comparing noisy experimental image data with statistical models requires a quantitative analysis of grey-scale images beyond mean values and two-point correlations. A real-space image analysis technique is introduced for digitized grey-scale images, based on Minkowski functionals of thresholded patterns. A novel feature of this marching square algorithm is the use of weighted side lengths for pixels, so that boundary lengths are captured accurately. As examples to illustrate the technique we study surface topologies emerging during the dewetting process of thin films and analyse spinodal decomposition as well as turbulent patterns in chemical reaction–diffusion systems. The grey-scale value corresponds to the height of the film or to the concentration of chemicals, respectively. Comparison with analytic calculations in stochastic geometry models reveals a remarkable agreement of the examples with a Gaussian random field. Thus, a statistical test for non-Gaussian features in experimental data becomes possible with this image analysis technique—even for small image sizes. Implementations of the software used for the analysis are offered for download

  20. Image analysis for remote examination of fuel pins

    International Nuclear Information System (INIS)

    Cook, J.H.; Nayak, U.P.

    1982-01-01

    An image analysis system operating in the Wing 9 Hot Cell Facility at Los Alamos National Laboratory provides quantitative microstructural analyses of irradiated fuels and materials. With this system, fewer photomicrographs are required during postirradiation microstructural examination and data are available for analysis much faster. The system has been used successfully to examine Westinghouse Advanced Reactors Division experimental fuel pins

  1. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

    Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

  2. Estimation of Melanin and Hemoglobin Using Spectral Reflectance Images Reconstructed from a Digital RGB Image by the Wiener Estimation Method

    Directory of Open Access Journals (Sweden)

    Yoshihisa Aizu

    2013-06-01

    Full Text Available A multi-spectral diffuse reflectance imaging method based on a single snap shot of Red-Green-Blue images acquired with the exposure time of 65 ms (15 fps was investigated for estimating melanin concentration, blood concentration, and oxygen saturation in human skin tissue. The technique utilizes the Wiener estimation method to deduce spectral reflectance images instantaneously from an RGB image. Using the resultant absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are numerically deduced in advance by the Monte Carlo simulations for light transport in skin. Oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments on fingers during upper limb occlusion demonstrated the ability of the method to evaluate physiological reactions of human skin.

  3. Low-level processing for real-time image analysis

    Science.gov (United States)

    Eskenazi, R.; Wilf, J. M.

    1979-01-01

    A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

  4. Image analysis of ocular fundus for retinopathy characterization

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela; Cuadros, Jorge

    2010-02-05

    Automated analysis of ocular fundus images is a common procedure in countries as England, including both nonemergency examination and retinal screening of patients with diabetes mellitus. This involves digital image capture and transmission of the images to a digital reading center for evaluation and treatment referral. In collaboration with the Optometry Department, University of California, Berkeley, we have tested computer vision algorithms to segment vessels and lesions in ground-truth data (DRIVE database) and hundreds of images of non-macular centric and nonuniform illumination views of the eye fundus from EyePACS program. Methods under investigation involve mathematical morphology (Figure 1) for image enhancement and pattern matching. Recently, we have focused in more efficient techniques to model the ocular fundus vasculature (Figure 2), using deformable contours. Preliminary results show accurate segmentation of vessels and high level of true-positive microaneurysms.

  5. Image registration based on virtual frame sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chen, H.; Ng, W.S. [Nanyang Technological University, Computer Integrated Medical Intervention Laboratory, School of Mechanical and Aerospace Engineering, Singapore (Singapore); Shi, D. (Nanyang Technological University, School of Computer Engineering, Singapore, Singpore); Wee, S.B. [Tan Tock Seng Hospital, Department of General Surgery, Singapore (Singapore)

    2007-08-15

    This paper is to propose a new framework for medical image registration with large nonrigid deformations, which still remains one of the biggest challenges for image fusion and further analysis in many medical applications. Registration problem is formulated as to recover a deformation process with the known initial state and final state. To deal with large nonlinear deformations, virtual frames are proposed to be inserted to model the deformation process. A time parameter is introduced and the deformation between consecutive frames is described with a linear affine transformation. Experiments are conducted with simple geometric deformation as well as complex deformations presented in MRI and ultrasound images. All the deformations are characterized with nonlinearity. The positive results demonstrated the effectiveness of this algorithm. The framework proposed in this paper is feasible to register medical images with large nonlinear deformations and is especially useful for sequential images. (orig.)

  6. Implicitly Weighted Methods in Robust Image Analysis

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 44, č. 3 (2012), s. 449-462 ISSN 0924-9907 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robustness * high breakdown point * outlier detection * robust correlation analysis * template matching * face recognition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.767, year: 2012

  7. Spot analysis system by digitalization and imaging

    International Nuclear Information System (INIS)

    Gedin, F.

    1988-05-01

    Laser isotope separation experiments use series of laser producing several beams with characteristics adapted to physical conditions of photoionization. This paper describes briefly the laser chain and systems for measure and test with more details on analysis of spatial distribution of fluence and superposition of the three beams and alignment on the experiment axis [fr

  8. Analysis of Microplastics using FTIR Imaging

    DEFF Research Database (Denmark)

    Olesen, Kristina Borg; van Alst, Nikki; Simon, Marta

    2017-01-01

    In recent years, plastic pollution has received an increasing amount of interest from researchers, politicians, and the public. Microplastics (... and can remain in the environment for hundreds of years before they finally decompose. However, the accumulation level and the effects on the environment and aquatic life are poorly understood. This is partly due to a lack of standard analysis protocols and current analytical techniques...

  9. Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

    Science.gov (United States)

    Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

    1999-01-01

    The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

  10. Imaging analysis of direct alanine uptake by rice seedlings

    International Nuclear Information System (INIS)

    Nihei, Naoto; Masuda, Sayaka; Rai, Hiroki; Nakanishi, Tomoko M.

    2008-01-01

    We presented alanine, a kind of amino acids, uptake by a rice seedling to study the basic mechanism of the organic fertilizer effectiveness in organic farming. The rice grown in the culture solution containing alanine as a nitrogen source absorbed alanine approximately two times faster than that grown with NH 4 + from analysis of 14 C-alanine images by Imaging Plate method. It was suggested that the active transport ability of the rice seeding was induced in roots by existence of alanine in the rhizosphere. The alanine uptake images of the rice roots were acquired every 5 minutes successively by the real-time autoradiography system we developed. The analysis of the successive images showed that alanine uptake was not uniform throughout the root but especially active at the root tip. (author)

  11. Standardization of Image Quality Analysis – ISO 19264

    DEFF Research Database (Denmark)

    Wüller, Dietmar; Kejser, Ulla Bøgvad

    2016-01-01

    There are a variety of image quality analysis tools available for the archiving world, which are based on different test charts and analysis algorithms. ISO has formed a working group in 2012 to harmonize these approaches and create a standard way of analyzing the image quality for archiving...... systems. This has resulted in three documents that have been or are going to be published soon. ISO 19262 defines the terms used in the area of image capture to unify the language. ISO 19263 describes the workflow issues and provides detailed information on how the measurements are done. Last...... but not least ISO 19264 describes the measurements in detail and provides aims and tolerance levels for the different aspects. This paper will present the new ISO 19264 technical specification to analyze image quality based on a single capture of a multi-pattern test chart, and discuss the reasoning behind its...

  12. Mathematical methods in time series analysis and digital image processing

    CERN Document Server

    Kurths, J; Maass, P; Timmer, J

    2008-01-01

    The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.

  13. A hyperspectral image analysis workbench for environmental science applications

    Energy Technology Data Exchange (ETDEWEB)

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.

    1992-10-01

    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or ``hyperspectral`` imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne`s Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image ``texture spectra`` derived from fractal signatures computed for subimage tiles at each wavelength.

  14. A hyperspectral image analysis workbench for environmental science applications

    Energy Technology Data Exchange (ETDEWEB)

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.

    1992-01-01

    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or hyperspectral'' imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne's Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image texture spectra'' derived from fractal signatures computed for subimage tiles at each wavelength.

  15. Peripheral blood smear image analysis: A comprehensive review

    Directory of Open Access Journals (Sweden)

    Emad A Mohammed

    2014-01-01

    Full Text Available Peripheral blood smear image examination is a part of the routine work of every laboratory. The manual examination of these images is tedious, time-consuming and suffers from interobserver variation. This has motivated researchers to develop different algorithms and methods to automate peripheral blood smear image analysis. Image analysis itself consists of a sequence of steps consisting of image segmentation, features extraction and selection and pattern classification. The image segmentation step addresses the problem of extraction of the object or region of interest from the complicated peripheral blood smear image. Support vector machine (SVM and artificial neural networks (ANNs are two common approaches to image segmentation. Features extraction and selection aims to derive descriptive characteristics of the extracted object, which are similar within the same object class and different between different objects. This will facilitate the last step of the image analysis process: pattern classification. The goal of pattern classification is to assign a class to the selected features from a group of known classes. There are two types of classifier learning algorithms: supervised and unsupervised. Supervised learning algorithms predict the class of the object under test using training data of known classes. The training data have a predefined label for every class and the learning algorithm can utilize this data to predict the class of a test object. Unsupervised learning algorithms use unlabeled training data and divide them into groups using similarity measurements. Unsupervised learning algorithms predict the group to which a new test object belong to, based on the training data without giving an explicit class to that object. ANN, SVM, decision tree and K-nearest neighbor are possible approaches to classification algorithms. Increased discrimination may be obtained by combining several classifiers together.

  16. A software package for biomedical image processing and analysis

    International Nuclear Information System (INIS)

    Goncalves, J.G.M.; Mealha, O.

    1988-01-01

    The decreasing cost of computing power and the introduction of low cost imaging boards justifies the increasing number of applications of digital image processing techniques in the area of biomedicine. There is however a large software gap to be fulfilled, between the application and the equipment. The requirements to bridge this gap are twofold: good knowledge of the hardware provided and its interface to the host computer, and expertise in digital image processing and analysis techniques. A software package incorporating these two requirements was developed using the C programming language, in order to create a user friendly image processing programming environment. The software package can be considered in two different ways: as a data structure adapted to image processing and analysis, which acts as the backbone and the standard of communication for all the software; and as a set of routines implementing the basic algorithms used in image processing and analysis. Hardware dependency is restricted to a single module upon which all hardware calls are based. The data structure that was built has four main features: hierchical, open, object oriented, and object dependent dimensions. Considering the vast amount of memory needed by imaging applications and the memory available in small imaging systems, an effective image memory management scheme was implemented. This software package is being used for more than one and a half years by users with different applications. It proved to be an excellent tool for helping people to get adapted into the system, and for standardizing and exchanging software, yet preserving flexibility allowing for users' specific implementations. The philosophy of the software package is discussed and the data structure that was built is described in detail

  17. Muscle contraction analysis with MRI image

    International Nuclear Information System (INIS)

    Horio, Hideyuki; Kuroda, Yoshihiro; Imura, Masataka; Oshiro, Osamu

    2010-01-01

    The MRI measurement has been widely used from the advantage such as no radiation exposure and high resolution. In various measurement objects, the muscle is used for a research and clinical practice. But it was difficult to judge static state of a muscle contraction. In this study, we focused on a proton density change by the blood vessel pressure at the time of the muscle contraction, and aimed the judgments of muscle contraction from variance of the signal intensity. First, the background was removed from the measured images. Second, each signal divided into the low signal side and the high signal side, and variance values (σ H , σ L ) and the ratio (μ) were calculated. Finally, Relax and strain state ware judged from the ratio (μ). As a Result, in relax state, ratio (μ r ) was 0.9823±0.06133. And in strain state, ratio (μ s ) was 0.7547±0.10824. Therefore, a significant difference was obtained in relax state and strain state. Therefore, the strain state judgment of the muscle was possible by this study's method. (author)

  18. Flexibility analysis in adolescent idiopathic scoliosis on side-bending images using the EOS imaging system.

    Science.gov (United States)

    Hirsch, C; Ilharreborde, B; Mazda, K

    2016-06-01

    Analysis of preoperative flexibility in adolescent idiopathic scoliosis (AIS) is essential to classify the curves, determine their structurality, and select the fusion levels during preoperative planning. Side-bending x-rays are the gold standard for the analysis of preoperative flexibility. The objective of this study was to examine the feasibility and performance of side-bending images taken in the standing position using the EOS imaging system. All patients who underwent preoperative assessment between April 2012 and January 2013 for AIS were prospectively included in the study. The work-up included standing AP and lateral EOS x-rays of the spine, standard side-bending x-rays in the supine position, and standing bending x-rays in the EOS booth. The irradiation dose was measured for each of the tests. Two-dimensional reducibility of the Cobb angle was measured on both types of bending x-rays. The results were based on the 50 patients in the study. No significant difference was demonstrated for reducibility of the Cobb angle between the standing side-bending images with the EOS imaging system and those in the supine position for all types of Lenke deformation. The irradiation dose was five times lower during the EOS bending imaging. The standing side-bending images in the EOS device contributed the same results as the supine images, with five times less irradiation. They should therefore be used in clinical routine. 2. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  19. NDVI and Panchromatic Image Correlation Using Texture Analysis

    Science.gov (United States)

    2010-03-01

    6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

  20. Telemetry Timing Analysis for Image Reconstruction of Kompsat Spacecraft

    Directory of Open Access Journals (Sweden)

    Jin-Ho Lee

    2000-06-01

    Full Text Available The KOMPSAT (KOrea Multi-Purpose SATellite has two optical imaging instruments called EOC (Electro-Optical Camera and OSMI (Ocean Scanning Multispectral Imager. The image data of these instruments are transmitted to ground station and restored correctly after post-processing with the telemetry data transferred from KOMPSAT spacecraft. The major timing information of the KOMPSAT is OBT (On-Board Time which is formatted by the on-board computer of the spacecraft, based on 1Hz sync. pulse coming from the GPS receiver involved. The OBT is transmitted to ground station with the house-keeping telemetry data of the spacecraft while it is distributed to the instruments via 1553B data bus for synchronization during imaging and formatting. The timing information contained in the spacecraft telemetry data would have direct relation to the image data of the instruments, which should be well explained to get a more accurate image. This paper addresses the timing analysis of the KOMPSAT spacecraft and instruments, including the gyro data timing analysis for the correct restoration of the EOC and OSMI image data at ground station.

  1. Second order statistical analysis of US image texture

    International Nuclear Information System (INIS)

    Tanzi, F.; Novario, R.

    1999-01-01

    The study reports the sonographic image texture of the neonatal heart in different stages of development by calculating numerical parameters extracted from the gray scale co-occurrence matrix. To show pixel values differences and enhance texture structure, images were equalized and then the gray level range was reduced to 16 to allow sufficiently high occupancy frequency of the co-occurrence matrix. Differences are so little significant that they may be due to different factors affecting image texture and the variability introduced by manual ROI positioning; therefore no definitive conclusions can be drawn as to considering this kind of analysis capable of discriminating different stages of myocardial development [it

  2. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  3. Imaging for dismantlement verification: Information management and analysis algorithms

    International Nuclear Information System (INIS)

    Robinson, S.M.; Jarman, K.D.; Pitts, W.K.; Seifert, A.; Misner, A.C.; Woodring, M.L.; Myjak, M.J.

    2012-01-01

    The level of detail discernible in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes. An image will almost certainly contain highly sensitive information, and storing a comparison image will almost certainly violate a cardinal principle of information barriers: that no sensitive information be stored in the system. To overcome this problem, some features of the image might be reduced to a few parameters suitable for definition as an attribute, which must be non-sensitive to be acceptable in an Information Barrier regime. However, this process must be performed with care. Features like the perimeter, area, and intensity of an object, for example, might reveal sensitive information. Any data-reduction technique must provide sufficient information to discriminate a real object from a spoofed or incorrect one, while avoiding disclosure (or storage) of any sensitive object qualities. Ultimately, algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We discuss the utility of imaging for arms control applications and present three image-based verification algorithms in this context. The algorithms reduce full image information to non-sensitive feature information, in a process that is intended to enable verification while eliminating the possibility of image reconstruction. The underlying images can be highly detailed, since they are dynamically generated behind an information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography. We study these algorithms in terms of technical performance in image analysis and application to an information barrier scheme.

  4. SIMA: Python software for analysis of dynamic fluorescence imaging data

    Directory of Open Access Journals (Sweden)

    Patrick eKaifosh

    2014-09-01

    Full Text Available Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs, and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/.

  5. Perceptual and statistical analysis of cardiac phase and amplitude images

    International Nuclear Information System (INIS)

    Houston, A.; Craig, A.

    1991-01-01

    A perceptual experiment was conducted using cardiac phase and amplitude images. Estimates of statistical parameters were derived from the images and the diagnostic potential of human and statistical decisions compared. Five methods were used to generate the images from 75 gated cardiac studies, 39 of which were classified as pathological. The images were presented to 12 observers experienced in nuclear medicine. The observers rated the images using a five-category scale based on their confidence of an abnormality presenting. Circular and linear statistics were used to analyse phase and amplitude image data, respectively. Estimates of mean, standard deviation (SD), skewness, kurtosis and the first term of the spatial correlation function were evaluated in the region of the left ventricle. A receiver operating characteristic analysis was performed on both sets of data and the human and statistical decisions compared. For phase images, circular SD was shown to discriminate better between normal and abnormal than experienced observers, but no single statistic discriminated as well as the human observer for amplitude images. (orig.)

  6. Analysis of plasmaspheric plumes: CLUSTER and IMAGE observations

    Directory of Open Access Journals (Sweden)

    F. Darrouzet

    2006-07-01

    Full Text Available Plasmaspheric plumes have been routinely observed by CLUSTER and IMAGE. The CLUSTER mission provides high time resolution four-point measurements of the plasmasphere near perigee. Total electron density profiles have been derived from the electron plasma frequency identified by the WHISPER sounder supplemented, in-between soundings, by relative variations of the spacecraft potential measured by the electric field instrument EFW; ion velocity is also measured onboard these satellites. The EUV imager onboard the IMAGE spacecraft provides global images of the plasmasphere with a spatial resolution of 0.1 RE every 10 min; such images acquired near apogee from high above the pole show the geometry of plasmaspheric plumes, their evolution and motion. We present coordinated observations of three plume events and compare CLUSTER in-situ data with global images of the plasmasphere obtained by IMAGE. In particular, we study the geometry and the orientation of plasmaspheric plumes by using four-point analysis methods. We compare several aspects of plume motion as determined by different methods: (i inner and outer plume boundary velocity calculated from time delays of this boundary as observed by the wave experiment WHISPER on the four spacecraft, (ii drift velocity measured by the electron drift instrument EDI onboard CLUSTER and (iii global velocity determined from successive EUV images. These different techniques consistently indicate that plasmaspheric plumes rotate around the Earth, with their foot fully co-rotating, but with their tip rotating slower and moving farther out.

  7. Flying-spot analysis of solar images

    International Nuclear Information System (INIS)

    Azzarelli, L.; Carlesi, C.; Panicucci, R.; Falciani, R.; Giordano, M.; Rigutti, M.; Roberti, G.

    1975-01-01

    This work has been performed to test the new results obtained previously with a photographic isodensitometric method about the photometric evolution of solar flares and to study the degree of utility and reliability and the general performances of high speed, computer controlled devices in the photometric analysis of extended sources. Some series of good Hα solar filter grams, obtained during 1969 (May 15-16-17-25 and Oct 25-27), at the Athens National Observatory, with time resolution of about 30 sec, with uniform exposure and high photometric accuracy (approximately 5000 filtergrams) are studied. (Auth.)

  8. Analysis of an image quality assurance program

    International Nuclear Information System (INIS)

    Goethlin, J.H.; Alders, B.

    1985-01-01

    Reject film analysis before and after the introduction of a quality assurance program showed a 45% decrease in rejected films. The main changes in equipment and routines were: 1. Increased control of film processors and X-ray generators. 2. New film casettes and screens. 3. Decreased number of film sizes. 4. Information to and supervision of radiographing personnel. Savings in costs and increased income from an increased amount of out-patients corresponded to about 4.5% of the total cost of operating and maintaining the department. (orig.)

  9. MR image analysis: Longitudinal cardiac motion influences left ventricular measurements

    International Nuclear Information System (INIS)

    Berkovic, Patrick; Hemmink, Maarten; Parizel, Paul M.; Vrints, Christiaan J.; Paelinck, Bernard P.

    2010-01-01

    Background: Software for the analysis of left ventricular (LV) volumes and mass using border detection in short-axis images only, is hampered by through-plane cardiac motion. Therefore we aimed to evaluate software that involves longitudinal cardiac motion. Methods: Twenty-three consecutive patients underwent 1.5-Tesla cine magnetic resonance (MR) imaging of the entire heart in the long-axis and short-axis orientation with breath-hold steady-state free precession imaging. Offline analysis was performed using software that uses short-axis images (Medis MASS) and software that includes two-chamber and four-chamber images to involve longitudinal LV expansion and shortening (CAAS-MRV). Intraobserver and interobserver reproducibility was assessed by using Bland-Altman analysis. Results: Compared with MASS software, CAAS-MRV resulted in significantly smaller end-diastolic (156 ± 48 ml versus 167 ± 52 ml, p = 0.001) and end-systolic LV volumes (79 ± 48 ml versus 94 ± 52 ml, p < 0.001). In addition, CAAS-MRV resulted in higher LV ejection fraction (52 ± 14% versus 46 ± 13%, p < 0.001) and calculated LV mass (154 ± 52 g versus 142 ± 52 g, p = 0.004). Intraobserver and interobserver limits of agreement were similar for both methods. Conclusion: MR analysis of LV volumes and mass involving long-axis LV motion is a highly reproducible method, resulting in smaller LV volumes, higher ejection fraction and calculated LV mass.

  10. An optimal big data workflow for biomedical image analysis

    Directory of Open Access Journals (Sweden)

    Aurelle Tchagna Kouanou

    Full Text Available Background and objective: In the medical field, data volume is increasingly growing, and traditional methods cannot manage it efficiently. In biomedical computation, the continuous challenges are: management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of data, using machine learning and artificial intelligence techniques. It also allows a quick access to data using the NoSQL database. Thus, big data technologies include new frameworks to process medical data in a manner similar to biomedical images. It becomes very important to develop methods and/or architectures based on big data technologies, for a complete processing of biomedical image data. Method: This paper describes big data analytics for biomedical images, shows examples reported in the literature, briefly discusses new methods used in processing, and offers conclusions. We argue for adapting and extending related work methods in the field of big data software, using Hadoop and Spark frameworks. These provide an optimal and efficient architecture for biomedical image analysis. This paper thus gives a broad overview of big data analytics to automate biomedical image diagnosis. A workflow with optimal methods and algorithm for each step is proposed. Results: Two architectures for image classification are suggested. We use the Hadoop framework to design the first, and the Spark framework for the second. The proposed Spark architecture allows us to develop appropriate and efficient methods to leverage a large number of images for classification, which can be customized with respect to each other. Conclusions: The proposed architectures are more complete, easier, and are adaptable in all of the steps from conception. The obtained Spark architecture is the most complete, because it facilitates the implementation of algorithms with its embedded libraries. Keywords: Biomedical images, Big

  11. Image analysis of microsialograms of the mouse parotid gland using digital image processing

    International Nuclear Information System (INIS)

    Yoshiura, K.; Ohki, M.; Yamada, N.

    1991-01-01

    The authors compared two digital-image feature-extraction methods for the analysis of microsialograms of the mouse parotid gland following either overfilling, experimentally induced acute sialoadenitis or irradiation. Microsialograms were digitized using a drum-scanning microdensitometer. The grey levels were then partitioned into four bands representing soft tissue, peripheral minor, middle-sized and major ducts, and run-length and histogram analysis of the digital images performed. Serial analysis of microsialograms during progressive filling showed that both methods depicted the structural characteristics of the ducts at each grey level. However, in the experimental groups, run-length analysis showed slight changes in the peripheral duct system more clearly. This method was therefore considered more effective than histogram analysis

  12. Automated image analysis in the study of collagenous colitis

    DEFF Research Database (Denmark)

    Fiehn, Anne-Marie Kanstrup; Kristensson, Martin; Engel, Ulla

    2016-01-01

    PURPOSE: The aim of this study was to develop an automated image analysis software to measure the thickness of the subepithelial collagenous band in colon biopsies with collagenous colitis (CC) and incomplete CC (CCi). The software measures the thickness of the collagenous band on microscopic...... slides stained with Van Gieson (VG). PATIENTS AND METHODS: A training set consisting of ten biopsies diagnosed as CC, CCi, and normal colon mucosa was used to develop the automated image analysis (VG app) to match the assessment by a pathologist. The study set consisted of biopsies from 75 patients...

  13. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    Science.gov (United States)

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  14. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation

    International Nuclear Information System (INIS)

    Zhao, Zhanqi; Möller, Knut; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich

    2014-01-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton–Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR C ) and (4) GREIT with individual thorax geometry (GR T ). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal–Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms. (paper)

  15. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2014-06-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

  16. Software for 3D diagnostic image reconstruction and analysis

    International Nuclear Information System (INIS)

    Taton, G.; Rokita, E.; Sierzega, M.; Klek, S.; Kulig, J.; Urbanik, A.

    2005-01-01

    Recent advances in computer technologies have opened new frontiers in medical diagnostics. Interesting possibilities are the use of three-dimensional (3D) imaging and the combination of images from different modalities. Software prepared in our laboratories devoted to 3D image reconstruction and analysis from computed tomography and ultrasonography is presented. In developing our software it was assumed that it should be applicable in standard medical practice, i.e. it should work effectively with a PC. An additional feature is the possibility of combining 3D images from different modalities. The reconstruction and data processing can be conducted using a standard PC, so low investment costs result in the introduction of advanced and useful diagnostic possibilities. The program was tested on a PC using DICOM data from computed tomography and TIFF files obtained from a 3D ultrasound system. The results of the anthropomorphic phantom and patient data were taken into consideration. A new approach was used to achieve spatial correlation of two independently obtained 3D images. The method relies on the use of four pairs of markers within the regions under consideration. The user selects the markers manually and the computer calculates the transformations necessary for coupling the images. The main software feature is the possibility of 3D image reconstruction from a series of two-dimensional (2D) images. The reconstructed 3D image can be: (1) viewed with the most popular methods of 3D image viewing, (2) filtered and processed to improve image quality, (3) analyzed quantitatively (geometrical measurements), and (4) coupled with another, independently acquired 3D image. The reconstructed and processed 3D image can be stored at every stage of image processing. The overall software performance was good considering the relatively low costs of the hardware used and the huge data sets processed. The program can be freely used and tested (source code and program available at

  17. Mediman: Object oriented programming approach for medical image analysis

    International Nuclear Information System (INIS)

    Coppens, A.; Sibomana, M.; Bol, A.; Michel, C.

    1993-01-01

    Mediman is a new image analysis package which has been developed to analyze quantitatively Positron Emission Tomography (PET) data. It is object-oriented, written in C++ and its user interface is based on InterViews on top of which new classes have been added. Mediman accesses data using external data representation or import/export mechanism which avoids data duplication. Multimodality studies are organized in a simple database which includes images, headers, color tables, lists and objects of interest (OOI's) and history files. Stored color table parameters allow to focus directly on the interesting portion of the dynamic range. Lists allow to organize the study according to modality, acquisition protocol, time and spatial properties. OOI's (points, lines and regions) are stored in absolute 3-D coordinates allowing correlation with other co-registered imaging modalities such as MRI or SPECT. OOI's have visualization properties and are organized into groups. Quantitative ROI analysis of anatomic images consists of position, distance, volume calculation on selected OOI's. An image calculator is connected to mediman. Quantitation of metabolic images is performed via profiles, sectorization, time activity curves and kinetic modeling. Mediman is menu and mouse driven, macro-commands can be registered and replayed. Its interface is customizable through a configuration file. The benefit of the object-oriented approach are discussed from a development point of view

  18. Cardiac imaging: working towards fully-automated machine analysis & interpretation.

    Science.gov (United States)

    Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

    2017-03-01

    Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

  19. Cascaded image analysis for dynamic crack detection in material testing

    Science.gov (United States)

    Hampel, U.; Maas, H.-G.

    Concrete probes in civil engineering material testing often show fissures or hairline-cracks. These cracks develop dynamically. Starting at a width of a few microns, they usually cannot be detected visually or in an image of a camera imaging the whole probe. Conventional image analysis techniques will detect fissures only if they show a width in the order of one pixel. To be able to detect and measure fissures with a width of a fraction of a pixel at an early stage of their development, a cascaded image analysis approach has been developed, implemented and tested. The basic idea of the approach is to detect discontinuities in dense surface deformation vector fields. These deformation vector fields between consecutive stereo image pairs, which are generated by cross correlation or least squares matching, show a precision in the order of 1/50 pixel. Hairline-cracks can be detected and measured by applying edge detection techniques such as a Sobel operator to the results of the image matching process. Cracks will show up as linear discontinuities in the deformation vector field and can be vectorized by edge chaining. In practical tests of the method, cracks with a width of 1/20 pixel could be detected, and their width could be determined at a precision of 1/50 pixel.

  20. The analysis of image feature robustness using cometcloud

    Directory of Open Access Journals (Sweden)

    Xin Qi

    2012-01-01

    Full Text Available The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval.

  1. Reliability of tumor volume estimation from MR images in patients with malignant glioma. Results from the American College of Radiology Imaging Network (ACRIN) 6662 Trial

    International Nuclear Information System (INIS)

    Ertl-Wagner, Birgit B.; Blume, Jeffrey D.; Herman, Benjamin; Peck, Donald; Udupa, Jayaram K.; Levering, Anthony; Schmalfuss, Ilona M.

    2009-01-01

    Reliable assessment of tumor growth in malignant glioma poses a common problem both clinically and when studying novel therapeutic agents. We aimed to evaluate two software-systems in their ability to estimate volume change of tumor and/or edema on magnetic resonance (MR) images of malignant gliomas. Twenty patients with malignant glioma were included from different sites. Serial post-operative MR images were assessed with two software systems representative of the two fundamental segmentation methods, single-image fuzzy analysis (3DVIEWNIX-TV) and multi-spectral-image analysis (Eigentool), and with a manual method by 16 independent readers (eight MR-certified technologists, four neuroradiology fellows, four neuroradiologists). Enhancing tumor volume and tumor volume plus edema were assessed independently by each reader. Intraclass correlation coefficients (ICCs), variance components, and prediction intervals were estimated. There were no significant differences in the average tumor volume change over time between the software systems (p > 0.05). Both software systems were much more reliable and yielded smaller prediction intervals than manual measurements. No significant differences were observed between the volume changes determined by fellows/neuroradiologists or technologists.Semi-automated software systems are reliable tools to serve as outcome parameters in clinical studies and the basis for therapeutic decision-making for malignant gliomas, whereas manual measurements are less reliable and should not be the basis for clinical or research outcome studies. (orig.)

  2. Image decomposition as a tool for validating stress analysis models

    Directory of Open Access Journals (Sweden)

    Mottershead J.

    2010-06-01

    Full Text Available It is good practice to validate analytical and numerical models used in stress analysis for engineering design by comparison with measurements obtained from real components either in-service or in the laboratory. In reality, this critical step is often neglected or reduced to placing a single strain gage at the predicted hot-spot of stress. Modern techniques of optical analysis allow full-field maps of displacement, strain and, or stress to be obtained from real components with relative ease and at modest cost. However, validations continued to be performed only at predicted and, or observed hot-spots and most of the wealth of data is ignored. It is proposed that image decomposition methods, commonly employed in techniques such as fingerprinting and iris recognition, can be employed to validate stress analysis models by comparing all of the key features in the data from the experiment and the model. Image decomposition techniques such as Zernike moments and Fourier transforms have been used to decompose full-field distributions for strain generated from optical techniques such as digital image correlation and thermoelastic stress analysis as well as from analytical and numerical models by treating the strain distributions as images. The result of the decomposition is 101 to 102 image descriptors instead of the 105 or 106 pixels in the original data. As a consequence, it is relatively easy to make a statistical comparison of the image descriptors from the experiment and from the analytical/numerical model and to provide a quantitative assessment of the stress analysis.

  3. Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

    Science.gov (United States)

    Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

    2014-05-01

    The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

  4. Image Post-Processing and Analysis. Chapter 17

    Energy Technology Data Exchange (ETDEWEB)

    Yushkevich, P. A. [University of Pennsylvania, Philadelphia (United States)

    2014-09-15

    For decades, scientists have used computers to enhance and analyse medical images. At first, they developed simple computer algorithms to enhance the appearance of interesting features in images, helping humans read and interpret them better. Later, they created more advanced algorithms, where the computer would not only enhance images but also participate in facilitating understanding of their content. Segmentation algorithms were developed to detect and extract specific anatomical objects in images, such as malignant lesions in mammograms. Registration algorithms were developed to align images of different modalities and to find corresponding anatomical locations in images from different subjects. These algorithms have made computer aided detection and diagnosis, computer guided surgery and other highly complex medical technologies possible. Nowadays, the field of image processing and analysis is a complex branch of science that lies at the intersection of applied mathematics, computer science, physics, statistics and biomedical sciences. This chapter will give a general overview of the most common problems in this field and the algorithms that address them.

  5. Two-dimensional DFA scaling analysis applied to encrypted images

    Science.gov (United States)

    Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

    2015-01-01

    The technique of detrended fluctuation analysis (DFA) has been widely used to unveil scaling properties of many different signals. In this paper, we determine scaling properties in the encrypted images by means of a two-dimensional DFA approach. To carry out the image encryption, we use an enhanced cryptosystem based on a rule-90 cellular automaton and we compare the results obtained with its unmodified version and the encryption system AES. The numerical results show that the encrypted images present a persistent behavior which is close to that of the 1/f-noise. These results point to the possibility that the DFA scaling exponent can be used to measure the quality of the encrypted image content.

  6. Nonlinear Denoising and Analysis of Neuroimages With Kernel Principal Component Analysis and Pre-Image Estimation

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Abrahamsen, Trine Julie; Madsen, Kristoffer Hougaard

    2012-01-01

    We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising...... procedure is performed within a data-driven split-half evaluation framework. ii) We introduce manifold navigation for exploration of a nonlinear data manifold, and illustrate how pre-image estimation can be used to generate brain maps in the continuum between experimentally defined brain states/classes. We...

  7. Three-dimensional analysis and display of medical images

    International Nuclear Information System (INIS)

    Bajcsy, R.

    1985-01-01

    Until recently, the most common medical images were X-rays on film analyzed by an expert, ususally a radiologist, who used, in addition to his/her visual perceptual abilities, knowledge obtained through medical studies, and experience. Today, however, with the advent of various imaging techniques, X-ray computerized axial tomographs (CAT), positron emission tomographs (PET), ultrasound tomographs, nuclear magnetic resonance tomographs (NMR), just to mention a few, the images are generated by computers and displayed on computer-controlled devices; so it is appropriate to think about more quantitative and perhaps automated ways of data analysis. Furthermore, since the data are generated by computer, it is only natural to take advantage of the computer for analysis purposes. In addition, using the computer, one can analyze more data and relate different modalities from the same subject, such as, for example, comparing the CAT images with PET images from the same subject. In the next section (The PET Scanner) the authors shall only briefly mention with appropriate references the modeling of the positron emission tomographic scanner, since this imaging technique is not as widely described in the literature as the CAT scanner. The modeling of the interpreter is not going to be mentioned, since it is a topic that by itself deserves a full paper; see, for example, Pizer [1981]. The thrust of this chapter is on modeling the organs that are being imaged and the matching techniques between the model and the data. The image data is from CAT and PET scans. Although the authors believe that their techniques are applicable to any organ of the human body, the examples are only from the brain

  8. SENTINEL-2 LEVEL 1 PRODUCTS AND IMAGE PROCESSING PERFORMANCES

    OpenAIRE

    S. J. Baillarin; A. Meygret; C. Dechoz; B. Petrucci; S. Lacherade; T. Tremas; C. Isola; P. Martimort; F. Spoto

    2012-01-01

    In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES) program, the European Space Agency (ESA) is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. While ensuring data continuity of former SPOT and LANDSAT multi-spectral missions, Sentinel-2 wil...

  9. Secure thin client architecture for DICOM image analysis

    Science.gov (United States)

    Mogatala, Harsha V. R.; Gallet, Jacqueline

    2005-04-01

    This paper presents a concept of Secure Thin Client (STC) Architecture for Digital Imaging and Communications in Medicine (DICOM) image analysis over Internet. STC Architecture provides in-depth analysis and design of customized reports for DICOM images using drag-and-drop and data warehouse technology. Using a personal computer and a common set of browsing software, STC can be used for analyzing and reporting detailed patient information, type of examinations, date, Computer Tomography (CT) dose index, and other relevant information stored within the images header files as well as in the hospital databases. STC Architecture is three-tier architecture. The First-Tier consists of drag-and-drop web based interface and web server, which provides customized analysis and reporting ability to the users. The Second-Tier consists of an online analytical processing (OLAP) server and database system, which serves fast, real-time, aggregated multi-dimensional data using OLAP technology. The Third-Tier consists of a smart algorithm based software program which extracts DICOM tags from CT images in this particular application, irrespective of CT vendor's, and transfers these tags into a secure database system. This architecture provides Winnipeg Regional Health Authorities (WRHA) with quality indicators for CT examinations in the hospitals. It also provides health care professionals with analytical tool to optimize radiation dose and image quality parameters. The information is provided to the user by way of a secure socket layer (SSL) and role based security criteria over Internet. Although this particular application has been developed for WRHA, this paper also discusses the effort to extend the Architecture to other hospitals in the region. Any DICOM tag from any imaging modality could be tracked with this software.

  10. Imaging spectroscopic analysis at the Advanced Light Source

    International Nuclear Information System (INIS)

    MacDowell, A. A.; Warwick, T.; Anders, S.; Lamble, G.M.; Martin, M.C.; McKinney, W.R.; Padmore, H.A.

    1999-01-01

    One of the major advances at the high brightness third generation synchrotrons is the dramatic improvement of imaging capability. There is a large multi-disciplinary effort underway at the ALS to develop imaging X-ray, UV and Infra-red spectroscopic analysis on a spatial scale from. a few microns to 10nm. These developments make use of light that varies in energy from 6meV to 15KeV. Imaging and spectroscopy are finding applications in surface science, bulk materials analysis, semiconductor structures, particulate contaminants, magnetic thin films, biology and environmental science. This article is an overview and status report from the developers of some of these techniques at the ALS. The following table lists all the currently available microscopes at the. ALS. This article will describe some of the microscopes and some of the early applications

  11. Image processing and analysis using neural networks for optometry area

    Science.gov (United States)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  12. Automated rice leaf disease detection using color image analysis

    Science.gov (United States)

    Pugoy, Reinald Adrian D. L.; Mariano, Vladimir Y.

    2011-06-01

    In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as a manual eyeball exercise, is important to come up with good nutrient and disease management strategies. In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then, these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.

  13. Analysis and Comparison of Objective Methods for Image Quality Assessment

    Directory of Open Access Journals (Sweden)

    P. S. Babkin

    2014-01-01

    Full Text Available The purpose of this work is research and modification of the reference objective methods for image quality assessment. The ultimate goal is to obtain a modification of formal assessments that more closely corresponds to the subjective expert estimates (MOS.In considering the formal reference objective methods for image quality assessment we used the results of other authors, which offer results and comparative analyzes of the most effective algorithms. Based on these investigations we have chosen two of the most successful algorithm for which was made a further analysis in the MATLAB 7.8 R 2009 a (PQS and MSSSIM. The publication focuses on the features of the algorithms, which have great importance in practical implementation, but are insufficiently covered in the publications by other authors.In the implemented modification of the algorithm PQS boundary detector Kirsch was replaced by the boundary detector Canny. Further experiments were carried out according to the method of the ITU-R VT.500-13 (01/2012 using monochrome images treated with different types of filters (should be emphasized that an objective assessment of image quality PQS is applicable only to monochrome images. Images were obtained with a thermal imaging surveillance system. The experimental results proved the effectiveness of this modification.In the specialized literature in the field of formal to evaluation methods pictures, this type of modification was not mentioned.The method described in the publication can be applied to various practical implementations of digital image processing.Advisability and effectiveness of using the modified method of PQS to assess the structural differences between the images are shown in the article and this will be used in solving the problems of identification and automatic control.

  14. The Medical Analysis of Child Sexual Abuse Images

    Science.gov (United States)

    Cooper, Sharon W.

    2011-01-01

    Analysis of child sexual abuse images, commonly referred to as pornography, requires a familiarity with the sexual maturation rating of children and an understanding of growth and development parameters. This article explains barriers that exist in working in this area of child abuse, the differences between subjective and objective analyses,…

  15. Evaluating wood failure in plywood shear by optical image analysis

    Science.gov (United States)

    Charles W. McMillin

    1984-01-01

    This exploratory study evaulates the potential of using an automatic image analysis method to measure percent wood failure in plywood shear specimens. The results suggest that this method my be as accurate as the visual method in tracking long-term gluebond quality. With further refinement, the method could lead to automated equipment replacing the subjective visual...

  16. Identification of Trichoderma strains by image analysis of HPLC chromatograms

    DEFF Research Database (Denmark)

    Thrane, Ulf; Poulsen, S.B.; Nirenberg, H.I.

    2001-01-01

    Forty-four Trichoderma strains from water-damaged building materials or indoor dust were classified with chromatographic image analysis on full chromatographic matrices obtained by high performance liquid chromatography with UV detection of culture extracts. The classes were compared with morphol...

  17. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2003-01-01

    Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  18. Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

    Science.gov (United States)

    Stankov, L

    1979-07-01

    The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

  19. Quantifying biodiversity using digital cameras and automated image analysis.

    Science.gov (United States)

    Roadknight, C. M.; Rose, R. J.; Barber, M. L.; Price, M. C.; Marshall, I. W.

    2009-04-01

    Monitoring the effects on biodiversity of extensive grazing in complex semi-natural habitats is labour intensive. There are also concerns about the standardization of semi-quantitative data collection. We have chosen to focus initially on automating the most time consuming aspect - the image analysis. The advent of cheaper and more sophisticated digital camera technology has lead to a sudden increase in the number of habitat monitoring images and information that is being collected. We report on the use of automated trail cameras (designed for the game hunting market) to continuously capture images of grazer activity in a variety of habitats at Moor House National Nature Reserve, which is situated in the North of England at an average altitude of over 600m. Rainfall is high, and in most areas the soil consists of deep peat (1m to 3m), populated by a mix of heather, mosses and sedges. The cameras have been continuously in operation over a 6 month period, daylight images are in full colour and night images (IR flash) are black and white. We have developed artificial intelligence based methods to assist in the analysis of the large number of images collected, generating alert states for new or unusual image conditions. This paper describes the data collection techniques, outlines the quantitative and qualitative data collected and proposes online and offline systems that can reduce the manpower overheads and increase focus on important subsets in the collected data. By converting digital image data into statistical composite data it can be handled in a similar way to other biodiversity statistics thus improving the scalability of monitoring experiments. Unsupervised feature detection methods and supervised neural methods were tested and offered solutions to simplifying the process. Accurate (85 to 95%) categorization of faunal content can be obtained, requiring human intervention for only those images containing rare animals or unusual (undecidable) conditions, and

  20. Image Processing Tools for Improved Visualization and Analysis of Remotely Sensed Images for Agriculture and Forest Classifications

    OpenAIRE

    SINHA G. R.

    2017-01-01

    This paper suggests Image Processing tools for improved visualization and better analysis of remotely sensed images. There are methods already available in literature for the purpose but the most important challenge among the limitations is lack of robustness. We propose an optimal method for image enhancement of the images using fuzzy based approaches and few optimization tools. The segmentation images subsequently obtained after de-noising will be classified into distinct information and th...

  1. Semivariogram Analysis of Bone Images Implemented on FPGA Architectures.

    Science.gov (United States)

    Shirvaikar, Mukul; Lagadapati, Yamuna; Dong, Xuanliang

    2017-03-01

    Osteoporotic fractures are a major concern for the healthcare of elderly and female populations. Early diagnosis of patients with a high risk of osteoporotic fractures can be enhanced by introducing second-order statistical analysis of bone image data using techniques such as variogram analysis. Such analysis is computationally intensive thereby creating an impediment for introduction into imaging machines found in common clinical settings. This paper investigates the fast implementation of the semivariogram algorithm, which has been proven to be effective in modeling bone strength, and should be of interest to readers in the areas of computer-aided diagnosis and quantitative image analysis. The semivariogram is a statistical measure of the spatial distribution of data, and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. A semi-variance, γ ( h ), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h . Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O ( n 2 ) Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current

  2. Automatic analysis of image quality control for Image Guided Radiation Therapy (IGRT) devices in external radiotherapy

    International Nuclear Information System (INIS)

    Torfeh, Tarraf

    2009-01-01

    On-board imagers mounted on a radiotherapy treatment machine are very effective devices that improve the geometric accuracy of radiation delivery. However, a precise and regular quality control program is required in order to achieve this objective. Our purpose consisted of developing software tools dedicated to an automatic image quality control of IGRT devices used in external radiotherapy: 2D-MV mode for measuring patient position during the treatment using high energy images, 2D-kV mode (low energy images) and 3D Cone Beam Computed Tomography (CBCT) MV or kV mode, used for patient positioning before treatment. Automated analysis of the Winston and Lutz test was also proposed. This test is used for the evaluation of the mechanical aspects of treatment machines on which additional constraints are carried out due to the on-board imagers additional weights. Finally, a technique of generating digital phantoms in order to assess the performance of the proposed software tools is described. Software tools dedicated to an automatic quality control of IGRT devices allow reducing by a factor of 100 the time spent by the medical physics team to analyze the results of controls while improving their accuracy by using objective and reproducible analysis and offering traceability through generating automatic monitoring reports and statistical studies. (author) [fr

  3. An Integrative Object-Based Image Analysis Workflow for Uav Images

    Science.gov (United States)

    Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

    2016-06-01

    In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  4. AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

    Directory of Open Access Journals (Sweden)

    H. Yu

    2016-06-01

    Full Text Available In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA. More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC. Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  5. GANALYZER: A TOOL FOR AUTOMATIC GALAXY IMAGE ANALYSIS

    International Nuclear Information System (INIS)

    Shamir, Lior

    2011-01-01

    We describe Ganalyzer, a model-based tool that can automatically analyze and classify galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ∼10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large data sets of galaxy images collected by autonomous sky surveys such as SDSS, LSST, or DES. The software is available for free download at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer, and the data used in the experiment are available at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer/GalaxyImages.zip.

  6. Ganalyzer: A Tool for Automatic Galaxy Image Analysis

    Science.gov (United States)

    Shamir, Lior

    2011-08-01

    We describe Ganalyzer, a model-based tool that can automatically analyze and classify galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ~10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large data sets of galaxy images collected by autonomous sky surveys such as SDSS, LSST, or DES. The software is available for free download at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer, and the data used in the experiment are available at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer/GalaxyImages.zip.

  7. Image analysis and machine learning for detecting malaria.

    Science.gov (United States)

    Poostchi, Mahdieh; Silamut, Kamolrat; Maude, Richard J; Jaeger, Stefan; Thoma, George

    2018-04-01

    Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts at fighting the disease. One of the barriers toward a successful mortality reduction has been inadequate malaria diagnosis in particular. To improve diagnosis, image analysis software and machine learning methods have been used to quantify parasitemia in microscopic blood slides. This article gives an overview of these techniques and discusses the current developments in image analysis and machine learning for microscopic malaria diagnosis. We organize the different approaches published in the literature according to the techniques used for imaging, image preprocessing, parasite detection and cell segmentation, feature computation, and automatic cell classification. Readers will find the different techniques listed in tables, with the relevant articles cited next to them, for both thin and thick blood smear images. We also discussed the latest developments in sections devoted to deep learning and smartphone technology for future malaria diagnosis. Published by Elsevier Inc.

  8. Positron emission tomography: Physics, instrumentation, and image analysis

    International Nuclear Information System (INIS)

    Porenta, G.

    1994-01-01

    Positron emission tomography (PET) is a noninvasive diagnostic technique that permits reconstruction of cross-sectional images of the human body which depict the biodistribution of PET tracer substances. A large variety of physiological PET tracers, mostly based on isotopes of carbon, nitrogen, oxygen, and fluorine is available and allows the in vivo investigation of organ perfusion, metabolic pathways and biomolecular processes in normal and diseased states. PET cameras utilize the physical characteristics of positron decay to derive quantitative measurements of tracer concentrations, a capability that has so far been elusive for conventional SPECT (single photon emission computed tomography) imaging techniques. Due to the short half lives of most PET isotopes, an on-site cyclotron and a radiochemistry unit are necessary to provide an adequate supply of PET tracers. While operating a PET center in the past was a complex procedure restricted to few academic centers with ample resources. PET technology has rapidly advanced in recent years and has entered the commercial nuclear medicine market. To date, the availability of compact cyclotrons with remote computer control, automated synthesis units for PET radiochemistry, high-performance PET cameras, and userfriendly analysis workstations permits installation of a clinical PET center within most nuclear medicine facilities. This review provides simple descriptions of important aspects concerning physics, instrumentation, and image analysis in PET imaging which should be understood by medical personnel involved in the clinical operation of a PET imaging center. (author)

  9. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir; Tsvankin, Ilya; Alkhalifah, Tariq Ali

    2016-01-01

    Extended images obtained from reverse time migration (RTM) contain information about the accuracy of the velocity field and subsurface illumination at different incidence angles. Here, we evaluate the influence of errors in the anisotropy parameters on the shape of the residual moveout (RMO) in P-wave RTM extended images for VTI (transversely isotropic with a vertical symmetry axis) media. Using the actual spatial distribution of the zero-dip NMO velocity (Vnmo), which could be approximately estimated by conventional techniques, we analyze the extended images obtained with distorted fields of the parameters η and δ. Differential semblance optimization (DSO) and stack-power estimates are employed to study the sensitivity of focusing to the anisotropy parameters. We also build angle gathers to facilitate interpretation of the shape of RMO in the extended images. The results show that the signature of η is dip-dependent, whereas errors in δ cause defocusing only if that parameter is laterally varying. Hence, earlier results regarding the influence of η and δ on reflection moveout and migration velocity analysis remain generally valid in the extended image space for complex media. The dependence of RMO on errors in the anisotropy parameters provides essential insights for anisotropic wavefield tomography using extended images.

  10. Semi-automated analysis of three-dimensional track images

    International Nuclear Information System (INIS)

    Meesen, G.; Poffijn, A.

    2001-01-01

    In the past, three-dimensional (3-d) track images in solid state detectors were difficult to obtain. With the introduction of the confocal scanning laser microscope it is now possible to record 3-d track images in a non-destructive way. These 3-d track images can latter be used to measure typical track parameters. Preparing the detectors and recording the 3-d images however is only the first step. The second step in this process is enhancing the image quality by means of deconvolution techniques to obtain the maximum possible resolution. The third step is extracting the typical track parameters. This can be done on-screen by an experienced operator. For large sets of data however, this manual technique is not desirable. This paper will present some techniques to analyse 3-d track data in an automated way by means of image analysis routines. Advanced thresholding techniques guarantee stable results in different recording situations. By using pre-knowledge about the track shape, reliable object identification is obtained. In case of ambiguity, manual intervention is possible

  11. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir

    2016-04-28

    Extended images obtained from reverse time migration (RTM) contain information about the accuracy of the velocity field and subsurface illumination at different incidence angles. Here, we evaluate the influence of errors in the anisotropy parameters on the shape of the residual moveout (RMO) in P-wave RTM extended images for VTI (transversely isotropic with a vertical symmetry axis) media. Using the actual spatial distribution of the zero-dip NMO velocity (Vnmo), which could be approximately estimated by conventional techniques, we analyze the extended images obtained with distorted fields of the parameters η and δ. Differential semblance optimization (DSO) and stack-power estimates are employed to study the sensitivity of focusing to the anisotropy parameters. We also build angle gathers to facilitate interpretation of the shape of RMO in the extended images. The results show that the signature of η is dip-dependent, whereas errors in δ cause defocusing only if that parameter is laterally varying. Hence, earlier results regarding the influence of η and δ on reflection moveout and migration velocity analysis remain generally valid in the extended image space for complex media. The dependence of RMO on errors in the anisotropy parameters provides essential insights for anisotropic wavefield tomography using extended images.

  12. Parallel multiple instance learning for extremely large histopathology image analysis.

    Science.gov (United States)

    Xu, Yan; Li, Yeshu; Shen, Zhengyang; Wu, Ziwei; Gao, Teng; Fan, Yubo; Lai, Maode; Chang, Eric I-Chao

    2017-08-03

    Histopathology images are critical for medical diagnosis, e.g., cancer and its treatment. A standard histopathology slice can be easily scanned at a high resolution of, say, 200,000×200,000 pixels. These high resolution images can make most existing imaging processing tools infeasible or less effective when operated on a single machine with limited memory, disk space and computing power. In this paper, we propose an algorithm tackling this new emerging "big data" problem utilizing parallel computing on High-Performance-Computing (HPC) clusters. Experimental results on a large-scale data set (1318 images at a scale of 10 billion pixels each) demonstrate the efficiency and effectiveness of the proposed algorithm for low-latency real-time applications. The framework proposed an effective and efficient system for extremely large histopathology image analysis. It is based on the multiple instance learning formulation for weakly-supervised learning for image classification, segmentation and clustering. When a max-margin concept is adopted for different clusters, we obtain further improvement in clustering performance.

  13. Analysis and improvement of the quantum image matching

    Science.gov (United States)

    Dang, Yijie; Jiang, Nan; Hu, Hao; Zhang, Wenyin

    2017-11-01

    We investigate the quantum image matching algorithm proposed by Jiang et al. (Quantum Inf Process 15(9):3543-3572, 2016). Although the complexity of this algorithm is much better than the classical exhaustive algorithm, there may be an error in it: After matching the area between two images, only the pixel at the upper left corner of the matched area played part in following steps. That is to say, the paper only matched one pixel, instead of an area. If more than one pixels in the big image are the same as the one at the upper left corner of the small image, the algorithm will randomly measure one of them, which causes the error. In this paper, an improved version is presented which takes full advantage of the whole matched area to locate a small image in a big image. The theoretical analysis indicates that the network complexity is higher than the previous algorithm, but it is still far lower than the classical algorithm. Hence, this algorithm is still efficient.

  14. Semiautomated analysis of embryoscope images: Using localized variance of image intensity to detect embryo developmental stages.

    Science.gov (United States)

    Mölder, Anna; Drury, Sarah; Costen, Nicholas; Hartshorne, Geraldine M; Czanner, Silvester

    2015-02-01

    Embryo selection in in vitro fertilization (IVF) treatment has traditionally been done manually using microscopy at intermittent time points during embryo development. Novel technique has made it possible to monitor embryos using time lapse for long periods of time and together with the reduced cost of data storage, this has opened the door to long-term time-lapse monitoring, and large amounts of image material is now routinely gathered. However, the analysis is still to a large extent performed manually, and images are mostly used as qualitative reference. To make full use of the increased amount of microscopic image material, (semi)automated computer-aided tools are needed. An additional benefit of automation is the establishment of standardization tools for embryo selection and transfer, making decisions more transparent and less subjective. Another is the possibility to gather and analyze data in a high-throughput manner, gathering data from multiple clinics and increasing our knowledge of early human embryo development. In this study, the extraction of data to automatically select and track spatio-temporal events and features from sets of embryo images has been achieved using localized variance based on the distribution of image grey scale levels. A retrospective cohort study was performed using time-lapse imaging data derived from 39 human embryos from seven couples, covering the time from fertilization up to 6.3 days. The profile of localized variance has been used to characterize syngamy, mitotic division and stages of cleavage, compaction, and blastocoel formation. Prior to analysis, focal plane and embryo location were automatically detected, limiting precomputational user interaction to a calibration step and usable for automatic detection of region of interest (ROI) regardless of the method of analysis. The results were validated against the opinion of clinical experts. © 2015 International Society for Advancement of Cytometry. © 2015 International

  15. Parallel imaging: is GRAPPA a useful acquisition tool for MR imaging intended for volumetric brain analysis?

    Directory of Open Access Journals (Sweden)

    Frank Anders

    2009-08-01

    Full Text Available Abstract Background The work presented here investigates parallel imaging applied to T1-weighted high resolution imaging for use in longitudinal volumetric clinical studies involving Alzheimer's disease (AD and Mild Cognitive Impairment (MCI patients. This was in an effort to shorten acquisition times to minimise the risk of motion artefacts caused by patient discomfort and disorientation. The principle question is, "Can parallel imaging be used to acquire images at 1.5 T of sufficient quality to allow volumetric analysis of patient brains?" Methods Optimisation studies were performed on a young healthy volunteer and the selected protocol (including the use of two different parallel imaging acceleration factors was then tested on a cohort of 15 elderly volunteers including MCI and AD patients. In addition to automatic brain segmentation, hippocampus volumes were manually outlined and measured in all patients. The 15 patients were scanned on a second occasion approximately one week later using the same protocol and evaluated in the same manner to test repeatability of measurement using images acquired with the GRAPPA parallel imaging technique applied to the MPRAGE sequence. Results Intraclass correlation tests show that almost perfect agreement between repeated measurements of both segmented brain parenchyma fraction and regional measurement of hippocampi. The protocol is suitable for both global and regional volumetric measurement dementia patients. Conclusion In summary, these results indicate that parallel imaging can be used without detrimental effect to brain tissue segmentation and volumetric measurement and should be considered for both clinical and research studies where longitudinal measurements of brain tissue volumes are of interest.

  16. Preliminary PCA/TT Results on MRO CRISM Multispectral Images

    Science.gov (United States)

    Klassen, David R.; Smith, M. D.

    2010-10-01

    Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One goal of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From these data we can create image cubes using 64 wavelengths from 0.410 to 3.923 µm. We present here our analysis of these multispectral mode data products using Principal Components Analysis (PCA) and Target Transformation (TT) [1]. Previous work with ground-based images [2-5] has shown that over an entire visible hemisphere, there are only three to four meaningful components using 32-105 wavelengths over 1.5-4.1 µm the first two are consistent over all temporal scales. The TT retrieved spectral endmembers show nearly the same level of consistency [5]. The preliminary work on the CRISM images cubes implies similar results; three to four significant principal components that are fairly consistent over time. These components are then used in TT to find spectral endmembers which can be used to characterize the surface reflectance for future use in radiative transfer cloud optical depth retrievals. We present here the PCA/TT results comparing the principal components and recovered endmembers from six reconstructed CRISM multi-spectral image cubes. References: [1] Bandfield, J. L., et al. (2000) JGR, 105, 9573. [2] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [4] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [5] Klassen, D. R. (2009) Icarus, 204, 32.

  17. Novel axolotl cardiac function analysis method using magnetic resonance imaging.

    Directory of Open Access Journals (Sweden)

    Pedro Gomes Sanches

    Full Text Available The salamander axolotl is capable of complete regeneration of amputated heart tissue. However, non-invasive imaging tools for assessing its cardiac function were so far not employed. In this study, cardiac magnetic resonance imaging is introduced as a non-invasive technique to image heart function of axolotls. Three axolotls were imaged with magnetic resonance imaging using a retrospectively gated Fast Low Angle Shot cine sequence. Within one scanning session the axolotl heart was imaged three times in all planes, consecutively. Heart rate, ejection fraction, stroke volume and cardiac output were calculated using three techniques: (1 combined long-axis, (2 short-axis series, and (3 ultrasound (control for heart rate only. All values are presented as mean ± standard deviation. Heart rate (beats per minute among different animals was 32.2±6.0 (long axis, 30.4±5.5 (short axis and 32.7±4.9 (ultrasound and statistically similar regardless of the imaging method (p > 0.05. Ejection fraction (% was 59.6±10.8 (long axis and 48.1±11.3 (short axis and it differed significantly (p = 0.019. Stroke volume (μl/beat was 133.7±33.7 (long axis and 93.2±31.2 (short axis, also differed significantly (p = 0.015. Calculations were consistent among the animals and over three repeated measurements. The heart rate varied depending on depth of anaesthesia. We described a new method for defining and imaging the anatomical planes of the axolotl heart and propose one of our techniques (long axis analysis may prove useful in defining cardiac function in regenerating axolotl hearts.

  18. Spectral analysis of mammographic images using a multitaper method

    International Nuclear Information System (INIS)

    Wu Gang; Mainprize, James G.; Yaffe, Martin J.

    2012-01-01

    Purpose: Power spectral analysis in radiographic images is conventionally performed using a windowed overlapping averaging periodogram. This study describes an alternative approach using a multitaper technique and compares its performance with that of the standard method. This tool will be valuable in power spectrum estimation of images, whose content deviates significantly from uniform white noise. The performance of the multitaper approach will be evaluated in terms of spectral stability, variance reduction, bias, and frequency precision. The ultimate goal is the development of a useful tool for image quality assurance. Methods: A multitaper approach uses successive data windows of increasing order. This mitigates spectral leakage allowing one to calculate a reduced-variance power spectrum. The multitaper approach will be compared with the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom, NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems, and the estimation of the anatomic noise in mammographic images (simulated images and clinical mammograms). Results: Examination of spectrum variance versus frequency resolution and bias indicates that the multitaper approach is superior to the conventional single taper methods in the prevention of spectrum leakage and variance reduction. More than four times finer frequency precision can be achieved with equivalent or less variance and bias. Conclusions: Without any shortening of the image data length, the bias is smaller and the frequency resolution is higher with the multitaper method, and the need to compromise in the choice of regions of interest size to balance between the reduction of variance and the loss of frequency resolution is largely eliminated.

  19. Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

    Science.gov (United States)

    Bigler, Erin D

    2015-09-01

    Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

  20. Identification of Fusarium damaged wheat kernels using image analysis

    Directory of Open Access Journals (Sweden)

    Ondřej Jirsa

    2011-01-01

    Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.

  1. Image segmentation and particles classification using texture analysis method

    Directory of Open Access Journals (Sweden)

    Mayar Aly Atteya

    Full Text Available Introduction: Ingredients of oily fish include a large amount of polyunsaturated fatty acids, which are important elements in various metabolic processes of humans, and have also been used to prevent diseases. However, in an attempt to reduce cost, recent developments are starting a replace the ingredients of fish oil with products of microalgae, that also produce polyunsaturated fatty acids. To do so, it is important to closely monitor morphological changes in algae cells and monitor their age in order to achieve the best results. This paper aims to describe an advanced vision-based system to automatically detect, classify, and track the organic cells using a recently developed SOPAT-System (Smart On-line Particle Analysis Technology, a photo-optical image acquisition device combined with innovative image analysis software. Methods The proposed method includes image de-noising, binarization and Enhancement, as well as object recognition, localization and classification based on the analysis of particles’ size and texture. Results The methods allowed for correctly computing cell’s size for each particle separately. By computing an area histogram for the input images (1h, 18h, and 42h, the variation could be observed showing a clear increase in cell. Conclusion The proposed method allows for algae particles to be correctly identified with accuracies up to 99% and classified correctly with accuracies up to 100%.

  2. Applications of wavelets in morphometric analysis of medical images

    Science.gov (United States)

    Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

    2003-11-01

    Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

  3. Quantitative imaging analysis of posterior fossa ependymoma location in children.

    Science.gov (United States)

    Sabin, Noah D; Merchant, Thomas E; Li, Xingyu; Li, Yimei; Klimo, Paul; Boop, Frederick A; Ellison, David W; Ogg, Robert J

    2016-08-01

    Imaging descriptions of posterior fossa ependymoma in children have focused on magnetic resonance imaging (MRI) signal and local anatomic relationships with imaging location only recently used to classify these neoplasms. We developed a quantitative method for analyzing the location of ependymoma in the posterior fossa, tested its effectiveness in distinguishing groups of tumors, and examined potential associations of distinct tumor groups with treatment and prognostic factors. Pre-operative MRI examinations of the brain for 38 children with histopathologically proven posterior fossa ependymoma were analyzed. Tumor margin contours and anatomic landmarks were manually marked and used to calculate the centroid of each tumor. Landmarks were used to calculate a transformation to align, scale, and rotate each patient's image coordinates to a common coordinate space. Hierarchical cluster analysis of the location and morphological variables was performed to detect multivariate patterns in tumor characteristics. The ependymomas were also characterized as "central" or "lateral" based on published radiological criteria. Therapeutic details and demographic, recurrence, and survival information were obtained from medical records and analyzed with the tumor location and morphology to identify prognostic tumor characteristics. Cluster analysis yielded two distinct tumor groups based on centroid location The cluster groups were associated with differences in PFS (p = .044), "central" vs. "lateral" radiological designation (p = .035), and marginally associated with multiple operative interventions (p = .064). Posterior fossa ependymoma can be objectively classified based on quantitative analysis of tumor location, and these classifications are associated with prognostic and treatment factors.

  4. Registration and analysis for images couple : application to mammograms

    OpenAIRE

    Boucher, Arnaud

    2014-01-01

    Advisor: Nicole Vincent. Date and location of PhD thesis defense: 10 January 2013, University of Paris Descartes In this thesis, the problem addressed is the development of a computer-aided diagnosis system (CAD) based on conjoint analysis of several images, and therefore on the comparison of these medical images. The particularity of our approach is to look for evolutions or aberrant new tissues in a given set, rather than attempting to characterize, with a strong a priori, the type of ti...

  5. Noise estimation for remote sensing image data analysis

    Science.gov (United States)

    Du, Qian

    2004-01-01

    Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.

  6. Image Chunking: Defining Spatial Building Blocks for Scene Analysis.

    Science.gov (United States)

    1987-04-01

    mumgs0.USmusa 7.AUWOJO 4. CIUTAC Rm6ANT Wuugme*j James V/. Mlahoney DACA? 6-85-C-00 10 NOQ 1 4-85-K-O 124 Artificial Inteligence Laboratory US USS 545...0197 672 IMAGE CHUWING: DEINING SPATIAL UILDING PLOCKS FOR 142 SCENE ANRLYSIS(U) MASSACHUSETTS INST OF TECH CAIIAIDGE ARTIFICIAL INTELLIGENCE LAO J...Technical Report 980 F-Image Chunking: Defining Spatial Building Blocks for Scene DTm -Analysis S ELECTED James V. Mahoney’ MIT Artificial Intelligence

  7. Diffraction imaging and velocity analysis using oriented velocity continuation

    KAUST Repository

    Decker, Luke

    2014-08-05

    We perform seismic diffraction imaging and velocity analysis by separating diffractions from specular reflections and decomposing them into slope components. We image slope components using extrapolation in migration velocity in time-space-slope coordinates. The extrapolation is described by a convection-type partial differential equation and implemented efficiently in the Fourier domain. Synthetic and field data experiments show that the proposed algorithm is able to detect accurate time-migration velocities by automatically measuring the flatness of events in dip-angle gathers.

  8. Uniform color space analysis of LACIE image products

    Science.gov (United States)

    Nalepka, R. F. (Principal Investigator); Balon, R. J.; Cicone, R. C.

    1979-01-01

    The author has identified the following significant results. Analysis and comparison of image products generated by different algorithms show that the scaling and biasing of data channels for control of PFC primaries lead to loss of information (in a probability-of misclassification sense) by two major processes. In order of importance they are: neglecting the input of one channel of data in any one image, and failing to provide sufficient color resolution of the data. The scaling and biasing approach tends to distort distance relationships in data space and provides less than desirable resolution when the data variation is typical of a developed, nonhazy agricultural scene.

  9. Quantitative image analysis in sonograms of the thyroid gland

    Energy Technology Data Exchange (ETDEWEB)

    Catherine, Skouroliakou [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece); Maria, Lyra [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece)]. E-mail: mlyra@pindos.uoa.gr; Aristides, Antoniou [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece); Lambros, Vlahos [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece)

    2006-12-20

    High-resolution, real-time ultrasound is a routine examination for assessing the disorders of the thyroid gland. However, the current diagnosis practice is based mainly on qualitative evaluation of the resulting sonograms, therefore depending on the physician's experience. Computerized texture analysis is widely employed in sonographic images of various organs (liver, breast), and it has been proven to increase the sensitivity of diagnosis by providing a better tissue characterization. The present study attempts to characterize thyroid tissue by automatic texture analysis. The texture features that are calculated are based on co-occurrence matrices as they have been proposed by Haralick. The sample consists of 40 patients. For each patient two sonographic images (one for each lobe) are recorded in DICOM format. The lobe is manually delineated in each sonogram, and the co-occurrence matrices for 52 separation vectors are calculated. The texture features extracted from each one of these matrices are: contrast, correlation, energy and homogeneity. Primary component analysis is used to select the optimal set of features. The statistical analysis resulted in the extraction of 21 optimal descriptors. The optimal descriptors are all co-occurrence parameters as the first-order statistics did not prove to be representative of the images characteristics. The bigger number of components depends mainly on correlation for very close or very far distances. The results indicate that quantitative analysis of thyroid sonograms can provide an objective characterization of thyroid tissue.

  10. Componential distribution analysis of food using near infrared ray image

    Science.gov (United States)

    Yamauchi, Hiroki; Kato, Kunihito; Yamamoto, Kazuhiko; Ogawa, Noriko; Ohba, Kimie

    2008-11-01

    The components of the food related to the "deliciousness" are usually evaluated by componential analysis. The component content and type of components in the food are determined by this analysis. However, componential analysis is not able to analyze measurements in detail, and the measurement is time consuming. We propose a method to measure the two-dimensional distribution of the component in food using a near infrared ray (IR) image. The advantage of our method is to be able to visualize the invisible components. Many components in food have characteristics such as absorption and reflection of light in the IR range. The component content is measured using subtraction between two wavelengths of near IR light. In this paper, we describe a method to measure the component of food using near IR image processing, and we show an application to visualize the saccharose in the pumpkin.

  11. Automatic analysis of microscopic images of red blood cell aggregates

    Science.gov (United States)

    Menichini, Pablo A.; Larese, Mónica G.; Riquelme, Bibiana D.

    2015-06-01

    Red blood cell aggregation is one of the most important factors in blood viscosity at stasis or at very low rates of flow. The basic structure of aggregates is a linear array of cell commonly termed as rouleaux. Enhanced or abnormal aggregation is seen in clinical conditions, such as diabetes and hypertension, producing alterations in the microcirculation, some of which can be analyzed through the characterization of aggregated cells. Frequently, image processing and analysis for the characterization of RBC aggregation were done manually or semi-automatically using interactive tools. We propose a system that processes images of RBC aggregation and automatically obtains the characterization and quantification of the different types of RBC aggregates. Present technique could be interesting to perform the adaptation as a routine used in hemorheological and Clinical Biochemistry Laboratories because this automatic method is rapid, efficient and economical, and at the same time independent of the user performing the analysis (repeatability of the analysis).

  12. Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

    Energy Technology Data Exchange (ETDEWEB)

    Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui [Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States); Duewer, Fred; Malkov, Serghei; Joe, Bonnie; Kerlikowske, Karla; Shepherd, John A. [Radiology Department, University of California, San Francisco, California 94143 (United States); Flowers, Chris I. [Department of Radiology, University of South Florida, Tampa, Florida 33612 (United States); Drukteinis, Jennifer S. [Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida 33612 (United States)

    2014-03-15

    Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CB alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.

  13. Image quality assessment based on multiscale geometric analysis.

    Science.gov (United States)

    Gao, Xinbo; Lu, Wen; Tao, Dacheng; Li, Xuelong

    2009-07-01

    Reduced-reference (RR) image quality assessment (IQA) has been recognized as an effective and efficient way to predict the visual quality of distorted images. The current standard is the wavelet-domain natural image statistics model (WNISM), which applies the Kullback-Leibler divergence between the marginal distributions of wavelet coefficients of the reference and distorted images to measure the image distortion. However, WNISM fails to consider the statistical correlations of wavelet coefficients in different subbands and the visual response characteristics of the mammalian cortical simple cells. In addition, wavelet transforms are optimal greedy approximations to extract singularity structures, so they fail to explicitly extract the image geometric information, e.g., lines and curves. Finally, wavelet coefficients are dense for smooth image edge contours. In this paper, to target the aforementioned problems in IQA, we develop a novel framework for IQA to mimic the human visual system (HVS) by incorporating the merits from multiscale geometric analysis (MGA), contrast sensitivity function (CSF), and the Weber's law of just noticeable difference (JND). In the proposed framework, MGA is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. Additionally, MGA offers a series of transforms including wavelet, curvelet, bandelet, contourlet, wavelet-based contourlet transform (WBCT), and hybrid wavelets and directional filter banks (HWD), and different transforms capture different types of image geometric information. CSF is applied to weight coefficients obtained by MGA to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the LIVE database against subjective mean opinion score (MOS) and demonstrate that 1) the proposed framework has

  14. Multispectral Image Analysis for Robust Prediction of Astaxanthin Coating

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Frosch, Stina; Nielsen, Michael Engelbrecht

    2013-01-01

    The aim of this study was to investigate the possibility of predicting the type and concentration level of astaxanthin coating of aquaculture feed pellets using multispectral image analysis. We used both natural and synthetic astaxanthin, and we used several different concentration levels...... of synthetic astaxanthin in combination with four different recipes of feed pellets. We used a VideometerLab with 20 spectral bands in the range of 385-1050 nm. We used linear discriminant analysis and sparse linear discriminant analysis for classification and variable selection. We used partial least squares...

  15. 3D Image Analysis of Geomaterials using Confocal Microscopy

    Science.gov (United States)

    Mulukutla, G.; Proussevitch, A.; Sahagian, D.

    2009-05-01

    Confocal microscopy is one of the most significant advances in optical microscopy of the last century. It is widely used in biological sciences but its application to geomaterials lingers due to a number of technical problems. Potentially the technique can perform non-invasive testing on a laser illuminated sample that fluoresces using a unique optical sectioning capability that rejects out-of-focus light reaching the confocal aperture. Fluorescence in geomaterials is commonly induced using epoxy doped with a fluorochrome that is impregnated into the sample to enable discrimination of various features such as void space or material boundaries. However, for many geomaterials, this method cannot be used because they do not naturally fluoresce and because epoxy cannot be impregnated into inaccessible parts of the sample due to lack of permeability. As a result, the confocal images of most geomaterials that have not been pre-processed with extensive sample preparation techniques are of poor quality and lack the necessary image and edge contrast necessary to apply any commonly used segmentation techniques to conduct any quantitative study of its features such as vesicularity, internal structure, etc. In our present work, we are developing a methodology to conduct a quantitative 3D analysis of images of geomaterials collected using a confocal microscope with minimal amount of prior sample preparation and no addition of fluorescence. Two sample geomaterials, a volcanic melt sample and a crystal chip containing fluid inclusions are used to assess the feasibility of the method. A step-by-step process of image analysis includes application of image filtration to enhance the edges or material interfaces and is based on two segmentation techniques: geodesic active contours and region competition. Both techniques have been applied extensively to the analysis of medical MRI images to segment anatomical structures. Preliminary analysis suggests that there is distortion in the

  16. Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

    Science.gov (United States)

    Prescott, Jeffrey William

    2013-02-01

    The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

  17. Physics-based deformable organisms for medical image analysis

    Science.gov (United States)

    Hamarneh, Ghassan; McIntosh, Chris

    2005-04-01

    Previously, "Deformable organisms" were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottom-up deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physical layer was absent and in order to complete medical image segmentation tasks, deformable organisms relied on pure geometry-based shape deformations guided by sensory data, prior structural knowledge, and expert-generated schedules of behaviors. In this paper we introduce the use of physics-based shape deformations within the deformable organisms framework yielding additional robustness by allowing intuitive real-time user guidance and interaction when necessary. We present the results of applying our physics-based deformable organisms, with an underlying dynamic spring-mass mesh model, to segmenting and labelling the corpus callosum in 2D midsagittal magnetic resonance images.

  18. Imaging hydrated microbial extracellular polymers: Comparative analysis by electron microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Dohnalkova, A.C.; Marshall, M. J.; Arey, B. W.; Williams, K. H.; Buck, E. C.; Fredrickson, J. K.

    2011-01-01

    Microbe-mineral and -metal interactions represent a major intersection between the biosphere and geosphere but require high-resolution imaging and analytical tools for investigating microscale associations. Electron microscopy has been used extensively for geomicrobial investigations and although used bona fide, the traditional methods of sample preparation do not preserve the native morphology of microbiological components, especially extracellular polymers. Herein, we present a direct comparative analysis of microbial interactions using conventional electron microscopy approaches of imaging at room temperature and a suite of cryogenic electron microscopy methods providing imaging in the close-to-natural hydrated state. In situ, we observed an irreversible transformation of the hydrated bacterial extracellular polymers during the traditional dehydration-based sample preparation that resulted in their collapse into filamentous structures. Dehydration-induced polymer collapse can lead to inaccurate spatial relationships and hence could subsequently affect conclusions regarding nature of interactions between microbial extracellular polymers and their environment.

  19. Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy.

    Science.gov (United States)

    Mudie, Lucy I; Wang, Xueyang; Friedman, David S; Brady, Christopher J

    2017-09-23

    As the number of people with diabetic retinopathy (DR) in the USA is expected to increase threefold by 2050, the need to reduce health care costs associated with screening for this treatable disease is ever present. Crowdsourcing and automated retinal image analysis (ARIA) are two areas where new technology has been applied to reduce costs in screening for DR. This paper reviews the current literature surrounding these new technologies. Crowdsourcing has high sensitivity for normal vs abnormal images; however, when multiple categories for severity of DR are added, specificity is reduced. ARIAs have higher sensitivity and specificity, and some commercial ARIA programs are already in use. Deep learning enhanced ARIAs appear to offer even more improvement in ARIA grading accuracy. The utilization of crowdsourcing and ARIAs may be a key to reducing the time and cost burden of processing images from DR screening.

  20. A survey on deep learning in medical image analysis.

    Science.gov (United States)

    Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A W M; van Ginneken, Bram; Sánchez, Clara I

    2017-12-01

    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis.

    Science.gov (United States)

    Isse, K; Lesniak, A; Grama, K; Roysam, B; Minervini, M I; Demetris, A J

    2012-01-01

    Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes. ©Copyright 2011 The American Society of Transplantation and the American Society of Transplant Surgeons.

  2. Mapping Fire Severity Using Imaging Spectroscopy and Kernel Based Image Analysis

    Science.gov (United States)

    Prasad, S.; Cui, M.; Zhang, Y.; Veraverbeke, S.

    2014-12-01

    Improved spatial representation of within-burn heterogeneity after wildfires is paramount to effective land management decisions and more accurate fire emissions estimates. In this work, we demonstrate feasibility and efficacy of airborne imaging spectroscopy (hyperspectral imagery) for quantifying wildfire burn severity, using kernel based image analysis techniques. Two different airborne hyperspectral datasets, acquired over the 2011 Canyon and 2013 Rim fire in California using the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor, were used in this study. The Rim Fire, covering parts of the Yosemite National Park started on August 17, 2013, and was the third largest fire in California's history. Canyon Fire occurred in the Tehachapi mountains, and started on September 4, 2011. In addition to post-fire data for both fires, half of the Rim fire was also covered with pre-fire images. Fire severity was measured in the field using Geo Composite Burn Index (GeoCBI). The field data was utilized to train and validate our models, wherein the trained models, in conjunction with imaging spectroscopy data were used for GeoCBI estimation wide geographical regions. This work presents an approach for using remotely sensed imagery combined with GeoCBI field data to map fire scars based on a non-linear (kernel based) epsilon-Support Vector Regression (e-SVR), which was used to learn the relationship between spectra and GeoCBI in a kernel-induced feature space. Classification of healthy vegetation versus fire-affected areas based on morphological multi-attribute profiles was also studied. The availability of pre- and post-fire imaging spectroscopy data over the Rim Fire provided a unique opportunity to evaluate the performance of bi-temporal imaging spectroscopy for assessing post-fire effects. This type of data is currently constrained because of limited airborne acquisitions before a fire, but will become widespread with future spaceborne sensors such as those on

  3. Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

    Science.gov (United States)

    de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

    2008-01-01

    Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications.

  4. Public-domain software for root image analysis

    Directory of Open Access Journals (Sweden)

    Mirian Cristina Gomes Costa

    2014-10-01

    Full Text Available In the search for high efficiency in root studies, computational systems have been developed to analyze digital images. ImageJ and Safira are public-domain systems that may be used for image analysis of washed roots. However, differences in root properties measured using ImageJ and Safira are supposed. This study compared values of root length and surface area obtained with public-domain systems with values obtained by a reference method. Root samples were collected in a banana plantation in an area of a shallower Typic Carbonatic Haplic Cambisol (CXk, and an area of a deeper Typic Haplic Ta Eutrophic Cambisol (CXve, at six depths in five replications. Root images were digitized and the systems ImageJ and Safira used to determine root length and surface area. The line-intersect method modified by Tennant was used as reference; values of root length and surface area measured with the different systems were analyzed by Pearson's correlation coefficient and compared by the confidence interval and t-test. Both systems ImageJ and Safira had positive correlation coefficients with the reference method for root length and surface area data in CXk and CXve. The correlation coefficient ranged from 0.54 to 0.80, with lowest value observed for ImageJ in the measurement of surface area of roots sampled in CXve. The IC (95 % revealed that root length measurements with Safira did not differ from that with the reference method in CXk (-77.3 to 244.0 mm. Regarding surface area measurements, Safira did not differ from the reference method for samples collected in CXk (-530.6 to 565.8 mm² as well as in CXve (-4231 to 612.1 mm². However, measurements with ImageJ were different from those obtained by the reference method, underestimating length and surface area in samples collected in CXk and CXve. Both ImageJ and Safira allow an identification of increases or decreases in root length and surface area. However, Safira results for root length and surface area are

  5. Automatic comic page image understanding based on edge segment analysis

    Science.gov (United States)

    Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

    2013-12-01

    Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

  6. Within-subject template estimation for unbiased longitudinal image analysis.

    Science.gov (United States)

    Reuter, Martin; Schmansky, Nicholas J; Rosas, H Diana; Fischl, Bruce

    2012-07-16

    Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir

    2015-08-19

    Extended images obtained from reverse-time migration (RTM) contain information about the accuracy of the velocity field and subsurface illumination at different incidence angles. Here, we evaluate the influence of errors in the anisotropy parameters on the shape of the residual moveout (RMO) in P-wave RTM extended images for VTI (transversely isotropic with a vertical symmetry axis) media. Considering the actual spatial distribution of the zero-dip NMO velocity (Vnmo), which could be approximately estimated by conventional techniques, we analyze the extended images obtained with distorted fields of the parameters η and δ. Differential semblance optimization (DSO) and stack-power estimates are employed to study the sensitivity of focusing to the anisotropy parameters. The results show that the signature of η is dip-dependent, whereas errors in δ cause defocusing only if that parameter is laterally varying. Hence, earlier results regarding the influence of η and δ on reflection moveout and migration velocity analysis remain generally valid in the extended image space for complex media. The dependence of RMO on errors in the anisotropy parameters provides essential insights for anisotropic wavefield tomography using extended images.

  8. Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

    Science.gov (United States)

    Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.

    2004-02-01

    We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

  9. Multivariate analysis of magnetic resonance imaging of focal hepatic lesions

    International Nuclear Information System (INIS)

    Fujishima, Mamoru; Suemitsu, Ichizou; Sei, Tetsurou; Takeda, Yoshihiro; Hiraki, Yoshio

    1993-01-01

    A total of 124 lesions from 1 to 6 cm in diameter, including 31 cavernous hemangiomas, 32 metastases and 61 hepatocellular carcinomas (HCC) were analyzed to study the usefulness of magnetic resonance imaging (MRI) at 0.5 Tesla to differentiate focal hepatic lesions on the basis of qualitative criteria. Each focal hepatic lesion was assessed for shape, internal architecture and signal intensity relative to normal liver parenchyma. While all cavernous hemangiomas and metastases except one lesion could be detected, detection rate of HCC was significantly inferior to that of the other two diseases. A tumor capsule and a hyperintense focus on T 1 -weighted images were demonstrated in only HCC lesions in strong contrast with the other two diseases; however, metastases with slow-growing characteristics or subacute hematoma may appear as similar images. Cavernous hemangiomas appeared markedly hyperintense on T 2 -weighted images in 23 of 31 lesions, but one metastasis and one HCC had similar images. A multivariate analysis of several MRI resulted in the following mean discriminant scores: cavernous hemangioma, -1.2652; metastasis, 0.1830; and HCC, 0.7138. It appeared to be possible to differentiate the three diseases with 84.4 percent accuracy. (author)

  10. Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

    Science.gov (United States)

    Robertson, Stephanie; Azizpour, Hossein; Smith, Kevin; Hartman, Johan

    2018-04-01

    Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide breast cancer treatment, but new challenges have emerged as our increasing understanding of cancer over the years has revealed its complex nature. As patient demand for personalized breast cancer therapy grows, we face an urgent need for more precise biomarker assessment and more accurate histopathologic breast cancer diagnosis to make better therapy decisions. The digitization of pathology data has opened the door to faster, more reproducible, and more precise diagnoses through computerized image analysis. Software to assist diagnostic breast pathology through image processing techniques have been around for years. But recent breakthroughs in artificial intelligence (AI) promise to fundamentally change the way we detect and treat breast cancer in the near future. Machine learning, a subfield of AI that applies statistical methods to learn from data, has seen an explosion of interest in recent years because of its ability to recognize patterns in data with less need for human instruction. One technique in particular, known as deep learning, has produced groundbreaking results in many important problems including image classification and speech recognition. In this review, we will cover the use of AI and deep learning in diagnostic breast pathology, and other recent developments in digital image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Analysis of Cultural Heritage by Accelerator Techniques and Analytical Imaging

    Science.gov (United States)

    Ide-Ektessabi, Ari; Toque, Jay Arre; Murayama, Yusuke

    2011-12-01

    In this paper we present the result of experimental investigation using two very important accelerator techniques: (1) synchrotron radiation XRF and XAFS; and (2) accelerator mass spectrometry and multispectral analytical imaging for the investigation of cultural heritage. We also want to introduce a complementary approach to the investigation of artworks which is noninvasive and nondestructive that can be applied in situ. Four major projects will be discussed to illustrate the potential applications of these accelerator and analytical imaging techniques: (1) investigation of Mongolian Textile (Genghis Khan and Kublai Khan Period) using XRF, AMS and electron microscopy; (2) XRF studies of pigments collected from Korean Buddhist paintings; (3) creating a database of elemental composition and spectral reflectance of more than 1000 Japanese pigments which have been used for traditional Japanese paintings; and (4) visible light-near infrared spectroscopy and multispectral imaging of degraded malachite and azurite. The XRF measurements of the Japanese and Korean pigments could be used to complement the results of pigment identification by analytical imaging through spectral reflectance reconstruction. On the other hand, analysis of the Mongolian textiles revealed that they were produced between 12th and 13th century. Elemental analysis of the samples showed that they contained traces of gold, copper, iron and titanium. Based on the age and trace elements in the samples, it was concluded that the textiles were produced during the height of power of the Mongol empire, which makes them a valuable cultural heritage. Finally, the analysis of the degraded and discolored malachite and azurite demonstrates how multispectral analytical imaging could be used to complement the results of high energy-based techniques.

  12. 3-D Image Analysis of Fluorescent Drug Binding

    Directory of Open Access Journals (Sweden)

    M. Raquel Miquel

    2005-01-01

    Full Text Available Fluorescent ligands provide the means of studying receptors in whole tissues using confocal laser scanning microscopy and have advantages over antibody- or non-fluorescence-based method. Confocal microscopy provides large volumes of images to be measured. Histogram analysis of 3-D image volumes is proposed as a method of graphically displaying large amounts of volumetric image data to be quickly analyzed and compared. The fluorescent ligand BODIPY FL-prazosin (QAPB was used in mouse aorta. Histogram analysis reports the amount of ligand-receptor binding under different conditions and the technique is sensitive enough to detect changes in receptor availability after antagonist incubation or genetic manipulations. QAPB binding was concentration dependent, causing concentration-related rightward shifts in the histogram. In the presence of 10 μM phenoxybenzamine (blocking agent, the QAPB (50 nM histogram overlaps the autofluorescence curve. The histogram obtained for the 1D knockout aorta lay to the left of that of control and 1B knockout aorta, indicating a reduction in 1D receptors. We have shown, for the first time, that it is possible to graphically display binding of a fluorescent drug to a biological tissue. Although our application is specific to adrenergic receptors, the general method could be applied to any volumetric, fluorescence-image-based assay.

  13. A hybrid correlation analysis with application to imaging genetics

    Science.gov (United States)

    Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

    2018-03-01

    Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

  14. Applied Fourier analysis from signal processing to medical imaging

    CERN Document Server

    Olson, Tim

    2017-01-01

    The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

  15. SPEKTROP DPU: optoelectronic platform for fast multispectral imaging

    Science.gov (United States)

    Graczyk, Rafal; Sitek, Piotr; Stolarski, Marcin

    2010-09-01

    In recent years it easy to spot and increasing need of high-quality Earth imaging in airborne and space applications. This is due fact that government and local authorities urge for up to date topological data for administrative purposes. On the other hand, interest in environmental sciences, push for ecological approach, efficient agriculture and forests management are also heavily supported by Earth images in various resolutions and spectral ranges. "SPEKTROP DPU: Opto-electronic platform for fast multi-spectral imaging" paper describes architectural datails of data processing unit, part of universal and modular platform that provides high quality imaging functionality in aerospace applications.

  16. Imbibition of wheat seeds: Application of image analysis

    Science.gov (United States)

    Lev, Jakub; Blahovec, Jiří

    2017-10-01

    Image analysis is widely used for monitoring seeds during germination, and it is often the final phase of germination that is subjected to the greatest attention. However, the initial phase of germination (the so-called imbibition) also exhibits interesting behaviour. This work shows that image analysis has significant potential in the imbibition. Herein, a total of 120 seeds were analysed during germination tests, and information about seed size and shape was stored and analysed. It was found that the imbibition can be divided into two newly defined parts. The first one (`abrupt imbibition') consists mainly of the swelling of the seed embryo part and lasts approximately one hour. The second one, referred to as `main imbibition', consists mainly of spatial expansion caused by imbibition in the other parts of the seed. The results presented are supported by the development of seed cross area and shape parameters, and by direct observation.

  17. Image-Analysis Based on Seed Phenomics in Sesame

    Directory of Open Access Journals (Sweden)

    Prasad R.

    2014-10-01

    Full Text Available The seed coat (testa structure of twenty-three cultivated (Sesamum indicum L. and six wild sesame (s. occidentale Regel & Heer., S. mulayanum Nair, S. prostratum Retz., S. radiatum Schumach. & Thonn., S. angustifolium (Oliv. Engl. and S. schinzianum Asch germplasm was analyzed from digital and Scanning Electron Microscopy (SEM images with dedicated software using the descriptors for computer based seed image analysis to understand the diversity of seed morphometric traits, which later on can be extended to screen and evaluate improved genotypes of sesame. Seeds of wild sesame species could conveniently be distinguished from cultivated varieties based on shape and architectural analysis. Results indicated discrete ‘cut off values to identify definite shape and contour of seed for a desirable sesame genotype along with the con-ventional practice of selecting lighter colored testa.

  18. Multifractural analysis of AFM images of Nb thin film surfaces

    International Nuclear Information System (INIS)

    Altajskij, M.V; Chernenko, L.P.; Balebanov, V.M.; Erokhin, N.S.; Moiseev, S.S.

    2000-01-01

    The multifractal analysis of the atomic Force Microscope (AFM) images of the Niobium (Nb) thin film surfaces has been performed. These Nb films are being used for the measurements of the London penetration depth of stationary magnetic field by polarized neutron reflectometry. The analysis shows the behavior of Renyi dimensions of images (in the range of available scales 6-2000 nm), like the known multifractal p-model, with typical Hausdorff dimension of prevalent color in the range of 1.6-1.9. This indicates the fractal nature of film landscape on those scales. The perspective of new mechanism of order parameter suppression on superconductor-vacuum boundary, manifested in anomalous magnetic field penetration in discussed

  19. Local crystallography analysis for atomically resolved scanning tunneling microscopy images

    International Nuclear Information System (INIS)

    Lin, Wenzhi; Li, Qing; Belianinov, Alexei; Gai, Zheng; Baddorf, Arthur P; Pan, Minghu; Jesse, Stephen; Kalinin, Sergei V; Sales, Brian C; Sefat, Athena

    2013-01-01

    Scanning probe microscopy has emerged as a powerful and flexible tool for atomically resolved imaging of surface structures. However, due to the amount of information extracted, in many cases the interpretation of such data is limited to being qualitative and semi-quantitative in nature. At the same time, much can be learned from local atom parameters, such as distances and angles, that can be analyzed and interpreted as variations of local chemical bonding, or order parameter fields. Here, we demonstrate an iterative algorithm for indexing and determining atomic positions that allows the analysis of inhomogeneous surfaces. This approach is further illustrated by local crystallographic analysis of several real surfaces, including highly ordered pyrolytic graphite and an Fe-based superconductor FeTe 0.55 Se 0.45 . This study provides a new pathway to extract and quantify local properties for scanning probe microscopy images. (paper)

  20. Off-line image analysis for froth flotation of coal

    Energy Technology Data Exchange (ETDEWEB)

    Citir, C.; Aktas, Z.; Berber, R. [Ankara University, Ankara (Turkey). Faculty of Engineering

    2004-05-15

    Froth flotation is an effective process for separating sulphur and fine minerals from coal. Such pre-cleaning of coal is necessary in order to reduce the environmental and operational problems in power plants. The separation depends very much on particle surface properties, and the selectivity can be improved by addition of a reagent. Image analysis can be used to determine the amount of reagent, by using the relation between surface properties and froth bubble sizes. This work reports some improvements in the efficiency of the image analysis, and in determination of bubble diameter distribution towards developing froth-based flotation models. Ultimate benefit of the technique would allow a pre-determined reagent addition profile to be identified for controlling the separation process.