WorldWideScience

Sample records for image analysis method

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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)

  6. 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...

  7. 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%.

  8. Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method.

    Science.gov (United States)

    Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

    2014-02-01

    To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

  9. Does thorax EIT image analysis depend on the image reconstruction method?

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2013-04-01

    Different methods were proposed to analyze the resulting images of electrical impedance tomography (EIT) measurements during ventilation. The aim of our study was to examine if the analysis methods based on back-projection deliver the same results when applied on images based on other reconstruction algorithms. Seven mechanically ventilated patients with ARDS were examined by EIT. The thorax contours were determined from the routine CT images. EIT raw data was reconstructed offline with (1) filtered back-projection with circular forward model (BPC); (2) GREIT reconstruction method with circular forward model (GREITC) and (3) GREIT with individual thorax geometry (GREITT). Three parameters were calculated on the resulting images: linearity, global ventilation distribution and regional ventilation distribution. The results of linearity test are 5.03±2.45, 4.66±2.25 and 5.32±2.30 for BPC, GREITC and GREITT, respectively (median ±interquartile range). The differences among the three methods are not significant (p = 0.93, Kruskal-Wallis test). The proportions of ventilation in the right lung are 0.58±0.17, 0.59±0.20 and 0.59±0.25 for BPC, GREITC and GREITT, respectively (p = 0.98). The differences of the GI index based on different reconstruction methods (0.53±0.16, 0.51±0.25 and 0.54±0.16 for BPC, GREITC and GREITT, respectively) are also not significant (p = 0.93). We conclude that the parameters developed for images generated with GREITT are comparable with filtered back-projection and GREITC.

  10. 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

  11. Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method

    OpenAIRE

    Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

    2014-01-01

    Objective: To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. Methods: TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Results: Both assays provided good linearity, accuracy, reproducibility and selectivity for dete...

  12. A Proposal on the Quantitative Homogeneity Analysis Method of SEM Images for Material Inspections

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Song Hyun; Kim, Jong Woo; Shin, Chang Ho [Hanyang University, Seoul (Korea, Republic of); Choi, Jung-Hoon; Cho, In-Hak; Park, Hwan Seo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-05-15

    A scanning electron microscope (SEM) is a method to inspect the surface microstructure of materials. The SEM uses electron beams for imaging high magnifications of material surfaces; therefore, various chemical analyses can be performed from the SEM images. Therefore, it is widely used for the material inspection, chemical characteristic analysis, and biological analysis. For the nuclear criticality analysis field, it is an important parameter to check the homogeneity of the compound material for using it in the nuclear system. In our previous study, the SEM was tried to use for the homogeneity analysis of the materials. In this study, a quantitative homogeneity analysis method of SEM images is proposed for the material inspections. The method is based on the stochastic analysis method with the information of the grayscales of the SEM images.

  13. A Proposal on the Quantitative Homogeneity Analysis Method of SEM Images for Material Inspections

    International Nuclear Information System (INIS)

    Kim, Song Hyun; Kim, Jong Woo; Shin, Chang Ho; Choi, Jung-Hoon; Cho, In-Hak; Park, Hwan Seo

    2015-01-01

    A scanning electron microscope (SEM) is a method to inspect the surface microstructure of materials. The SEM uses electron beams for imaging high magnifications of material surfaces; therefore, various chemical analyses can be performed from the SEM images. Therefore, it is widely used for the material inspection, chemical characteristic analysis, and biological analysis. For the nuclear criticality analysis field, it is an important parameter to check the homogeneity of the compound material for using it in the nuclear system. In our previous study, the SEM was tried to use for the homogeneity analysis of the materials. In this study, a quantitative homogeneity analysis method of SEM images is proposed for the material inspections. The method is based on the stochastic analysis method with the information of the grayscales of the SEM images

  14. Fringe image analysis based on the amplitude modulation method.

    Science.gov (United States)

    Gai, Shaoyan; Da, Feipeng

    2010-05-10

    A novel phase-analysis method is proposed. To get the fringe order of a fringe image, the amplitude-modulation fringe pattern is carried out, which is combined with the phase-shift method. The primary phase value is obtained by a phase-shift algorithm, and the fringe-order information is encoded in the amplitude-modulation fringe pattern. Different from other methods, the amplitude-modulation fringe identifies the fringe order by the amplitude of the fringe pattern. In an amplitude-modulation fringe pattern, each fringe has its own amplitude; thus, the order information is integrated in one fringe pattern, and the absolute fringe phase can be calculated correctly and quickly with the amplitude-modulation fringe image. The detailed algorithm is given, and the error analysis of this method is also discussed. Experimental results are presented by a full-field shape measurement system where the data has been processed using the proposed algorithm. (c) 2010 Optical Society of America.

  15. Application of computer intensive data analysis methods to the analysis of digital images and spatial data

    DEFF Research Database (Denmark)

    Windfeld, Kristian

    1992-01-01

    Computer-intensive methods for data analysis in a traditional setting has developed rapidly in the last decade. The application of and adaption of some of these methods to the analysis of multivariate digital images and spatial data are explored, evaluated and compared to well established classical...... into the projection pursuit is presented. Examples from remote sensing are given. The ACE algorithm for computing non-linear transformations for maximizing correlation is extended and applied to obtain a non-linear transformation that maximizes autocorrelation or 'signal' in a multivariate image....... This is a generalization of the minimum /maximum autocorrelation factors (MAF's) which is a linear method. The non-linear method is compared to the linear method when analyzing a multivariate TM image from Greenland. The ACE method is shown to give a more detailed decomposition of the image than the MAF-transformation...

  16. 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.

  17. 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

  18. Determining wood chip size: image analysis and clustering methods

    Directory of Open Access Journals (Sweden)

    Paolo Febbi

    2013-09-01

    Full Text Available One of the standard methods for the determination of the size distribution of wood chips is the oscillating screen method (EN 15149- 1:2010. Recent literature demonstrated how image analysis could return highly accurate measure of the dimensions defined for each individual particle, and could promote a new method depending on the geometrical shape to determine the chip size in a more accurate way. A sample of wood chips (8 litres was sieved through horizontally oscillating sieves, using five different screen hole diameters (3.15, 8, 16, 45, 63 mm; the wood chips were sorted in decreasing size classes and the mass of all fractions was used to determine the size distribution of the particles. Since the chip shape and size influence the sieving results, Wang’s theory, which concerns the geometric forms, was considered. A cluster analysis on the shape descriptors (Fourier descriptors and size descriptors (area, perimeter, Feret diameters, eccentricity was applied to observe the chips distribution. The UPGMA algorithm was applied on Euclidean distance. The obtained dendrogram shows a group separation according with the original three sieving fractions. A comparison has been made between the traditional sieve and clustering results. This preliminary result shows how the image analysis-based method has a high potential for the characterization of wood chip size distribution and could be further investigated. Moreover, this method could be implemented in an online detection machine for chips size characterization. An improvement of the results is expected by using supervised multivariate methods that utilize known class memberships. The main objective of the future activities will be to shift the analysis from a 2-dimensional method to a 3- dimensional acquisition process.

  19. Development of automatic image analysis methods for high-throughput and high-content screening

    NARCIS (Netherlands)

    Di, Zi

    2013-01-01

    This thesis focuses on the development of image analysis methods for ultra-high content analysis of high-throughput screens where cellular phenotype responses to various genetic or chemical perturbations that are under investigation. Our primary goal is to deliver efficient and robust image analysis

  20. System and method for image reconstruction, analysis, and/or de-noising

    KAUST Repository

    Laleg-Kirati, Taous-Meriem

    2015-11-12

    A method and system can analyze, reconstruct, and/or denoise an image. The method and system can include interpreting a signal as a potential of a Schrödinger operator, decomposing the signal into squared eigenfunctions, reducing a design parameter of the Schrödinger operator, analyzing discrete spectra of the Schrödinger operator and combining the analysis of the discrete spectra to construct the image.

  1. 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.

  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. Comparative analysis of different methods for image enhancement

    Institute of Scientific and Technical Information of China (English)

    吴笑峰; 胡仕刚; 赵瑾; 李志明; 李劲; 唐志军; 席在芳

    2014-01-01

    Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima (WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean (μ), standard deviation (s), mean square error (MSE) and PSNR (peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement.

  4. Transferability of Object-Oriented Image Analysis Methods for Slum Identification

    Directory of Open Access Journals (Sweden)

    Alfred Stein

    2013-08-01

    Full Text Available Updated spatial information on the dynamics of slums can be helpful to measure and evaluate progress of policies. Earlier studies have shown that semi-automatic detection of slums using remote sensing can be challenging considering the large variability in definition and appearance. In this study, we explored the potential of an object-oriented image analysis (OOA method to detect slums, using very high resolution (VHR imagery. This method integrated expert knowledge in the form of a local slum ontology. A set of image-based parameters was identified that was used for differentiating slums from non-slum areas in an OOA environment. The method was implemented on three subsets of the city of Ahmedabad, India. Results show that textural features such as entropy and contrast derived from a grey level co-occurrence matrix (GLCM and the size of image segments are stable parameters for classification of built-up areas and the identification of slums. Relation with classified slum objects, in terms of enclosed by slums and relative border with slums was used to refine classification. The analysis on three different subsets showed final accuracies ranging from 47% to 68%. We conclude that our method produces useful results as it allows including location specific adaptation, whereas generically applicable rulesets for slums are still to be developed.

  5. Software phantom with realistic speckle modeling for validation of image analysis methods in echocardiography

    Science.gov (United States)

    Law, Yuen C.; Tenbrinck, Daniel; Jiang, Xiaoyi; Kuhlen, Torsten

    2014-03-01

    Computer-assisted processing and interpretation of medical ultrasound images is one of the most challenging tasks within image analysis. Physical phenomena in ultrasonographic images, e.g., the characteristic speckle noise and shadowing effects, make the majority of standard methods from image analysis non optimal. Furthermore, validation of adapted computer vision methods proves to be difficult due to missing ground truth information. There is no widely accepted software phantom in the community and existing software phantoms are not exible enough to support the use of specific speckle models for different tissue types, e.g., muscle and fat tissue. In this work we propose an anatomical software phantom with a realistic speckle pattern simulation to _ll this gap and provide a exible tool for validation purposes in medical ultrasound image analysis. We discuss the generation of speckle patterns and perform statistical analysis of the simulated textures to obtain quantitative measures of the realism and accuracy regarding the resulting textures.

  6. Technical characterization by image analysis: an automatic method of mineralogical studies

    International Nuclear Information System (INIS)

    Oliveira, J.F. de

    1988-01-01

    The application of a modern method of image analysis fully automated for the study of grain size distribution modal assays, degree of liberation and mineralogical associations is discussed. The image analyser is interfaced with a scanning electron microscope and an energy dispersive X-rays analyser. The image generated by backscattered electrons is analysed automatically and the system has been used in accessment studies of applied mineralogy as well as in process control in the mining industry. (author) [pt

  7. Improved Dynamic Analysis method for quantitative PIXE and SXRF element imaging of complex materials

    International Nuclear Information System (INIS)

    Ryan, C.G.; Laird, J.S.; Fisher, L.A.; Kirkham, R.; Moorhead, G.F.

    2015-01-01

    The Dynamic Analysis (DA) method in the GeoPIXE software provides a rapid tool to project quantitative element images from PIXE and SXRF imaging event data both for off-line analysis and in real-time embedded in a data acquisition system. Initially, it assumes uniform sample composition, background shape and constant model X-ray relative intensities. A number of image correction methods can be applied in GeoPIXE to correct images to account for chemical concentration gradients, differential absorption effects, and to correct images for pileup effects. A new method, applied in a second pass, uses an end-member phase decomposition obtained from the first pass, and DA matrices determined for each end-member, to re-process the event data with each pixel treated as an admixture of end-member terms. This paper describes the new method and demonstrates through examples and Monte-Carlo simulations how it better tracks spatially complex composition and background shape while still benefitting from the speed of DA.

  8. Improved Dynamic Analysis method for quantitative PIXE and SXRF element imaging of complex materials

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, C.G., E-mail: chris.ryan@csiro.au; Laird, J.S.; Fisher, L.A.; Kirkham, R.; Moorhead, G.F.

    2015-11-15

    The Dynamic Analysis (DA) method in the GeoPIXE software provides a rapid tool to project quantitative element images from PIXE and SXRF imaging event data both for off-line analysis and in real-time embedded in a data acquisition system. Initially, it assumes uniform sample composition, background shape and constant model X-ray relative intensities. A number of image correction methods can be applied in GeoPIXE to correct images to account for chemical concentration gradients, differential absorption effects, and to correct images for pileup effects. A new method, applied in a second pass, uses an end-member phase decomposition obtained from the first pass, and DA matrices determined for each end-member, to re-process the event data with each pixel treated as an admixture of end-member terms. This paper describes the new method and demonstrates through examples and Monte-Carlo simulations how it better tracks spatially complex composition and background shape while still benefitting from the speed of DA.

  9. A quality quantitative method of silicon direct bonding based on wavelet image analysis

    Science.gov (United States)

    Tan, Xiao; Tao, Zhi; Li, Haiwang; Xu, Tiantong; Yu, Mingxing

    2018-04-01

    The rapid development of MEMS (micro-electro-mechanical systems) has received significant attention from researchers in various fields and subjects. In particular, the MEMS fabrication process is elaborate and, as such, has been the focus of extensive research inquiries. However, in MEMS fabrication, component bonding is difficult to achieve and requires a complex approach. Thus, improvements in bonding quality are relatively important objectives. A higher quality bond can only be achieved with improved measurement and testing capabilities. In particular, the traditional testing methods mainly include infrared testing, tensile testing, and strength testing, despite the fact that using these methods to measure bond quality often results in low efficiency or destructive analysis. Therefore, this paper focuses on the development of a precise, nondestructive visual testing method based on wavelet image analysis that is shown to be highly effective in practice. The process of wavelet image analysis includes wavelet image denoising, wavelet image enhancement, and contrast enhancement, and as an end result, can display an image with low background noise. In addition, because the wavelet analysis software was developed with MATLAB, it can reveal the bonding boundaries and bonding rates to precisely indicate the bond quality at all locations on the wafer. This work also presents a set of orthogonal experiments that consist of three prebonding factors, the prebonding temperature, the positive pressure value and the prebonding time, which are used to analyze the prebonding quality. This method was used to quantify the quality of silicon-to-silicon wafer bonding, yielding standard treatment quantities that could be practical for large-scale use.

  10. Quantitative analysis of γ–oryzanol content in cold pressed rice bran oil by TLC–image analysis method

    Directory of Open Access Journals (Sweden)

    Apirak Sakunpak

    2014-02-01

    Conclusions: The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

  11. Terahertz composite imaging method

    Institute of Scientific and Technical Information of China (English)

    QIAO Xiaoli; REN Jiaojiao; ZHANG Dandan; CAO Guohua; LI Lijuan; ZHANG Xinming

    2017-01-01

    In order to improve the imaging quality of terahertz(THz) spectroscopy, Terahertz Composite Imaging Method(TCIM) is proposed. The traditional methods of improving THz spectroscopy image quality are mainly from the aspects of de-noising and image enhancement. TCIM breaks through this limitation. A set of images, reconstructed in a single data collection, can be utilized to construct two kinds of composite images. One algorithm, called Function Superposition Imaging Algorithm(FSIA), is to construct a new gray image utilizing multiple gray images through a certain function. The features of the Region Of Interest (ROI) are more obvious after operating, and it has capability of merging ROIs in multiple images. The other, called Multi-characteristics Pseudo-color Imaging Algorithm(McPcIA), is to construct a pseudo-color image by combining multiple reconstructed gray images in a single data collection. The features of ROI are enhanced by color differences. Two algorithms can not only improve the contrast of ROIs, but also increase the amount of information resulting in analysis convenience. The experimental results show that TCIM is a simple and effective tool for THz spectroscopy image analysis.

  12. Method of assessing heterogeneity in images

    Science.gov (United States)

    Jacob, Richard E.; Carson, James P.

    2016-08-23

    A method of assessing heterogeneity in images is disclosed. 3D images of an object are acquired. The acquired images may be filtered and masked. Iterative decomposition is performed on the masked images to obtain image subdivisions that are relatively homogeneous. Comparative analysis, such as variogram analysis or correlogram analysis, is performed of the decomposed images to determine spatial relationships between regions of the images that are relatively homogeneous.

  13. Artificial Intelligence Methods in Analysis of Morphology of Selected Structures in Medical Images

    Directory of Open Access Journals (Sweden)

    Ryszard Tadeusiewicz

    2001-01-01

    Full Text Available The goal of this paper is the presentation of the possibilities of application of syntactic method of computer image analysis for recognition of local stenoscs of coronary arteries lumen and detection of pathological signs in upper parts of ureter ducts and renal calyxes. Analysis of correct morphology of these structures is possible thanks to thc application of sequence and tree methods from the group of syntactic methods of pattern recognition. In the case of analysis of coronary arteries images the main objective is computer-aided early diagnosis of different form of ischemic cardiovascular diseases. Such diseases may reveal in the form of stable or unstable disturbances of heart rhythm or infarction. ln analysis of kidney radiograms the main goal is recognition of local irregularities in ureter lumens and examination of morphology of renal pelvis and calyxes.

  14. Mathematical imaging methods for mitosis analysis in live-cell phase contrast microscopy.

    Science.gov (United States)

    Grah, Joana Sarah; Harrington, Jennifer Alison; Koh, Siang Boon; Pike, Jeremy Andrew; Schreiner, Alexander; Burger, Martin; Schönlieb, Carola-Bibiane; Reichelt, Stefanie

    2017-02-15

    In this paper we propose a workflow to detect and track mitotic cells in time-lapse microscopy image sequences. In order to avoid the requirement for cell lines expressing fluorescent markers and the associated phototoxicity, phase contrast microscopy is often preferred over fluorescence microscopy in live-cell imaging. However, common specific image characteristics complicate image processing and impede use of standard methods. Nevertheless, automated analysis is desirable due to manual analysis being subjective, biased and extremely time-consuming for large data sets. Here, we present the following workflow based on mathematical imaging methods. In the first step, mitosis detection is performed by means of the circular Hough transform. The obtained circular contour subsequently serves as an initialisation for the tracking algorithm based on variational methods. It is sub-divided into two parts: in order to determine the beginning of the whole mitosis cycle, a backwards tracking procedure is performed. After that, the cell is tracked forwards in time until the end of mitosis. As a result, the average of mitosis duration and ratios of different cell fates (cell death, no division, division into two or more daughter cells) can be measured and statistics on cell morphologies can be obtained. All of the tools are featured in the user-friendly MATLAB®Graphical User Interface MitosisAnalyser. Copyright © 2017. Published by Elsevier Inc.

  15. 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.

  16. Registration and three-dimensional reconstruction of autoradiographic images by the disparity analysis method

    International Nuclear Information System (INIS)

    Zhao, Weizhao; Ginsberg, M.; Young, T.Y.

    1993-01-01

    Quantitative autoradiography is a powerful radio-isotopic-imaging method for neuroscientists to study local cerebral blood flow and glucose-metabolic rate at rest, in response to physiologic activation of the visual, auditory, somatosensory, and motor systems, and in pathologic conditions. Most autoradiographic studies analyze glucose utilization and blood flow in two-dimensional (2-D) coronal sections. With modern digital computer and image-processing techniques, a large number of closely spaced coronal sections can be stacked appropriately to form a three-dimensional (3-d) image. 3-D autoradiography allows investigators to observe cerebral sections and surfaces from any viewing angle. A fundamental problem in 3-D reconstruction is the alignment (registration) of the coronal sections. A new alignment method based on disparity analysis is presented which can overcome many of the difficulties encountered by previous methods. The disparity analysis method can deal with asymmetric, damaged, or tilted coronal sections under the same general framework, and it can be used to match coronal sections of different sizes and shapes. Experimental results on alignment and 3-D reconstruction are presented

  17. A Novel Imaging Analysis Method for Capturing Pharyngeal Constriction During Swallowing.

    Science.gov (United States)

    Schwertner, Ryan W; Garand, Kendrea L; Pearson, William G

    2016-01-01

    Videofluoroscopic imaging of swallowing known as the Modified Barium Study (MBS) is the standard of care for assessing swallowing difficulty. While the clinical purpose of this radiographic imaging is to primarily assess aspiration risk, valuable biomechanical data is embedded in these studies. Computational analysis of swallowing mechanics (CASM) is an established research methodology for assessing multiple interactions of swallowing mechanics based on coordinates mapping muscle function including hyolaryngeal movement, pharyngeal shortening, tongue base retraction, and extension of the head and neck, however coordinates characterizing pharyngeal constriction is undeveloped. The aim of this study was to establish a method for locating the superior and middle pharyngeal constrictors using hard landmarks as guides on MBS videofluoroscopic imaging, and to test the reliability of this new method. Twenty de-identified, normal, MBS videos were randomly selected from a database. Two raters annotated landmarks for the superior and middle pharyngeal constrictors frame-by-frame using a semi-automated MATLAB tracker tool at two time points. Intraclass correlation coefficients were used to assess test-retest reliability between two raters with an ICC = 0.99 or greater for all coordinates for the retest measurement. MorphoJ integrated software was used to perform a discriminate function analysis to visualize how all 12 coordinates interact with each other in normal swallowing. The addition of the superior and middle pharyngeal constrictor coordinates to CASM allows for a robust analysis of the multiple components of swallowing mechanics interacting with a wide range of variables in both patient specific and cohort studies derived from common use imaging data.

  18. Mobile Image Ratiometry: A New Method for Instantaneous Analysis of Rapid Test Strips

    OpenAIRE

    Donald C. Cooper; Bryan Callahan; Phil Callahan; Lee Burnett

    2012-01-01

    Here we describe Mobile Image Ratiometry (MIR), a new method for the automated quantification of standardized rapid immunoassay strips using consumer-based mobile smartphone and tablet cameras. To demonstrate MIR we developed a standardized method using rapid immunotest strips directed against cocaine (COC) and its major metabolite, benzoylecgonine (BE). We performed image analysis of three brands of commercially available dye-conjugated anti-COC/BE antibody test strips in response to three d...

  19. Development and application of an automated analysis method for individual cerebral perfusion single photon emission tomography images

    International Nuclear Information System (INIS)

    Cluckie, Alice Jane

    2001-01-01

    Neurological images may be analysed by performing voxel by voxel comparisons with a group of control subject images. An automated, 3D, voxel-based method has been developed for the analysis of individual single photon emission tomography (SPET) scans. Clusters of voxels are identified that represent regions of abnormal radiopharmaceutical uptake. Morphological operators are applied to reduce noise in the clusters, then quantitative estimates of the size and degree of the radiopharmaceutical uptake abnormalities are derived. Statistical inference has been performed using a Monte Carlo method that has not previously been applied to SPET scans, or for the analysis of individual images. This has been validated for group comparisons of SPET scans and for the analysis of an individual image using comparison with a group. Accurate statistical inference was obtained independent of experimental factors such as degrees of freedom, image smoothing and voxel significance level threshold. The analysis method has been evaluated for application to cerebral perfusion SPET imaging in ischaemic stroke. It has been shown that useful quantitative estimates, high sensitivity and high specificity may be obtained. Sensitivity and the accuracy of signal quantification were found to be dependent on the operator defined analysis parameters. Recommendations for the values of these parameters have been made. The analysis method developed has been compared with an established method and shown to result in higher specificity for the data and analysis parameter sets tested. In addition, application to a group of ischaemic stroke patient SPET scans has demonstrated its clinical utility. The influence of imaging conditions has been assessed using phantom data acquired with different gamma camera SPET acquisition parameters. A lower limit of five million counts and standardisation of all acquisition parameters has been recommended for the analysis of individual SPET scans. (author)

  20. PREFACE: Anti-counterfeit Image Analysis Methods (A Special Session of ICSXII)

    Science.gov (United States)

    Javidi, B.; Fournel, T.

    2007-06-01

    The International Congress for Stereology is dedicated to theoretical and applied aspects of stochastic tools, image analysis and mathematical morphology. A special emphasis on `anti-counterfeit image analysis methods' has been given this year for the XIIth edition (ICSXII). Facing the economic and social threat of counterfeiting, this devoted session presents recent advances and original solutions in the field. A first group of methods are related to marks located either on the product (physical marks) or on the data (hidden information) to be protected. These methods concern laser fs 3D encoding and source separation for machine-readable identification, moiré and `guilloche' engraving for visual verification and watermarking. Machine-readable travel documents are well-suited examples introducing the second group of methods which are related to cryptography. Used in passports for data authentication and identification (of people), cryptography provides some powerful tools. Opto-digital processing allows some efficient implementations described in the papers and promising applications. We would like to thank the reviewers who have contributed to a session of high quality, and the authors for their fine and hard work. We would like to address some special thanks to the invited lecturers, namely Professor Roger Hersch and Dr Isaac Amidror for their survey of moiré methods, Prof. Serge Vaudenay for his survey of existing protocols concerning machine-readable travel documents, and Dr Elisabet Pérez-Cabré for her presentation on optical encryption for multifactor authentication. We also thank Professor Dominique Jeulin, President of the International Society for Stereology, Professor Michel Jourlin, President of the organizing committee of ICSXII, for their help and advice, and Mr Graham Douglas, the Publisher of Journal of Physics: Conference Series at IOP Publishing, for his efficiency. We hope that this collection of papers will be useful as a tool to further

  1. 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...

  2. 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.

  3. Statistical Analysis of Compression Methods for Storing Binary Image for Low-Memory Systems

    Directory of Open Access Journals (Sweden)

    Roman Slaby

    2013-01-01

    Full Text Available The paper is focused on the statistical comparison of the selected compression methods which are used for compression of the binary images. The aim is to asses, which of presented compression method for low-memory system requires less number of bytes of memory. For assessment of the success rates of the input image to binary image the correlation functions are used. Correlation function is one of the methods of OCR algorithm used for the digitization of printed symbols. Using of compression methods is necessary for systems based on low-power micro-controllers. The data stream saving is very important for such systems with limited memory as well as the time required for decoding the compressed data. The success rate of the selected compression algorithms is evaluated using the basic characteristics of the exploratory analysis. The searched samples represent the amount of bytes needed to compress the test images, representing alphanumeric characters.

  4. COMPARISON OF IMAGE ENHANCEMENT METHODS FOR CHROMOSOME KARYOTYPE IMAGE ENHANCEMENT

    Directory of Open Access Journals (Sweden)

    Dewa Made Sri Arsa

    2017-02-01

    Full Text Available The chromosome is a set of DNA structure that carry information about our life. The information can be obtained through Karyotyping. The process requires a clear image so the chromosome can be evaluate well. Preprocessing have to be done on chromosome images that is image enhancement. The process starts with image background removing. The image will be cleaned background color. The next step is image enhancement. This paper compares several methods for image enhancement. We evaluate some method in image enhancement like Histogram Equalization (HE, Contrast-limiting Adaptive Histogram Equalization (CLAHE, Histogram Equalization with 3D Block Matching (HE+BM3D, and basic image enhancement, unsharp masking. We examine and discuss the best method for enhancing chromosome image. Therefore, to evaluate the methods, the original image was manipulated by the addition of some noise and blur. Peak Signal-to-noise Ratio (PSNR and Structural Similarity Index (SSIM are used to examine method performance. The output of enhancement method will be compared with result of Professional software for karyotyping analysis named Ikaros MetasystemT M . Based on experimental results, HE+BM3D method gets a stable result on both scenario noised and blur image.

  5. 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

  6. Bundle Adjustment-Based Stability Analysis Method with a Case Study of a Dual Fluoroscopy Imaging System

    Science.gov (United States)

    Al-Durgham, K.; Lichti, D. D.; Detchev, I.; Kuntze, G.; Ronsky, J. L.

    2018-05-01

    A fundamental task in photogrammetry is the temporal stability analysis of a camera/imaging-system's calibration parameters. This is essential to validate the repeatability of the parameters' estimation, to detect any behavioural changes in the camera/imaging system and to ensure precise photogrammetric products. Many stability analysis methods exist in the photogrammetric literature; each one has different methodological bases, and advantages and disadvantages. This paper presents a simple and rigorous stability analysis method that can be straightforwardly implemented for a single camera or an imaging system with multiple cameras. The basic collinearity model is used to capture differences between two calibration datasets, and to establish the stability analysis methodology. Geometric simulation is used as a tool to derive image and object space scenarios. Experiments were performed on real calibration datasets from a dual fluoroscopy (DF; X-ray-based) imaging system. The calibration data consisted of hundreds of images and thousands of image observations from six temporal points over a two-day period for a precise evaluation of the DF system stability. The stability of the DF system - for a single camera analysis - was found to be within a range of 0.01 to 0.66 mm in terms of 3D coordinates root-mean-square-error (RMSE), and 0.07 to 0.19 mm for dual cameras analysis. It is to the authors' best knowledge that this work is the first to address the topic of DF stability analysis.

  7. Subset geometric phase analysis method for deformation evaluation of HRTEM images

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hongye [School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081 (China); Liu, Zhanwei, E-mail: liuzw@bit.edu.cn [School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081 (China); Wen, Huihui [School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081 (China); Xie, Huimin, E-mail: xiehm@mail.tsinghua.edu.cn [AML, Department of Engineering Mechanics, Tsinghua University, Beijing 100084 (China); Liu, Chao [Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083 (China)

    2016-12-15

    Geometrical phase analysis (GPA) is typically a powerful tool to investigate the deformation in high resolution transmission electron microscopy images and has been used in various fields. The traditional GPA method using the fast Fourier transform, referred to as global-GPA (G-GPA) here, is based on the relationship between the displacement and the phase difference. In this paper, a subset-GPA (S-GPA) is introduced for further improvement. The S-GPA performs the windowed Fourier transform block by block in the image. The maximum strain measurement scale of the GPA method is theoretically analyzed on the basic of the phase spectrum extraction process. The upper limit is one third of the atomic spacing. The results of various numerical simulations verified that the S-GPA method performs better than the traditional G-GPA method in both the homogeneous and inhomogeneous deformation conditions, with the evaluation parameter of calculation reliability of S-GPA 10% higher than G-GPA. Specifically, the measurement accuracy of S-GPA is about three times higher than the G-GPA when calculating small strain (less than 2000με). For the large strain (greater than 150000με), the measurement accuracy of S-GPA is about 50% higher than that of the G-GPA. Besides, the S-GPA method can significantly eliminate the phase filling effect, while the G-GPA cannot. The S-GPA method has been successfully applied to analyze the strain field distribution in an lnGaAs/InAlAs supperlattice heterostructure. - Highlights: • A subset-GPA method, performing the windowed Fourier transform block by block in HRTEM image, is systematically introduced. • According to the theoretical analysis, the upper limit of absolute maximum strain of GPA method is 1/3. • The measurement accuracy of S-GPA is about three times higher than that of the G-GPA when calculating small strain. • The measurement capability of S-GPA is about 50 percent higher than that of the G-GPA when calculating large strain.

  8. Laser speckle imaging of rat retinal blood flow with hybrid temporal and spatial analysis method

    Science.gov (United States)

    Cheng, Haiying; Yan, Yumei; Duong, Timothy Q.

    2009-02-01

    Noninvasive monitoring of blood flow in retinal circulation will reveal the progression and treatment of ocular disorders, such as diabetic retinopathy, age-related macular degeneration and glaucoma. A non-invasive and direct BF measurement technique with high spatial-temporal resolution is needed for retinal imaging. Laser speckle imaging (LSI) is such a method. Currently, there are two analysis methods for LSI: spatial statistics LSI (SS-LSI) and temporal statistical LSI (TS-LSI). Comparing these two analysis methods, SS-LSI has higher signal to noise ratio (SNR) and TSLSI is less susceptible to artifacts from stationary speckle. We proposed a hybrid temporal and spatial analysis method (HTS-LSI) to measure the retinal blood flow. Gas challenge experiment was performed and images were analyzed by HTS-LSI. Results showed that HTS-LSI can not only remove the stationary speckle but also increase the SNR. Under 100% O2, retinal BF decreased by 20-30%. This was consistent with the results observed with laser Doppler technique. As retinal blood flow is a critical physiological parameter and its perturbation has been implicated in the early stages of many retinal diseases, HTS-LSI will be an efficient method in early detection of retina diseases.

  9. A New Method for Automated Identification and Morphometry of Myelinated Fibers Through Light Microscopy Image Analysis.

    Science.gov (United States)

    Novas, Romulo Bourget; Fazan, Valeria Paula Sassoli; Felipe, Joaquim Cezar

    2016-02-01

    Nerve morphometry is known to produce relevant information for the evaluation of several phenomena, such as nerve repair, regeneration, implant, transplant, aging, and different human neuropathies. Manual morphometry is laborious, tedious, time consuming, and subject to many sources of error. Therefore, in this paper, we propose a new method for the automated morphometry of myelinated fibers in cross-section light microscopy images. Images from the recurrent laryngeal nerve of adult rats and the vestibulocochlear nerve of adult guinea pigs were used herein. The proposed pipeline for fiber segmentation is based on the techniques of competitive clustering and concavity analysis. The evaluation of the proposed method for segmentation of images was done by comparing the automatic segmentation with the manual segmentation. To further evaluate the proposed method considering morphometric features extracted from the segmented images, the distributions of these features were tested for statistical significant difference. The method achieved a high overall sensitivity and very low false-positive rates per image. We detect no statistical difference between the distribution of the features extracted from the manual and the pipeline segmentations. The method presented a good overall performance, showing widespread potential in experimental and clinical settings allowing large-scale image analysis and, thus, leading to more reliable results.

  10. Benchmarking the performance of fixed-image receptor digital radiographic systems part 1: a novel method for image quality analysis.

    Science.gov (United States)

    Lee, Kam L; Ireland, Timothy A; Bernardo, Michael

    2016-06-01

    This is the first part of a two-part study in benchmarking the performance of fixed digital radiographic general X-ray systems. This paper concentrates on reporting findings related to quantitative analysis techniques used to establish comparative image quality metrics. A systematic technical comparison of the evaluated systems is presented in part two of this study. A novel quantitative image quality analysis method is presented with technical considerations addressed for peer review. The novel method was applied to seven general radiographic systems with four different makes of radiographic image receptor (12 image receptors in total). For the System Modulation Transfer Function (sMTF), the use of grid was found to reduce veiling glare and decrease roll-off. The major contributor in sMTF degradation was found to be focal spot blurring. For the System Normalised Noise Power Spectrum (sNNPS), it was found that all systems examined had similar sNNPS responses. A mathematical model is presented to explain how the use of stationary grid may cause a difference between horizontal and vertical sNNPS responses.

  11. 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.

  12. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

  13. Computational methods for molecular imaging

    CERN Document Server

    Shi, Kuangyu; Li, Shuo

    2015-01-01

    This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers fro...

  14. Image analysis as a non-destructive method to assess regrowth of weeds after repeated flame weeding

    DEFF Research Database (Denmark)

    Rask, Anne Merete; Kristoffersen, Palle; Andreasen, Christian

    2013-01-01

    picture of the long-term effect of repeated treatments. Image analysis was most useful for assessing the effect of repeated treatments when weed cover was relatively low (below 40%) and when plots contained relatively much withered plant material. However, when weed cover is close to 100%, dry weight......, and therefore it may influence the long-term effect of repeated treatments. Visual assessment of weed cover or image analysis do not affect the remaining parts of the weed plants after treatment, but the methods may have other disadvantages. In order to evaluate and compare three methods we measured changes...... in vegetation cover of perennial ryegrass after flaming by (1) a simple image analysis programme counting green pixels, (2) visual assessment of images and (3) by taking biomass samples. Plants were flame treated with eight different dosages (0, 20, 30, 35, 45, 60, 90 and 180 kg propane ha-1) and with various...

  15. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results. PMID:24083133

  16. Methods in Astronomical Image Processing

    Science.gov (United States)

    Jörsäter, S.

    A Brief Introductory Note History of Astronomical Imaging Astronomical Image Data Images in Various Formats Digitized Image Data Digital Image Data Philosophy of Astronomical Image Processing Properties of Digital Astronomical Images Human Image Processing Astronomical vs. Computer Science Image Processing Basic Tools of Astronomical Image Processing Display Applications Calibration of Intensity Scales Calibration of Length Scales Image Re-shaping Feature Enhancement Noise Suppression Noise and Error Analysis Image Processing Packages: Design of AIPS and MIDAS AIPS MIDAS Reduction of CCD Data Bias Subtraction Clipping Preflash Subtraction Dark Subtraction Flat Fielding Sky Subtraction Extinction Correction Deconvolution Methods Rebinning/Combining Summary and Prospects for the Future

  17. Diagnostic Value of Nineteen Different Imaging Methods for Patients with Breast Cancer: a Network Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Xiao-Hong Zhang

    2018-04-01

    Full Text Available Background/Aims: We performed a network meta-analysis (NMA to investigate and compare the diagnostic value of 19 different imaging methods used for breast cancer (BC. Methods: Cochrane Library, PubMed and EMBASE were searched to collect the relevant literature from the inception of the study until November 2016. A combination of direct and indirect comparisons was performed using an NMA to evaluate the combined odd ratios (OR and draw the surface under the cumulative ranking curves (SUCRA of the diagnostic value of different imaging methods for BC. Results: A total of 39 eligible diagnostic tests regarding 19 imaging methods (mammography [MG], breast-specific gamma imaging [BSGI], color Doppler sonography [CD], contrast-enhanced magnetic resonance imaging [CE-MRI], digital breast tomosynthesis [DBT], fluorodeoxyglucose positron-emission tomography/computed tomography [FDG PET/CT], fluorodeoxyglucose positron-emission tomography [FDG-PET], full field digital mammography [FFDM], handheld breast ultrasound [HHUS], magnetic resonance imaging [MRI], automated breast volume scanner [ABUS], magnetic resonance mammography [MRM], scintimammography [SMM], single photon emission computed tomography scintimammography [SPECT SMM], ultrasound elastography [UE], ultrasonography [US], mammography + ultrasonography [MG + US], mammography + scintimammography [MG + SMM], and ultrasound elastography + ultrasonography [UE + US] were included in the study. According to this network meta-analysis, in comparison to the MG method, the CE-MRI, MRI, MRM, MG + SMM and UE + US methods exhibited relatively higher sensitivity, and the specificity of the FDG PET/CT method was higher, while the BSGI and MRI methods exhibited higher accuracy. Conclusion: The results from this NMA indicate that the diagnostic value of the BSGI, MG + SMM, MRI and CE-MRI methods for BC were relatively higher in terms of sensitivity, specificity and accuracy.

  18. Registration methods for pulmonary image analysis integration of morphological and physiological knowledge

    CERN Document Server

    Schmidt-Richberg, Alexander

    2014-01-01

    Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved.

  19. Swept-frequency feedback interferometry using terahertz frequency QCLs: a method for imaging and materials analysis.

    Science.gov (United States)

    Rakić, Aleksandar D; Taimre, Thomas; Bertling, Karl; Lim, Yah Leng; Dean, Paul; Indjin, Dragan; Ikonić, Zoran; Harrison, Paul; Valavanis, Alexander; Khanna, Suraj P; Lachab, Mohammad; Wilson, Stephen J; Linfield, Edmund H; Davies, A Giles

    2013-09-23

    The terahertz (THz) frequency quantum cascade laser (QCL) is a compact source of high-power radiation with a narrow intrinsic linewidth. As such, THz QCLs are extremely promising sources for applications including high-resolution spectroscopy, heterodyne detection, and coherent imaging. We exploit the remarkable phase-stability of THz QCLs to create a coherent swept-frequency delayed self-homodyning method for both imaging and materials analysis, using laser feedback interferometry. Using our scheme we obtain amplitude-like and phase-like images with minimal signal processing. We determine the physical relationship between the operating parameters of the laser under feedback and the complex refractive index of the target and demonstrate that this coherent detection method enables extraction of complex refractive indices with high accuracy. This establishes an ultimately compact and easy-to-implement THz imaging and materials analysis system, in which the local oscillator, mixer, and detector are all combined into a single laser.

  20. Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

    Science.gov (United States)

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

    2015-10-06

    Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

  1. A method for the automated processing and analysis of images of ULVWF-platelet strings.

    Science.gov (United States)

    Reeve, Scott R; Abbitt, Katherine B; Cruise, Thomas D; Hose, D Rodney; Lawford, Patricia V

    2013-01-01

    We present a method for identifying and analysing unusually large von Willebrand factor (ULVWF)-platelet strings in noisy low-quality images. The method requires relatively inexpensive, non-specialist equipment and allows multiple users to be employed in the capture of images. Images are subsequently enhanced and analysed, using custom-written software to perform the processing tasks. The formation and properties of ULVWF-platelet strings released in in vitro flow-based assays have recently become a popular research area. Endothelial cells are incorporated into a flow chamber, chemically stimulated to induce ULVWF release and perfused with isolated platelets which are able to bind to the ULVWF to form strings. The numbers and lengths of the strings released are related to characteristics of the flow. ULVWF-platelet strings are routinely identified by eye from video recordings captured during experiments and analysed manually using basic NIH image software to determine the number of strings and their lengths. This is a laborious, time-consuming task and a single experiment, often consisting of data from four to six dishes of endothelial cells, can take 2 or more days to analyse. The method described here allows analysis of the strings to provide data such as the number and length of strings, number of platelets per string and the distance between each platelet to be found. The software reduces analysis time, and more importantly removes user subjectivity, producing highly reproducible results with an error of less than 2% when compared with detailed manual analysis.

  2. 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...

  3. Analysis and Extension of the PCA Method, Estimating a Noise Curve from a Single Image

    Directory of Open Access Journals (Sweden)

    Miguel Colom

    2016-12-01

    Full Text Available In the article 'Image Noise Level Estimation by Principal Component Analysis', S. Pyatykh, J. Hesser, and L. Zheng propose a new method to estimate the variance of the noise in an image from the eigenvalues of the covariance matrix of the overlapping blocks of the noisy image. Instead of using all the patches of the noisy image, the authors propose an iterative strategy to adaptively choose the optimal set containing the patches with lowest variance. Although the method measures uniform Gaussian noise, it can be easily adapted to deal with signal-dependent noise, which is realistic with the Poisson noise model obtained by a CMOS or CCD device in a digital camera.

  4. Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images.

    Science.gov (United States)

    Pang, Jincheng; Özkucur, Nurdan; Ren, Michael; Kaplan, David L; Levin, Michael; Miller, Eric L

    2015-11-01

    Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

  5. Analysis of S-box in Image Encryption Using Root Mean Square Error Method

    Science.gov (United States)

    Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

    2012-07-01

    The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes

  6. Double-compression method for biomedical images

    Science.gov (United States)

    Antonenko, Yevhenii A.; Mustetsov, Timofey N.; Hamdi, Rami R.; Małecka-Massalska, Teresa; Orshubekov, Nurbek; DzierŻak, RóŻa; Uvaysova, Svetlana

    2017-08-01

    This paper describes a double compression method (DCM) of biomedical images. A comparison of image compression factors in size JPEG, PNG and developed DCM was carried out. The main purpose of the DCM - compression of medical images while maintaining the key points that carry diagnostic information. To estimate the minimum compression factor an analysis of the coding of random noise image is presented.

  7. On an image reconstruction method for ECT

    Science.gov (United States)

    Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro

    2007-04-01

    An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.

  8. 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

  9. A modified method of 3D-SSP analysis for amyloid PET imaging using [¹¹C]BF-227.

    Science.gov (United States)

    Kaneta, Tomohiro; Okamura, Nobuyuki; Minoshima, Satoshi; Furukawa, Katsutoshi; Tashiro, Manabu; Furumoto, Shozo; Iwata, Ren; Fukuda, Hiroshi; Takahashi, Shoki; Yanai, Kazuhiko; Kudo, Yukitsuka; Arai, Hiroyuki

    2011-12-01

    Three-dimensional stereotactic surface projection (3D-SSP) analyses have been widely used in dementia imaging studies. However, 3D-SSP sometimes shows paradoxical results on amyloid positron emission tomography (PET) analyses. This is thought to be caused by errors in anatomical standardization (AS) based on an (18)F-fluorodeoxyglucose (FDG) template. We developed a new method of 3D-SSP analysis for amyloid PET imaging, and used it to analyze (11)C-labeled 2-(2-[2-dimethylaminothiazol-5-yl]ethenyl)-6-(2-[fluoro]ethoxy)benzoxazole (BF-227) PET images of subjects with mild cognitive impairment (MCI) and Alzheimer's disease (AD). The subjects were 20 with MCI, 19 patients with AD, and 17 healthy controls. Twelve subjects with MCI were followed up for 3 years or more, and conversion to AD was seen in 6 cases. All subjects underwent PET with both FDG and BF-227. For AS and 3D-SSP analyses of PET data, Neurostat (University of Washington, WA, USA) was used. Method 1 involves AS for BF-227 images using an FDG template. In this study, we developed a new method (Method 2) for AS: First, an FDG image was subjected to AS using an FDG template. Then, the BF-227 image of the same patient was registered to the FDG image, and AS was performed using the transformation parameters calculated for AS of the corresponding FDG images. Regional values were normalized by the average value obtained at the cerebellum and values were calculated for the frontal, parietal, temporal, and occipital lobes. For statistical comparison of the 3 groups, we applied one-way analysis of variance followed by the Bonferroni post hoc test. For statistical comparison between converters and non-converters, the t test was applied. Statistical significance was defined as p SSP analysis of amyloid PET imaging possible. This new method of 3D-SSP analysis for BF-227 PET could prove useful for detecting differences between normal groups and AD and MCI groups, and between converters and non-converters.

  10. Quantitative Analysis of Range Image Patches by NEB Method

    Directory of Open Access Journals (Sweden)

    Wang Wen

    2017-01-01

    Full Text Available In this paper we analyze sampled high dimensional data with the NEB method from a range image database. Select a large random sample of log-valued, high contrast, normalized, 8×8 range image patches from the Brown database. We make a density estimator and we establish 1-dimensional cell complexes from the range image patch data. We find topological properties of 8×8 range image patches, prove that there exist two types of subsets of 8×8 range image patches modelled as a circle.

  11. 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.

  12. 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.

  13. Computational methods in molecular imaging technologies

    CERN Document Server

    Gunjan, Vinit Kumar; Venkatesh, C; Amarnath, M

    2017-01-01

    This book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image processing techniques, and tabulates the statistical values wherever necessary. In a very simple and straightforward way, it explains how image processing methods are used to improve the quality of medical images and facilitate analysis. It offers a valuable resource for researchers, engineers, medical doctors and bioinformatics experts alike.

  14. A method for the automated detection phishing websites through both site characteristics and image analysis

    Science.gov (United States)

    White, Joshua S.; Matthews, Jeanna N.; Stacy, John L.

    2012-06-01

    Phishing website analysis is largely still a time-consuming manual process of discovering potential phishing sites, verifying if suspicious sites truly are malicious spoofs and if so, distributing their URLs to the appropriate blacklisting services. Attackers increasingly use sophisticated systems for bringing phishing sites up and down rapidly at new locations, making automated response essential. In this paper, we present a method for rapid, automated detection and analysis of phishing websites. Our method relies on near real-time gathering and analysis of URLs posted on social media sites. We fetch the pages pointed to by each URL and characterize each page with a set of easily computed values such as number of images and links. We also capture a screen-shot of the rendered page image, compute a hash of the image and use the Hamming distance between these image hashes as a form of visual comparison. We provide initial results demonstrate the feasibility of our techniques by comparing legitimate sites to known fraudulent versions from Phishtank.com, by actively introducing a series of minor changes to a phishing toolkit captured in a local honeypot and by performing some initial analysis on a set of over 2.8 million URLs posted to Twitter over a 4 days in August 2011. We discuss the issues encountered during our testing such as resolvability and legitimacy of URL's posted on Twitter, the data sets used, the characteristics of the phishing sites we discovered, and our plans for future work.

  15. Quality control in dual head γ-cameras: comparison between methods and software s used for image analysis

    International Nuclear Information System (INIS)

    Nayl E, A.; Fornasier, M. R.; De Denaro, M.; Sulieman, A.; Alkhorayef, M.; Bradley, D.

    2017-10-01

    Patient radiation dose and image quality are the main issues in nuclear medicine (Nm) procedures. Currently, many protocols are used for image acquisition and analysis of quality control (Qc) tests. National Electrical Manufacturers Association (Nema) methods and protocols are widely accepted method used for providing accurate description, measurement and reporting of γ-camera performance parameters. However, no standard software is available for image analysis. The aim os this study was to compare between the vendor Qc software analysis and three software from different developers downloaded free from internet; NMQC, Nm Tool kit and ImageJ-Nm Tool kit software. The three software are used for image analysis of some Qc tests for γ-cameras based on Nema protocols including non-uniformity evaluation. Ten non-uniformity Qc images were taken from dual head γ-camera (Siemens Symbia) installed in Trieste general hospital (Italy), and analyzed. Excel analysis was used as baseline calculation of the non-uniformity test according Nema procedures. The results of the non-uniformity analysis showed good agreement between the three independent software and excel calculation (the average differences were 0.3%, 2.9%, 1.3% and 1.6% for UFOV integral, UFOV differential, CFOV integral and CFOV differential respectively), while significant difference was detected on the analysis of the company Qc software with compare to the excel analysis (the average differences were 14.6%, 20.7%, 25.7% and 31.9% for UFOV integral, UFOV differential, CFOV integral and CFOV differential respectively). NMQC software was the best in comparison with the excel calculations. The variation in the results is due to different pixel sizes used for analysis in the three software and the γ-camera Qc software. Therefore, is important to perform the tests by the vendor Qc software as well as by independent analysis to understand the differences between the values. Moreover, the medical physicist should know

  16. Quality control in dual head γ-cameras: comparison between methods and software s used for image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Nayl E, A. [Sudan Atomic Energy Commission, Radiation Safety Institute, Khartoum (Sudan); Fornasier, M. R.; De Denaro, M. [Azienda Sanitaria Universitaria Integrata di Trieste, Medical Physics Department, Via Giovanni Sai 7, 34128 Trieste (Italy); Sulieman, A. [Prince Sattam bin Abdulaziz University, College of Applied Medical Sciences, Radiology and Medical Imaging Department, P. O. Box 422, 11942 Al-Kharj (Saudi Arabia); Alkhorayef, M.; Bradley, D., E-mail: abdwsh10@hotmail.com [University of Surrey, Department of Physics, GU2-7XH Guildford, Surrey (United Kingdom)

    2017-10-15

    Patient radiation dose and image quality are the main issues in nuclear medicine (Nm) procedures. Currently, many protocols are used for image acquisition and analysis of quality control (Qc) tests. National Electrical Manufacturers Association (Nema) methods and protocols are widely accepted method used for providing accurate description, measurement and reporting of γ-camera performance parameters. However, no standard software is available for image analysis. The aim os this study was to compare between the vendor Qc software analysis and three software from different developers downloaded free from internet; NMQC, Nm Tool kit and ImageJ-Nm Tool kit software. The three software are used for image analysis of some Qc tests for γ-cameras based on Nema protocols including non-uniformity evaluation. Ten non-uniformity Qc images were taken from dual head γ-camera (Siemens Symbia) installed in Trieste general hospital (Italy), and analyzed. Excel analysis was used as baseline calculation of the non-uniformity test according Nema procedures. The results of the non-uniformity analysis showed good agreement between the three independent software and excel calculation (the average differences were 0.3%, 2.9%, 1.3% and 1.6% for UFOV integral, UFOV differential, CFOV integral and CFOV differential respectively), while significant difference was detected on the analysis of the company Qc software with compare to the excel analysis (the average differences were 14.6%, 20.7%, 25.7% and 31.9% for UFOV integral, UFOV differential, CFOV integral and CFOV differential respectively). NMQC software was the best in comparison with the excel calculations. The variation in the results is due to different pixel sizes used for analysis in the three software and the γ-camera Qc software. Therefore, is important to perform the tests by the vendor Qc software as well as by independent analysis to understand the differences between the values. Moreover, the medical physicist should know

  17. 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

  18. Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

    Science.gov (United States)

    Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

    2013-01-08

    Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

  19. Method for analysis of failure of material employing imaging

    Energy Technology Data Exchange (ETDEWEB)

    Vinegar, H.J.; Wellington, S.L.; de Waal, J.A.

    1989-12-05

    This patent describes a method for determining at least one preselected property of a sample of material employing an imaging apparatus. It comprises: imaging the sample during the application of known preselected forces to the sample, and determining density in the sample responsive to the preselected forces.

  20. 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.

  1. Statistical Methods for Magnetic Resonance Image Analysis with Applications to Multiple Sclerosis

    Science.gov (United States)

    Pomann, Gina-Maria

    Multiple sclerosis (MS) is an immune-mediated neurological disease that causes disability and morbidity. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. In the first part of the dissertation, we present methodology to study to compare the brain anatomy between patients with MS and controls. A nonparametric testing procedure is proposed for testing the null hypothesis that two samples of curves observed at discrete grids and with noise have the same underlying distribution. We propose to decompose the curves using functional principal component analysis of an appropriate mixture process, which we refer to as marginal functional principal component analysis. This approach reduces the dimension of the testing problem in a way that enables the use of traditional nonparametric univariate testing procedures. The procedure is computationally efficient and accommodates different sampling designs. Numerical studies are presented to validate the size and power properties of the test in many realistic scenarios. In these cases, the proposed test is more powerful than its primary competitor. The proposed methodology is illustrated on a state-of-the art diffusion tensor imaging study, where the objective is to compare white matter tract profiles in healthy individuals and MS patients. In the second part of the thesis, we present methods to study the behavior of MS in the white matter of the brain. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related processes and is a primary outcome considered in clinical trials of treatments for MS. Such abnormalities in active MS lesions are evaluated in vivo using contrast-enhanced structural magnetic resonance imaging (MRI), during which patients receive an intravenous infusion of a costly magnetic contrast agent. In some instances, the contrast agents can have toxic effects. Recently, local

  2. 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...

  3. A comparative study on medical image segmentation methods

    Directory of Open Access Journals (Sweden)

    Praylin Selva Blessy SELVARAJ ASSLEY

    2014-03-01

    Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

  4. 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

  5. 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.)

  6. 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

  7. An Image Encryption Method Based on Bit Plane Hiding Technology

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; LI Zhitang; TU Hao

    2006-01-01

    A novel image hiding method based on the correlation analysis of bit plane is described in this paper. Firstly, based on the correlation analysis, different bit plane of a secret image is hided in different bit plane of several different open images. And then a new hiding image is acquired by a nesting "Exclusive-OR" operation on those images obtained from the first step. At last, by employing image fusion technique, the final hiding result is achieved. The experimental result shows that the method proposed in this paper is effective.

  8. METHODS OF DISTANCE MEASUREMENT’S ACCURACY INCREASING BASED ON THE CORRELATION ANALYSIS OF STEREO IMAGES

    Directory of Open Access Journals (Sweden)

    V. L. Kozlov

    2018-01-01

    Full Text Available To solve the problem of increasing the accuracy of restoring a three-dimensional picture of space using two-dimensional digital images, it is necessary to use new effective techniques and algorithms for processing and correlation analysis of digital images. Actively developed tools that allow you to reduce the time costs for processing stereo images, improve the quality of the depth maps construction and automate their construction. The aim of the work is to investigate the possibilities of using various techniques for processing digital images to improve the measurements accuracy of the rangefinder based on the correlation analysis of the stereo image. The results of studies of the influence of color channel mixing techniques on the distance measurements accuracy for various functions realizing correlation processing of images are presented. Studies on the analysis of the possibility of using integral representation of images to reduce the time cost in constructing a depth map areproposed. The results of studies of the possibility of using images prefiltration before correlation processing when distance measuring by stereo imaging areproposed.It is obtained that using of uniform mixing of channels leads to minimization of the total number of measurement errors, and using of brightness extraction according to the sRGB standard leads to an increase of errors number for all of the considered correlation processing techniques. Integral representation of the image makes it possible to accelerate the correlation processing, but this method is useful for depth map calculating in images no more than 0.5 megapixels. Using of image filtration before correlation processing can provide, depending on the filter parameters, either an increasing of the correlation function value, which is useful for analyzing noisy images, or compression of the correlation function.

  9. A simple method for detecting tumor in T2-weighted MRI brain images. An image-based analysis

    International Nuclear Information System (INIS)

    Lau, Phooi-Yee; Ozawa, Shinji

    2006-01-01

    The objective of this paper is to present a decision support system which uses a computer-based procedure to detect tumor blocks or lesions in digitized medical images. The authors developed a simple method with a low computation effort to detect tumors on T2-weighted Magnetic Resonance Imaging (MRI) brain images, focusing on the connection between the spatial pixel value and tumor properties from four different perspectives: cases having minuscule differences between two images using a fixed block-based method, tumor shape and size using the edge and binary images, tumor properties based on texture values using spatial pixel intensity distribution controlled by a global discriminate value, and the occurrence of content-specific tumor pixel for threshold images. Measurements of the following medical datasets were performed: different time interval images, and different brain disease images on single and multiple slice images. Experimental results have revealed that our proposed technique incurred an overall error smaller than those in other proposed methods. In particular, the proposed method allowed decrements of false alarm and missed alarm errors, which demonstrate the effectiveness of our proposed technique. In this paper, we also present a prototype system, known as PCB, to evaluate the performance of the proposed methods by actual experiments, comparing the detection accuracy and system performance. (author)

  10. Methods of Blood Oxygen Level-Dependent Magnetic Resonance Imaging Analysis for Evaluating Renal Oxygenation

    Directory of Open Access Journals (Sweden)

    Fen Chen

    2018-03-01

    Full Text Available Blood oxygen level-dependent magnetic resonance imaging (BOLD MRI has recently been utilized as a noninvasive tool for evaluating renal oxygenation. Several methods have been proposed for analyzing BOLD images. Regional ROI selection is the earliest and most widely used method for BOLD analysis. In the last 20 years, many investigators have used this method to evaluate cortical and medullary oxygenation in patients with ischemic nephropathy, hypertensive nephropathy, diabetic nephropathy, chronic kidney disease (CKD, acute kidney injury and renal allograft rejection. However, clinical trials of BOLD MRI using regional ROI selection revealed that it was difficult to distinguish the renal cortico-medullary zones with this method, and that it was susceptible to observer variability. To overcome these deficiencies, several new methods were proposed for analyzing BOLD images, including the compartmental approach, fractional hypoxia method, concentric objects (CO method and twelve-layer concentric objects (TLCO method. The compartmental approach provides an algorithm to judge whether the pixel belongs to the cortex or medulla. Fractional kidney hypoxia, measured by using BOLD MRI, was negatively correlated with renal blood flow, tissue perfusion and glomerular filtration rate (GFR in patients with atherosclerotic renal artery stenosis. The CO method divides the renal parenchyma into six or twelve layers of thickness in each coronal slice of BOLD images and provides a R2* radial profile curve. The slope of the R2* curve associated positively with eGFR in CKD patients. Indeed, each method invariably has advantages and disadvantages, and there is generally no consensus method so far. Undoubtedly, analytic approaches for BOLD MRI with better reproducibility would assist clinicians in monitoring the degree of kidney hypoxia and thus facilitating timely reversal of tissue hypoxia.

  11. Survey: interpolation methods for whole slide image processing.

    Science.gov (United States)

    Roszkowiak, L; Korzynska, A; Zak, J; Pijanowska, D; Swiderska-Chadaj, Z; Markiewicz, T

    2017-02-01

    Evaluating whole slide images of histological and cytological samples is used in pathology for diagnostics, grading and prognosis . It is often necessary to rescale whole slide images of a very large size. Image resizing is one of the most common applications of interpolation. We collect the advantages and drawbacks of nine interpolation methods, and as a result of our analysis, we try to select one interpolation method as the preferred solution. To compare the performance of interpolation methods, test images were scaled and then rescaled to the original size using the same algorithm. The modified image was compared to the original image in various aspects. The time needed for calculations and results of quantification performance on modified images were also compared. For evaluation purposes, we used four general test images and 12 specialized biological immunohistochemically stained tissue sample images. The purpose of this survey is to determine which method of interpolation is the best to resize whole slide images, so they can be further processed using quantification methods. As a result, the interpolation method has to be selected depending on the task involving whole slide images. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

  12. Magnetic resonance spectroscopy as an imaging method

    International Nuclear Information System (INIS)

    Bomsdorf, H.; Imme, M.; Jensen, D.; Kunz, D.; Menhardt, W.; Ottenberg, K.; Roeschmann, P.; Schmidt, K.H.; Tschendel, O.; Wieland, J.

    1990-01-01

    An experimental Magnetic Resonance (MR) system with 4 tesla flux density was set up. For that purpose a data acquisition system and RF coils for resonance frequencies up to 170 MHz were developed. Methods for image guided spectroscopy as well as spectroscopic imaging focussing on the nuclei 1 H and 13 C were developed and tested on volunteers and selected patients. The advantages of the high field strength with respect to spectroscopic studies were demonstrated. Developments of a new fast imaging technique for the acquisition of scout images as well as a method for mapping and displaying the magnetic field inhomogeneity in-vivo represent contributions to the optimisation of the experimental procedure in spectroscopic studies. Investigations on the interaction of RF radiation with the exposed tissue allowed conclusions regarding the applicability of MR methods at high field strengths. Methods for display and processing of multi-dimensional spectroscopic imaging data sets were developed and existing methods for real-time image synthesis were extended. Results achieved in the field of computer aided analysis of MR images comprised new techniques for image background detection, contour detection and automatic image interpretation as well as knowledge bases for textural representation of medical knowledge for diagnosis. (orig.) With 82 refs., 3 tabs., 75 figs [de

  13. 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.

  14. [Multimodal medical image registration using cubic spline interpolation method].

    Science.gov (United States)

    He, Yuanlie; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

    2007-12-01

    Based on the characteristic of the PET-CT multimodal image series, a novel image registration and fusion method is proposed, in which the cubic spline interpolation method is applied to realize the interpolation of PET-CT image series, then registration is carried out by using mutual information algorithm and finally the improved principal component analysis method is used for the fusion of PET-CT multimodal images to enhance the visual effect of PET image, thus satisfied registration and fusion results are obtained. The cubic spline interpolation method is used for reconstruction to restore the missed information between image slices, which can compensate for the shortage of previous registration methods, improve the accuracy of the registration, and make the fused multimodal images more similar to the real image. Finally, the cubic spline interpolation method has been successfully applied in developing 3D-CRT (3D Conformal Radiation Therapy) system.

  15. Images Encryption Method using Steganographic LSB Method, AES and RSA algorithm

    Science.gov (United States)

    Moumen, Abdelkader; Sissaoui, Hocine

    2017-03-01

    Vulnerability of communication of digital images is an extremely important issue nowadays, particularly when the images are communicated through insecure channels. To improve communication security, many cryptosystems have been presented in the image encryption literature. This paper proposes a novel image encryption technique based on an algorithm that is faster than current methods. The proposed algorithm eliminates the step in which the secrete key is shared during the encryption process. It is formulated based on the symmetric encryption, asymmetric encryption and steganography theories. The image is encrypted using a symmetric algorithm, then, the secret key is encrypted by means of an asymmetrical algorithm and it is hidden in the ciphered image using a least significant bits steganographic scheme. The analysis results show that while enjoying the faster computation, our method performs close to optimal in terms of accuracy.

  16. Efficient analysis of three dimensional EUV mask induced imaging artifacts using the waveguide decomposition method

    Science.gov (United States)

    Shao, Feng; Evanschitzky, Peter; Fühner, Tim; Erdmann, Andreas

    2009-10-01

    This paper employs the Waveguide decomposition method as an efficient rigorous electromagnetic field (EMF) solver to investigate three dimensional mask-induced imaging artifacts in EUV lithography. The major mask diffraction induced imaging artifacts are first identified by applying the Zernike analysis of the mask nearfield spectrum of 2D lines/spaces. Three dimensional mask features like 22nm semidense/dense contacts/posts, isolated elbows and line-ends are then investigated in terms of lithographic results. After that, the 3D mask-induced imaging artifacts such as feature orientation dependent best focus shift, process window asymmetries, and other aberration-like phenomena are explored for the studied mask features. The simulation results can help lithographers to understand the reasons of EUV-specific imaging artifacts and to devise illumination and feature dependent strategies for their compensation in the optical proximity correction (OPC) for EUV masks. At last, an efficient approach using the Zernike analysis together with the Waveguide decomposition technique is proposed to characterize the impact of mask properties for the future OPC process.

  17. VELOCITY FIELD COMPUTATION IN VIBRATED GRANULAR MEDIA USING AN OPTICAL FLOW BASED MULTISCALE IMAGE ANALYSIS METHOD

    Directory of Open Access Journals (Sweden)

    Johan Debayle

    2011-05-01

    Full Text Available An image analysis method has been developed in order to compute the velocity field of a granular medium (sand grains, mean diameter 600 μm submitted to different kinds of mechanical stresses. The differential method based on optical flow conservation consists in describing a dense motion field with vectors associated to each pixel. A multiscale, coarse-to-fine, analytical approach through tailor sized windows yields the best compromise between accuracy and robustness of the results, while enabling an acceptable computation time. The corresponding algorithmis presented and its validation discussed through different tests. The results of the validation tests of the proposed approach show that the method is satisfactory when attributing specific values to parameters in association with the size of the image analysis window. An application in the case of vibrated sand has been studied. An instrumented laboratory device provides sinusoidal vibrations and enables external optical observations of sand motion in 3D transparent boxes. At 50 Hz, by increasing the relative acceleration G, the onset and development of two convective rolls can be observed. An ultra fast camera records the grain avalanches, and several pairs of images are analysed by the proposed method. The vertical velocity profiles are deduced and allow to precisely quantify the dimensions of the fluidized region as a function of G.

  18. A new method of the light irradiation image by the computed radiography (imaging plate) system

    International Nuclear Information System (INIS)

    Aiba, Susumu; Nishi, Katsuki.

    1997-01-01

    There are two method for the purpose of diagnosing medically by using gamma-ray light irradiation image. One is to use of the scintillation camera for gamma-ray, the other is to use of the photostimulable luminescence point by the secondary excitation of the image plate (IP) system for X-ray. The standpoint of the spatial resolution at the total medical image, using gamma-ray, the first can get the image on a short time, but the first is a poor image quality, and the second is good image quality, but the second can get the image on a long time, because of insensitive to gamma-ray. We report on the improvement for IP's week point by our proposal method, and by our clinical and quantitative analysis data, to use the highly efficient IP (ST-III). We make the improvement on the imaging time (from 30 minutes to 20 minutes), and the inprocessing time (from 33-50 minutes to 27 minutes) for a former method on an organism. We strongly believe that our convenience improvement method, and our clinical quantitative analysis data can contribute to the wide application as well as the quality up for the clinical diagnosis to use gamma-ray. (author)

  19. Seismic zonation of Port-Au-Prince using pixel- and object-based imaging analysis methods on ASTER GDEM

    Science.gov (United States)

    Yong, Alan; Hough, Susan E.; Cox, Brady R.; Rathje, Ellen M.; Bachhuber, Jeff; Dulberg, Ranon; Hulslander, David; Christiansen, Lisa; and Abrams, Michael J.

    2011-01-01

    We report about a preliminary study to evaluate the use of semi-automated imaging analysis of remotely-sensed DEM and field geophysical measurements to develop a seismic-zonation map of Port-au-Prince, Haiti. For in situ data, VS30 values are derived from the MASW technique deployed in and around the city. For satellite imagery, we use an ASTER GDEM of Hispaniola. We apply both pixel- and object-based imaging methods on the ASTER GDEM to explore local topography (absolute elevation values) and classify terrain types such as mountains, alluvial fans and basins/near-shore regions. We assign NEHRP seismic site class ranges based on available VS30 values. A comparison of results from imagery-based methods to results from traditional geologic-based approaches reveals good overall correspondence. We conclude that image analysis of RS data provides reliable first-order site characterization results in the absence of local data and can be useful to refine detailed site maps with sparse local data.

  20. Mathematical methods in elasticity imaging

    CERN Document Server

    Ammari, Habib; Garnier, Josselin; Kang, Hyeonbae; Lee, Hyundae; Wahab, Abdul

    2015-01-01

    This book is the first to comprehensively explore elasticity imaging and examines recent, important developments in asymptotic imaging, modeling, and analysis of deterministic and stochastic elastic wave propagation phenomena. It derives the best possible functional images for small inclusions and cracks within the context of stability and resolution, and introduces a topological derivative-based imaging framework for detecting elastic inclusions in the time-harmonic regime. For imaging extended elastic inclusions, accurate optimal control methodologies are designed and the effects of uncertainties of the geometric or physical parameters on stability and resolution properties are evaluated. In particular, the book shows how localized damage to a mechanical structure affects its dynamic characteristics, and how measured eigenparameters are linked to elastic inclusion or crack location, orientation, and size. Demonstrating a novel method for identifying, locating, and estimating inclusions and cracks in elastic...

  1. Wavelet-Based Bayesian Methods for Image Analysis and Automatic Target Recognition

    National Research Council Canada - National Science Library

    Nowak, Robert

    2001-01-01

    .... We have developed two new techniques. First, we have develop a wavelet-based approach to image restoration and deconvolution problems using Bayesian image models and an alternating-maximation method...

  2. Development of Quantification Method for Bioluminescence Imaging

    International Nuclear Information System (INIS)

    Kim, Hyeon Sik; Min, Jung Joon; Lee, Byeong Il; Choi, Eun Seo; Tak, Yoon O; Choi, Heung Kook; Lee, Ju Young

    2009-01-01

    Optical molecular luminescence imaging is widely used for detection and imaging of bio-photons emitted by luminescent luciferase activation. The measured photons in this method provide the degree of molecular alteration or cell numbers with the advantage of high signal-to-noise ratio. To extract useful information from the measured results, the analysis based on a proper quantification method is necessary. In this research, we propose a quantification method presenting linear response of measured light signal to measurement time. We detected the luminescence signal by using lab-made optical imaging equipment of animal light imaging system (ALIS) and different two kinds of light sources. One is three bacterial light-emitting sources containing different number of bacteria. The other is three different non-bacterial light sources emitting very weak light. By using the concept of the candela and the flux, we could derive simplified linear quantification formula. After experimentally measuring light intensity, the data was processed with the proposed quantification function. We could obtain linear response of photon counts to measurement time by applying the pre-determined quantification function. The ratio of the re-calculated photon counts and measurement time present a constant value although different light source was applied. The quantification function for linear response could be applicable to the standard quantification process. The proposed method could be used for the exact quantitative analysis in various light imaging equipment with presenting linear response behavior of constant light emitting sources to measurement time

  3. A biosegmentation benchmark for evaluation of bioimage analysis methods

    Directory of Open Access Journals (Sweden)

    Kvilekval Kristian

    2009-11-01

    Full Text Available Abstract Background We present a biosegmentation benchmark that includes infrastructure, datasets with associated ground truth, and validation methods for biological image analysis. The primary motivation for creating this resource comes from the fact that it is very difficult, if not impossible, for an end-user to choose from a wide range of segmentation methods available in the literature for a particular bioimaging problem. No single algorithm is likely to be equally effective on diverse set of images and each method has its own strengths and limitations. We hope that our benchmark resource would be of considerable help to both the bioimaging researchers looking for novel image processing methods and image processing researchers exploring application of their methods to biology. Results Our benchmark consists of different classes of images and ground truth data, ranging in scale from subcellular, cellular to tissue level, each of which pose their own set of challenges to image analysis. The associated ground truth data can be used to evaluate the effectiveness of different methods, to improve methods and to compare results. Standard evaluation methods and some analysis tools are integrated into a database framework that is available online at http://bioimage.ucsb.edu/biosegmentation/. Conclusion This online benchmark will facilitate integration and comparison of image analysis methods for bioimages. While the primary focus is on biological images, we believe that the dataset and infrastructure will be of interest to researchers and developers working with biological image analysis, image segmentation and object tracking in general.

  4. Box-Counting Method of 2D Neuronal Image: Method Modification and Quantitative Analysis Demonstrated on Images from the Monkey and Human Brain

    Directory of Open Access Journals (Sweden)

    Nemanja Rajković

    2017-01-01

    Full Text Available This study calls attention to the difference between traditional box-counting method and its modification. The appropriate scaling factor, influence on image size and resolution, and image rotation, as well as different image presentation, are showed on the sample of asymmetrical neurons from the monkey dentate nucleus. The standard BC method and its modification were evaluated on the sample of 2D neuronal images from the human neostriatum. In addition, three box dimensions (which estimate the space-filling property, the shape, complexity, and the irregularity of dendritic tree were used to evaluate differences in the morphology of type III aspiny neurons between two parts of the neostriatum.

  5. Box-Counting Method of 2D Neuronal Image: Method Modification and Quantitative Analysis Demonstrated on Images from the Monkey and Human Brain.

    Science.gov (United States)

    Rajković, Nemanja; Krstonošić, Bojana; Milošević, Nebojša

    2017-01-01

    This study calls attention to the difference between traditional box-counting method and its modification. The appropriate scaling factor, influence on image size and resolution, and image rotation, as well as different image presentation, are showed on the sample of asymmetrical neurons from the monkey dentate nucleus. The standard BC method and its modification were evaluated on the sample of 2D neuronal images from the human neostriatum. In addition, three box dimensions (which estimate the space-filling property, the shape, complexity, and the irregularity of dendritic tree) were used to evaluate differences in the morphology of type III aspiny neurons between two parts of the neostriatum.

  6. Computational Methods for Nanoscale X-ray Computed Tomography Image Analysis of Fuel Cell and Battery Materials

    Science.gov (United States)

    Kumar, Arjun S.

    Over the last fifteen years, there has been a rapid growth in the use of high resolution X-ray computed tomography (HRXCT) imaging in material science applications. We use it at nanoscale resolutions up to 50 nm (nano-CT) for key research problems in large scale operation of polymer electrolyte membrane fuel cells (PEMFC) and lithium-ion (Li-ion) batteries in automotive applications. PEMFC are clean energy sources that electrochemically react with hydrogen gas to produce water and electricity. To reduce their costs, capturing their electrode nanostructure has become significant in modeling and optimizing their performance. For Li-ion batteries, a key challenge in increasing their scope for the automotive industry is Li metal dendrite growth. Li dendrites are structures of lithium with 100 nm features of interest that can grow chaotically within a battery and eventually lead to a short-circuit. HRXCT imaging is an effective diagnostics tool for such applications as it is a non-destructive method of capturing the 3D internal X-ray absorption coefficient of materials from a large series of 2D X-ray projections. Despite a recent push to use HRXCT for quantitative information on material samples, there is a relative dearth of computational tools in nano-CT image processing and analysis. Hence, we focus on developing computational methods for nano-CT image analysis of fuel cell and battery materials as required by the limitations in material samples and the imaging environment. The first problem we address is the segmentation of nano-CT Zernike phase contrast images. Nano-CT instruments are equipped with Zernike phase contrast optics to distinguish materials with a low difference in X-ray absorption coefficient by phase shifting the X-ray wave that is not diffracted by the sample. However, it creates image artifacts that hinder the use of traditional image segmentation techniques. To restore such images, we setup an inverse problem by modeling the X-ray phase contrast

  7. 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)

  8. 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)

  9. Method for evaluation of human induced pluripotent stem cell quality using image analysis based on the biological morphology of cells.

    Science.gov (United States)

    Wakui, Takashi; Matsumoto, Tsuyoshi; Matsubara, Kenta; Kawasaki, Tomoyuki; Yamaguchi, Hiroshi; Akutsu, Hidenori

    2017-10-01

    We propose an image analysis method for quality evaluation of human pluripotent stem cells based on biologically interpretable features. It is important to maintain the undifferentiated state of induced pluripotent stem cells (iPSCs) while culturing the cells during propagation. Cell culture experts visually select good quality cells exhibiting the morphological features characteristic of undifferentiated cells. Experts have empirically determined that these features comprise prominent and abundant nucleoli, less intercellular spacing, and fewer differentiating cellular nuclei. We quantified these features based on experts' visual inspection of phase contrast images of iPSCs and found that these features are effective for evaluating iPSC quality. We then developed an iPSC quality evaluation method using an image analysis technique. The method allowed accurate classification, equivalent to visual inspection by experts, of three iPSC cell lines.

  10. Blind image deconvolution methods and convergence

    CERN Document Server

    Chaudhuri, Subhasis; Rameshan, Renu

    2014-01-01

    Blind deconvolution is a classical image processing problem which has been investigated by a large number of researchers over the last four decades. The purpose of this monograph is not to propose yet another method for blind image restoration. Rather the basic issue of deconvolvability has been explored from a theoretical view point. Some authors claim very good results while quite a few claim that blind restoration does not work. The authors clearly detail when such methods are expected to work and when they will not. In order to avoid the assumptions needed for convergence analysis in the

  11. Investigation of Optimal Integrated Circuit Raster Image Vectorization Method

    Directory of Open Access Journals (Sweden)

    Leonas Jasevičius

    2011-03-01

    Full Text Available Visual analysis of integrated circuit layer requires raster image vectorization stage to extract layer topology data to CAD tools. In this paper vectorization problems of raster IC layer images are presented. Various line extraction from raster images algorithms and their properties are discussed. Optimal raster image vectorization method was developed which allows utilization of common vectorization algorithms to achieve the best possible extracted vector data match with perfect manual vectorization results. To develop the optimal method, vectorized data quality dependence on initial raster image skeleton filter selection was assessed.Article in Lithuanian

  12. Comparison of different methods of spatial normalization of FDG-PET brain images in the voxel-wise analysis of MCI patients and controls

    International Nuclear Information System (INIS)

    Martino, M.E.; Villoria, J.G. de; Lacalle-Aurioles, M.; Olazaran, J.; Navarro, E.; Desco, M.; Cruz, I.; Garcia-Vazquez, V.; Carreras, J.L.

    2013-01-01

    One of the most interesting clinical applications of 18F-fluorodexyglucose (FDG) positron emission tomography (PET) imaging in neurodegenerative pathologies is that of establishing the prognosis of patients with mild cognitive impairment (MCI), some of whom have a high risk of progressing to Alzheimer's disease (AD). One method of analyzing these images is to perform statistical parametric mapping (SPM) analysis. Spatial normalization is a critical step in such an analysis. The purpose of this study was to assess the effect of using different methods of spatial normalization on the results of SPM analysis of 18F-FDG PET images by comparing patients with MCI and controls. We evaluated the results of three spatial normalization methods in an SPM analysis by comparing patients diagnosed with MCI with a group of control subjects. We tested three methods of spatial normalization: MRI-diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) and MRI-SPM8, which combine structural and functional images, and FDG-SPM8, which is based on the functional images only. The results obtained with the three methods were consistent in terms of the main pattern of functional alterations detected; namely, a bilateral reduction in glucose metabolism in the frontal and parietal cortices in the patient group. However, MRI-SPM8 also revealed differences in the left temporal cortex, and MRI-DARTEL revealed further differences in the left temporal cortex, precuneus, and left posterior cingulate. The results obtained with MRI-DARTEL were the most consistent with the pattern of changes in AD. When we compared our observations with those of previous reports, MRI-SPM8 and FDG-SPM8 seemed to show an incomplete pattern. Our results suggest that basing the spatial normalization method on functional images only can considerably impair the results of SPM analysis of 18F-FDG PET studies. (author)

  13. Methods of Hematoxylin and Erosin Image Information Acquisition and Optimization in Confocal Microscopy.

    Science.gov (United States)

    Yoon, Woong Bae; Kim, Hyunjin; Kim, Kwang Gi; Choi, Yongdoo; Chang, Hee Jin; Sohn, Dae Kyung

    2016-07-01

    We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis.

  14. A Study on the Improvement of Digital Periapical Images using Image Interpolation Methods

    International Nuclear Information System (INIS)

    Song, Nam Kyu; Koh, Kwang Joon

    1998-01-01

    Image resampling is of particular interest in digital radiology. When resampling an image to a new set of coordinate, there appears blocking artifacts and image changes. To enhance image quality, interpolation algorithms have been used. Resampling is used to increase the number of points in an image to improve its appearance for display. The process of interpolation is fitting a continuous function to the discrete points in the digital image. The purpose of this study was to determine the effects of the seven interpolation functions when image resampling in digital periapical images. The images were obtained by Digora, CDR and scanning of Ektaspeed plus periapical radiograms on the dry skull and human subject. The subjects were exposed to intraoral X-ray machine at 60 kVp and 70 kVp with exposure time varying between 0.01 and 0.50 second. To determine which interpolation method would provide the better image, seven functions were compared ; (1) nearest neighbor (2) linear (3) non-linear (4) facet model (5) cubic convolution (6) cubic spline (7) gray segment expansion. And resampled images were compared in terms of SNR (Signal to Noise Ratio) and MTF (Modulation Transfer Function) coefficient value. The obtained results were as follows ; 1. The highest SNR value (75.96 dB) was obtained with cubic convolution method and the lowest SNR value (72.44 dB) was obtained with facet model method among seven interpolation methods. 2. There were significant differences of SNR values among CDR, Digora and film scan (P 0.05). 4. There were significant differences of MTF coefficient values between linear interpolation method and the other six interpolation methods (P<0.05). 5. The speed of computation time was the fastest with nearest neighbor method and the slowest with non-linear method. 6. The better image was obtained with cubic convolution, cubic spline and gray segment method in ROC analysis. 7. The better sharpness of edge was obtained with gray segment expansion method

  15. Implementation of quantitative methods of analysis of the image quality in mammography

    International Nuclear Information System (INIS)

    Ruiz Rodriguez, Ana Mariela

    2012-01-01

    A proper diagnosis of a mammogram requires optimal contrast and maximum resolution, this allows to visualize different structures with low contrast and diameter of the order of millimeters. The evaluation of image quality allows to characterize the physical properties of the system of image acquisition, such assessment is one of the cornerstones in a quality control program. The image quality of the ACR phantom was evaluated with the IAEA TECDOC 1517 protocol. Analytical methods have determined quality parameters of the dummy image TOR MAS. A method is developed to analyze the image quality of both mammographic phantoms by use of computational techniques with the ImageJ program, in doing this, more information was able to objectively characterize the image quality of the dummies. Furthermore, these parameters will serve to compare the images obtained at different mammographic centers of the Caja Costarricense de Seguro Social (CCSS) and eventually the time evolution in a particular installation. (author) [es

  16. 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

  17. 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.

  18. Hybrid statistics-simulations based method for atom-counting from ADF STEM images

    Energy Technology Data Exchange (ETDEWEB)

    De wael, Annelies, E-mail: annelies.dewael@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); De Backer, Annick [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Jones, Lewys; Nellist, Peter D. [Department of Materials, University of Oxford, Parks Road, OX1 3PH Oxford (United Kingdom); Van Aert, Sandra, E-mail: sandra.vanaert@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium)

    2017-06-15

    A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. - Highlights: • A hybrid method for atom-counting from ADF STEM images is introduced. • Image simulations are incorporated into a statistical framework in a reliable manner. • Limits of the existing methods for atom-counting are far exceeded. • Reliable counting results from an experimental low dose image are obtained. • Progress towards reliable quantitative analysis of beam-sensitive materials is made.

  19. Highly Robust Statistical Methods in Medical Image Analysis

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf

  20. Seismic-zonation of Port-au-Prince using pixel- and object-based imaging analysis methods on ASTER GDEM

    Science.gov (United States)

    Yong, A.; Hough, S.E.; Cox, B.R.; Rathje, E.M.; Bachhuber, J.; Dulberg, R.; Hulslander, D.; Christiansen, L.; Abrams, M.J.

    2011-01-01

    We report about a preliminary study to evaluate the use of semi-automated imaging analysis of remotely-sensed DEM and field geophysical measurements to develop a seismic-zonation map of Port-au-Prince, Haiti. For in situ data, Vs30 values are derived from the MASW technique deployed in and around the city. For satellite imagery, we use an ASTER GDEM of Hispaniola. We apply both pixel- and object-based imaging methods on the ASTER GDEM to explore local topography (absolute elevation values) and classify terrain types such as mountains, alluvial fans and basins/near-shore regions. We assign NEHRP seismic site class ranges based on available Vs30 values. A comparison of results from imagery-based methods to results from traditional geologic-based approaches reveals good overall correspondence. We conclude that image analysis of RS data provides reliable first-order site characterization results in the absence of local data and can be useful to refine detailed site maps with sparse local data. ?? 2011 American Society for Photogrammetry and Remote Sensing.

  1. An automated image processing method for classification of diabetic retinopathy stages from conjunctival microvasculature images

    Science.gov (United States)

    Khansari, Maziyar M.; O'Neill, William; Penn, Richard; Blair, Norman P.; Chau, Felix; Shahidi, Mahnaz

    2017-03-01

    The conjunctiva is a densely vascularized tissue of the eye that provides an opportunity for imaging of human microcirculation. In the current study, automated fine structure analysis of conjunctival microvasculature images was performed to discriminate stages of diabetic retinopathy (DR). The study population consisted of one group of nondiabetic control subjects (NC) and 3 groups of diabetic subjects, with no clinical DR (NDR), non-proliferative DR (NPDR), or proliferative DR (PDR). Ordinary least square regression and Fisher linear discriminant analyses were performed to automatically discriminate images between group pairs of subjects. Human observers who were masked to the grouping of subjects performed image discrimination between group pairs. Over 80% and 70% of images of subjects with clinical and non-clinical DR were correctly discriminated by the automated method, respectively. The discrimination rates of the automated method were higher than human observers. The fine structure analysis of conjunctival microvasculature images provided discrimination of DR stages and can be potentially useful for DR screening and monitoring.

  2. 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

  3. Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

    Science.gov (United States)

    Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

    2015-06-01

    The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

  4. Enhancement of Electroluminescence (EL) image measurements for failure quantification methods

    DEFF Research Database (Denmark)

    Parikh, Harsh; Spataru, Sergiu; Sera, Dezso

    2018-01-01

    Enhanced quality images are necessary for EL image analysis and failure quantification. A method is proposed which determines image quality in terms of more accurate failure detection of solar panels through electroluminescence (EL) imaging technique. The goal of the paper is to determine the most...

  5. 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.

  6. Research of x-ray automatic image mosaic method

    Science.gov (United States)

    Liu, Bin; Chen, Shunan; Guo, Lianpeng; Xu, Wanpeng

    2013-10-01

    Image mosaic has widely applications value in the fields of medical image analysis, and it is a technology that carries on the spatial matching to a series of image which are overlapped with each other, and finally builds a seamless and high quality image which has high resolution and big eyeshot. In this paper, the method of grayscale cutting pseudo-color enhancement was firstly used to complete the mapping transformation from gray to the pseudo-color, and to extract SIFT features from the images. And then by making use of a similar measure of NCC (normalized cross correlation - Normalized cross-correlation), the method of RANSAC (Random Sample Consensus) was used to exclude the pseudofeature points right in order to complete the exact match of feature points. Finally, seamless mosaic and color fusion were completed by using wavelet multi-decomposition. The experiment shows that the method we used can effectively improve the precision and automation of the medical image mosaic, and provide an effective technical approach for automatic medical image mosaic.

  7. Content-based Image Hiding Method for Secure Network Biometric Verification

    Directory of Open Access Journals (Sweden)

    Xiangjiu Che

    2011-08-01

    Full Text Available For secure biometric verification, most existing methods embed biometric information directly into the cover image, but content correlation analysis between the biometric image and the cover image is often ignored. In this paper, we propose a novel biometric image hiding approach based on the content correlation analysis to protect the network-based transmitted image. By using principal component analysis (PCA, the content correlation between the biometric image and the cover image is firstly analyzed. Then based on particle swarm optimization (PSO algorithm, some regions of the cover image are selected to represent the biometric image, in which the cover image can carry partial content of the biometric image. As a result of the correlation analysis, the unrepresented part of the biometric image is embedded into the cover image by using the discrete wavelet transform (DWT. Combined with human visual system (HVS model, this approach makes the hiding result perceptually invisible. The extensive experimental results demonstrate that the proposed hiding approach is robust against some common frequency and geometric attacks; it also provides an effective protection for the secure biometric verification.

  8. 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.

  9. Review methods for image segmentation from computed tomography images

    International Nuclear Information System (INIS)

    Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik; Mahmud, Rozi

    2014-01-01

    Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affect the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan

  10. 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.

  11. 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.

  12. 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.

  13. Bubble structure evaluation method of sponge cake by using image morphology

    Science.gov (United States)

    Kato, Kunihito; Yamamoto, Kazuhiko; Nonaka, Masahiko; Katsuta, Yukiyo; Kasamatsu, Chinatsu

    2007-01-01

    Nowadays, many evaluation methods for food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that have been used for the quality evaluation recently. The goal of our research is structure evaluation of sponge cake by using the image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner, because the depth of field of this type scanner is very shallow. Therefore the bubble region of the surface has low gray scale value, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. The input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

  14. 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.

  15. Method for Assessment of Changes in the Width of Cracks in Cement Composites with Use of Computer Image Processing and Analysis

    Science.gov (United States)

    Tomczak, Kamil; Jakubowski, Jacek; Fiołek, Przemysław

    2017-06-01

    Crack width measurement is an important element of research on the progress of self-healing cement composites. Due to the nature of this research, the method of measuring the width of cracks and their changes over time must meet specific requirements. The article presents a novel method of measuring crack width based on images from a scanner with an optical resolution of 6400 dpi, subject to initial image processing in the ImageJ development environment and further processing and analysis of results. After registering a series of images of the cracks at different times using SIFT conversion (Scale-Invariant Feature Transform), a dense network of line segments is created in all images, intersecting the cracks perpendicular to the local axes. Along these line segments, brightness profiles are extracted, which are the basis for determination of crack width. The distribution and rotation of the line of intersection in a regular layout, automation of transformations, management of images and profiles of brightness, and data analysis to determine the width of cracks and their changes over time are made automatically by own code in the ImageJ and VBA environment. The article describes the method, tests on its properties, sources of measurement uncertainty. It also presents an example of application of the method in research on autogenous self-healing of concrete, specifically the ability to reduce a sample crack width and its full closure within 28 days of the self-healing process.

  16. Improved image alignment method in application to X-ray images and biological images.

    Science.gov (United States)

    Wang, Ching-Wei; Chen, Hsiang-Chou

    2013-08-01

    Alignment of medical images is a vital component of a large number of applications throughout the clinical track of events; not only within clinical diagnostic settings, but prominently so in the area of planning, consummation and evaluation of surgical and radiotherapeutical procedures. However, image registration of medical images is challenging because of variations on data appearance, imaging artifacts and complex data deformation problems. Hence, the aim of this study is to develop a robust image alignment method for medical images. An improved image registration method is proposed, and the method is evaluated with two types of medical data, including biological microscopic tissue images and dental X-ray images and compared with five state-of-the-art image registration techniques. The experimental results show that the presented method consistently performs well on both types of medical images, achieving 88.44 and 88.93% averaged registration accuracies for biological tissue images and X-ray images, respectively, and outperforms the benchmark methods. Based on the Tukey's honestly significant difference test and Fisher's least square difference test tests, the presented method performs significantly better than all existing methods (P ≤ 0.001) for tissue image alignment, and for the X-ray image registration, the proposed method performs significantly better than the two benchmark b-spline approaches (P < 0.001). The software implementation of the presented method and the data used in this study are made publicly available for scientific communities to use (http://www-o.ntust.edu.tw/∼cweiwang/ImprovedImageRegistration/). cweiwang@mail.ntust.edu.tw.

  17. Physical foundations of image quality in nuclear medicine. Methods for its evaluation

    International Nuclear Information System (INIS)

    Perez Diaz, Marlen; Diaz Rizo, Oscar

    2007-01-01

    The present paper describes the main physical factors which characterize image quality in Nuclear Medicine from the physical and mathematical point of view. A conceptual description of how image system (gamma camera) degrades the information emitted by the object is also presented. A critical review of some qualitative and quantitative methods for grading image quality, collateral to equipment quality control, follows this material. Among these methods we present the ROC analysis, Clustering Techniques and Discriminant Analysis. As a part of the two last ones, we also analyze the main factors which determine image quality and how they produce changes in the quantitative physical variables measured on the images. A comparison among the methods is also presented, remarking their utility to check image quality, as well as the main advantages and disadvantages of each one (au)

  18. Research on image complexity evaluation method based on color information

    Science.gov (United States)

    Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

    2017-11-01

    In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

  19. Imaging systems and methods for obtaining and using biometric information

    Science.gov (United States)

    McMakin, Douglas L [Richland, WA; Kennedy, Mike O [Richland, WA

    2010-11-30

    Disclosed herein are exemplary embodiments of imaging systems and methods of using such systems. In one exemplary embodiment, one or more direct images of the body of a clothed subject are received, and a motion signature is determined from the one or more images. In this embodiment, the one or more images show movement of the body of the subject over time, and the motion signature is associated with the movement of the subject's body. In certain implementations, the subject can be identified based at least in part on the motion signature. Imaging systems for performing any of the disclosed methods are also disclosed herein. Furthermore, the disclosed imaging, rendering, and analysis methods can be implemented, at least in part, as one or more computer-readable media comprising computer-executable instructions for causing a computer to perform the respective methods.

  20. Performance Analysis and Experimental Validation of the Direct Strain Imaging Method

    Science.gov (United States)

    Athanasios Iliopoulos; John G. Michopoulos; John C. Hermanson

    2013-01-01

    Direct Strain Imaging accomplishes full field measurement of the strain tensor on the surface of a deforming body, by utilizing arbitrarily oriented engineering strain measurements originating from digital imaging. In this paper an evaluation of the method’s performance with respect to its operating parameter space is presented along with a preliminary...

  1. Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method.

    Science.gov (United States)

    Du, Lei; Huang, Heng; Yan, Jingwen; Kim, Sungeun; Risacher, Shannon L; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

    2016-05-15

    Structured sparse canonical correlation analysis (SCCA) models have been used to identify imaging genetic associations. These models either use group lasso or graph-guided fused lasso to conduct feature selection and feature grouping simultaneously. The group lasso based methods require prior knowledge to define the groups, which limits the capability when prior knowledge is incomplete or unavailable. The graph-guided methods overcome this drawback by using the sample correlation to define the constraint. However, they are sensitive to the sign of the sample correlation, which could introduce undesirable bias if the sign is wrongly estimated. We introduce a novel SCCA model with a new penalty, and develop an efficient optimization algorithm. Our method has a strong upper bound for the grouping effect for both positively and negatively correlated features. We show that our method performs better than or equally to three competing SCCA models on both synthetic and real data. In particular, our method identifies stronger canonical correlations and better canonical loading patterns, showing its promise for revealing interesting imaging genetic associations. The Matlab code and sample data are freely available at http://www.iu.edu/∼shenlab/tools/angscca/ shenli@iu.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.

  2. A new automated assessment method for contrast-detail images by applying support vector machine and its robustness to nonlinear image processing.

    Science.gov (United States)

    Takei, Takaaki; Ikeda, Mitsuru; Imai, Kuniharu; Yamauchi-Kawaura, Chiyo; Kato, Katsuhiko; Isoda, Haruo

    2013-09-01

    The automated contrast-detail (C-D) analysis methods developed so-far cannot be expected to work well on images processed with nonlinear methods, such as noise reduction methods. Therefore, we have devised a new automated C-D analysis method by applying support vector machine (SVM), and tested for its robustness to nonlinear image processing. We acquired the CDRAD (a commercially available C-D test object) images at a tube voltage of 120 kV and a milliampere-second product (mAs) of 0.5-5.0. A partial diffusion equation based technique was used as noise reduction method. Three radiologists and three university students participated in the observer performance study. The training data for our SVM method was the classification data scored by the one radiologist for the CDRAD images acquired at 1.6 and 3.2 mAs and their noise-reduced images. We also compared the performance of our SVM method with the CDRAD Analyser algorithm. The mean C-D diagrams (that is a plot of the mean of the smallest visible hole diameter vs. hole depth) obtained from our devised SVM method agreed well with the ones averaged across the six human observers for both original and noise-reduced CDRAD images, whereas the mean C-D diagrams from the CDRAD Analyser algorithm disagreed with the ones from the human observers for both original and noise-reduced CDRAD images. In conclusion, our proposed SVM method for C-D analysis will work well for the images processed with the non-linear noise reduction method as well as for the original radiographic images.

  3. W-transform method for feature-oriented multiresolution image retrieval

    Energy Technology Data Exchange (ETDEWEB)

    Kwong, M.K.; Lin, B. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-07-01

    Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

  4. 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...

  5. Cluster analysis as a method for determining size ranges for spinal implants: disc lumbar replacement prosthesis dimensions from magnetic resonance images.

    Science.gov (United States)

    Lei, Dang; Holder, Roger L; Smith, Francis W; Wardlaw, Douglas; Hukins, David W L

    2006-12-01

    Statistical analysis of clinical radiologic data. To develop an objective method for finding the number of sizes for a lumbar disc replacement. Cluster analysis is a well-established technique for sorting observations into clusters so that the "similarity level" is maximal if they belong to the same cluster and minimal otherwise. Magnetic resonance scans from 69 patients, with no abnormal discs, yielded 206 sagittal and transverse images of 206 discs (levels L3-L4-L5-S1). Anteroposterior and lateral dimensions were measured from vertebral margins on transverse images; disc heights were measured from sagittal images. Hierarchical cluster analysis was performed to determine the number of clusters followed by nonhierarchical (K-means) cluster analysis. Discriminant analysis was used to determine how well the clusters could be used to classify an observation. The most successful method of clustering the data involved the following parameters: anteroposterior dimension; lateral dimension (both were the mean of results from the superior and inferior margins of a vertebral body, measured on transverse images); and maximum disc height (from a midsagittal image). These were grouped into 7 clusters so that a discriminant analysis was capable of correctly classifying 97.1% of the observations. The mean and standard deviations for the parameter values in each cluster were determined. Cluster analysis has been successfully used to find the dimensions of the minimum number of prosthesis sizes required to replace L3-L4 to L5-S1 discs; the range of sizes would enable them to be used at higher lumbar levels in some patients.

  6. 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.

  7. SU-F-J-177: A Novel Image Analysis Technique (center Pixel Method) to Quantify End-To-End Tests

    Energy Technology Data Exchange (ETDEWEB)

    Wen, N; Chetty, I [Henry Ford Health System, Detroit, MI (United States); Snyder, K [Henry Ford Hospital System, Detroit, MI (United States); Scheib, S [Varian Medical System, Barton (Switzerland); Qin, Y; Li, H [Henry Ford Health System, Detroit, Michigan (United States)

    2016-06-15

    Purpose: To implement a novel image analysis technique, “center pixel method”, to quantify end-to-end tests accuracy of a frameless, image guided stereotactic radiosurgery system. Methods: The localization accuracy was determined by delivering radiation to an end-to-end prototype phantom. The phantom was scanned with 0.8 mm slice thickness. The treatment isocenter was placed at the center of the phantom. In the treatment room, CBCT images of the phantom (kVp=77, mAs=1022, slice thickness 1 mm) were acquired to register to the reference CT images. 6D couch correction were applied based on the registration results. Electronic Portal Imaging Device (EPID)-based Winston Lutz (WL) tests were performed to quantify the errors of the targeting accuracy of the system at 15 combinations of gantry, collimator and couch positions. The images were analyzed using two different methods. a) The classic method. The deviation was calculated by measuring the radial distance between the center of the central BB and the full width at half maximum of the radiation field. b) The center pixel method. Since the imager projection offset from the treatment isocenter was known from the IsoCal calibration, the deviation was determined between the center of the BB and the central pixel of the imager panel. Results: Using the automatic registration method to localize the phantom and the classic method of measuring the deviation of the BB center, the mean and standard deviation of the radial distance was 0.44 ± 0.25, 0.47 ± 0.26, and 0.43 ± 0.13 mm for the jaw, MLC and cone defined field sizes respectively. When the center pixel method was used, the mean and standard deviation was 0.32 ± 0.18, 0.32 ± 0.17, and 0.32 ± 0.19 mm respectively. Conclusion: Our results demonstrated that the center pixel method accurately analyzes the WL images to evaluate the targeting accuracy of the radiosurgery system. The work was supported by a Research Scholar Grant, RSG-15-137-01-CCE from the American

  8. 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.

  9. Computational modeling of objects presented in images fundamentals, methods and applications

    CERN Document Server

    Iacoviello, Daniela; Jorge, Renato; Tavares, João

    2014-01-01

    This book contains extended versions of selected papers from the 3rd edition of the International Symposium CompIMAGE. These contributions include cover methods of signal and image processing and analysis to tackle problems found in medicine, material science, surveillance, biometric, robotics, defence, satellite data, traffic analysis and architecture, image segmentation, 2D and 3D reconstruction, data acquisition, interpolation and registration, data visualization, motion and deformation analysis, and 3D vision

  10. 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)

  11. 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

  12. 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.

  13. A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

    Science.gov (United States)

    Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene

    2017-11-01

    Parametric response map (PRM) analysis of functional imaging has been shown to be an effective tool for early prediction of cancer treatment outcomes and may also be well-suited toward guiding personalized adaptive radiotherapy (RT) strategies such as sub-volume boosting. However, the PRM method was primarily designed for analysis of longitudinally acquired pairs of single-parameter image data. The purpose of this study was to demonstrate the feasibility of a generalized parametric response map analysis framework, which enables analysis of multi-parametric data while maintaining the key advantages of the original PRM method. MRI-derived apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps acquired at 1 and 3-months post-RT for 19 patients with high-grade glioma were used to demonstrate the algorithm. Images were first co-registered and then standardized using normal tissue image intensity values. Tumor voxels were then plotted in a four-dimensional Cartesian space with coordinate values equal to a voxel's image intensity in each of the image volumes and an origin defined as the multi-parametric mean of normal tissue image intensity values. Voxel positions were orthogonally projected onto a line defined by the origin and a pre-determined response vector. The voxels are subsequently classified as positive, negative or nil, according to whether projected positions along the response vector exceeded a threshold distance from the origin. The response vector was selected by identifying the direction in which the standard deviation of tumor image intensity values was maximally different between responding and non-responding patients within a training dataset. Voxel classifications were visualized via familiar three-class response maps and then the fraction of tumor voxels associated with each of the classes was investigated for predictive utility analogous to the original PRM method. Independent PRM and MPRM analyses of the contrast

  14. System and method for image reconstruction, analysis, and/or de-noising

    KAUST Repository

    Laleg-Kirati, Taous-Meriem; Kaisserli, Zineb

    2015-01-01

    A method and system can analyze, reconstruct, and/or denoise an image. The method and system can include interpreting a signal as a potential of a Schrödinger operator, decomposing the signal into squared eigenfunctions, reducing a design parameter

  15. Optoelectronic imaging of speckle using image processing method

    Science.gov (United States)

    Wang, Jinjiang; Wang, Pengfei

    2018-01-01

    A detailed image processing of laser speckle interferometry is proposed as an example for the course of postgraduate student. Several image processing methods were used together for dealing with optoelectronic imaging system, such as the partial differential equations (PDEs) are used to reduce the effect of noise, the thresholding segmentation also based on heat equation with PDEs, the central line is extracted based on image skeleton, and the branch is removed automatically, the phase level is calculated by spline interpolation method, and the fringe phase can be unwrapped. Finally, the imaging processing method was used to automatically measure the bubble in rubber with negative pressure which could be used in the tire detection.

  16. Soft tissue tumors - imaging methods

    International Nuclear Information System (INIS)

    Arlart, I.P.

    1985-01-01

    Soft Tissue Tumors - Imaging Methods: Imaging methods play an important diagnostic role in soft tissue tumors concerning a preoperative evaluation of localization, size, topographic relationship, dignity, and metastatic disease. The present paper gives an overview about diagnostic methods available today such as ultrasound, thermography, roentgenographic plain films and xeroradiography, radionuclide methods, computed tomography, lymphography, angiography, and magnetic resonance imaging. Besides sonography particularly computed tomography has the most important diagnostic value in soft tissue tumors. The application of a recently developed method, the magnetic resonance imaging, cannot yet be assessed in its significance. (orig.) [de

  17. Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

    Science.gov (United States)

    De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

    2017-06-01

    A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods.

    Science.gov (United States)

    Boushey, C J; Spoden, M; Zhu, F M; Delp, E J; Kerr, D A

    2017-08-01

    For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

  19. 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.

  20. A new automated assessment method for contrast–detail images by applying support vector machine and its robustness to nonlinear image processing

    International Nuclear Information System (INIS)

    Takei, Takaaki; Ikeda, Mitsuru; Imai, Kumiharu; Yamauchi-Kawaura, Chiyo; Kato, Katsuhiko; Isoda, Haruo

    2013-01-01

    The automated contrast–detail (C–D) analysis methods developed so-far cannot be expected to work well on images processed with nonlinear methods, such as noise reduction methods. Therefore, we have devised a new automated C–D analysis method by applying support vector machine (SVM), and tested for its robustness to nonlinear image processing. We acquired the CDRAD (a commercially available C–D test object) images at a tube voltage of 120 kV and a milliampere-second product (mAs) of 0.5–5.0. A partial diffusion equation based technique was used as noise reduction method. Three radiologists and three university students participated in the observer performance study. The training data for our SVM method was the classification data scored by the one radiologist for the CDRAD images acquired at 1.6 and 3.2 mAs and their noise-reduced images. We also compared the performance of our SVM method with the CDRAD Analyser algorithm. The mean C–D diagrams (that is a plot of the mean of the smallest visible hole diameter vs. hole depth) obtained from our devised SVM method agreed well with the ones averaged across the six human observers for both original and noise-reduced CDRAD images, whereas the mean C–D diagrams from the CDRAD Analyser algorithm disagreed with the ones from the human observers for both original and noise-reduced CDRAD images. In conclusion, our proposed SVM method for C–D analysis will work well for the images processed with the non-linear noise reduction method as well as for the original radiographic images.

  1. Rapid flow imaging method

    International Nuclear Information System (INIS)

    Pelc, N.J.; Spritzer, C.E.; Lee, J.N.

    1988-01-01

    A rapid, phase-contrast, MR imaging method of imaging flow has been implemented. The method, called VIGRE (velocity imaging with gradient recalled echoes), consists of two interleaved, narrow flip angle, gradient-recalled acquisitions. One is flow compensated while the second has a specified flow encoding (both peak velocity and direction) that causes signals to contain additional phase in proportion to velocity in the specified direction. Complex image data from the first acquisition are used as a phase reference for the second, yielding immunity from phase accumulation due to causes other than motion. Images with pixel values equal to MΔΘ where M is the magnitude of the flow compensated image and ΔΘ is the phase difference at the pixel, are produced. The magnitude weighting provides additional vessel contrast, suppresses background noise, maintains the flow direction information, and still allows quantitative data to be retrieved. The method has been validated with phantoms and is undergoing initial clinical evaluation. Early results are extremely encouraging

  2. 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.

  3. Feed particle size evaluation: conventional approach versus digital holography based image analysis

    Directory of Open Access Journals (Sweden)

    Vittorio Dell’Orto

    2010-01-01

    Full Text Available The aim of this study was to evaluate the application of image analysis approach based on digital holography in defining particle size in comparison with the sieve shaker method (sieving method as reference method. For this purpose ground corn meal was analyzed by a sieve shaker Retsch VS 1000 and by image analysis approach based on digital holography. Particle size from digital holography were compared with results obtained by screen (sieving analysis for each of size classes by a cumulative distribution plot. Comparison between particle size values obtained by sieving method and image analysis indicated that values were comparable in term of particle size information, introducing a potential application for digital holography and image analysis in feed industry.

  4. FFT-enhanced IHS transform method for fusing high-resolution satellite images

    Science.gov (United States)

    Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

    2007-01-01

    Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

  5. A method of image improvement in three-dimensional imaging

    International Nuclear Information System (INIS)

    Suto, Yasuzo; Huang, Tewen; Furuhata, Kentaro; Uchino, Masafumi.

    1988-01-01

    In general, image interpolation is required when the surface configurations of such structures as bones and organs are three-dimensionally constructed from the multi-sliced images obtained by CT. Image interpolation is a processing method whereby an artificial image is inserted between two adjacent slices to make spatial resolution equal to slice resolution in appearance. Such image interpolation makes it possible to increase the image quality of the constructed three-dimensional image. In our newly-developed algorithm, we have converted the presently and subsequently sliced images to distance images, and generated the interpolation images from these two distance images. As a result, compared with the previous method, three-dimensional images with better image quality have been constructed. (author)

  6. An instructional guide for leaf color analysis using digital imaging software

    Science.gov (United States)

    Paula F. Murakami; Michelle R. Turner; Abby K. van den Berg; Paul G. Schaberg

    2005-01-01

    Digital color analysis has become an increasingly popular and cost-effective method utilized by resource managers and scientists for evaluating foliar nutrition and health in response to environmental stresses. We developed and tested a new method of digital image analysis that uses Scion Image or NIH image public domain software to quantify leaf color. This...

  7. Image enhancement of x-ray microscope using frequency spectrum analysis

    International Nuclear Information System (INIS)

    Li Wenjie; Chen Jie; Tian Jinping; Zhang Xiaobo; Liu Gang; Tian Yangchao; Liu Yijin; Wu Ziyu

    2009-01-01

    We demonstrate a new method for x-ray microscope image enhancement using frequency spectrum analysis. Fine sample characteristics are well enhanced with homogeneous visibility and better contrast from single image. This method is easy to implement and really helps to improve the quality of image taken by our imaging system.

  8. Image enhancement of x-ray microscope using frequency spectrum analysis

    Energy Technology Data Exchange (ETDEWEB)

    Li Wenjie; Chen Jie; Tian Jinping; Zhang Xiaobo; Liu Gang; Tian Yangchao [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui 230029 (China); Liu Yijin; Wu Ziyu, E-mail: wuzy@ihep.ac.c, E-mail: ychtian@ustc.edu.c [Institute of High Energy Physics, Chinese Academy of Science, Beijing 100049 (China)

    2009-09-01

    We demonstrate a new method for x-ray microscope image enhancement using frequency spectrum analysis. Fine sample characteristics are well enhanced with homogeneous visibility and better contrast from single image. This method is easy to implement and really helps to improve the quality of image taken by our imaging system.

  9. MO-F-BRA-04: Voxel-Based Statistical Analysis of Deformable Image Registration Error via a Finite Element Method.

    Science.gov (United States)

    Li, S; Lu, M; Kim, J; Glide-Hurst, C; Chetty, I; Zhong, H

    2012-06-01

    Purpose Clinical implementation of adaptive treatment planning is limited by the lack of quantitative tools to assess deformable image registration errors (R-ERR). The purpose of this study was to develop a method, using finite element modeling (FEM), to estimate registration errors based on mechanical changes resulting from them. Methods An experimental platform to quantify the correlation between registration errors and their mechanical consequences was developed as follows: diaphragm deformation was simulated on the CT images in patients with lung cancer using a finite element method (FEM). The simulated displacement vector fields (F-DVF) were used to warp each CT image to generate a FEM image. B-Spline based (Elastix) registrations were performed from reference to FEM images to generate a registration DVF (R-DVF). The F- DVF was subtracted from R-DVF. The magnitude of the difference vector was defined as the registration error, which is a consequence of mechanically unbalanced energy (UE), computed using 'in-house-developed' FEM software. A nonlinear regression model was used based on imaging voxel data and the analysis considered clustered voxel data within images. Results A regression model analysis showed that UE was significantly correlated with registration error, DVF and the product of registration error and DVF respectively with R̂2=0.73 (R=0.854). The association was verified independently using 40 tracked landmarks. A linear function between the means of UE values and R- DVF*R-ERR has been established. The mean registration error (N=8) was 0.9 mm. 85.4% of voxels fit this model within one standard deviation. Conclusions An encouraging relationship between UE and registration error has been found. These experimental results suggest the feasibility of UE as a valuable tool for evaluating registration errors, thus supporting 4D and adaptive radiotherapy. The research was supported by NIH/NCI R01CA140341. © 2012 American Association of Physicists in

  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. 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.)

  12. 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

  13. 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

  14. Applying quantitative benefit-risk analysis to aid regulatory decision making in diagnostic imaging: methods, challenges, and opportunities.

    Science.gov (United States)

    Agapova, Maria; Devine, Emily Beth; Bresnahan, Brian W; Higashi, Mitchell K; Garrison, Louis P

    2014-09-01

    Health agencies making regulatory marketing-authorization decisions use qualitative and quantitative approaches to assess expected benefits and expected risks associated with medical interventions. There is, however, no universal standard approach that regulatory agencies consistently use to conduct benefit-risk assessment (BRA) for pharmaceuticals or medical devices, including for imaging technologies. Economics, health services research, and health outcomes research use quantitative approaches to elicit preferences of stakeholders, identify priorities, and model health conditions and health intervention effects. Challenges to BRA in medical devices are outlined, highlighting additional barriers in radiology. Three quantitative methods--multi-criteria decision analysis, health outcomes modeling and stated-choice survey--are assessed using criteria that are important in balancing benefits and risks of medical devices and imaging technologies. To be useful in regulatory BRA, quantitative methods need to: aggregate multiple benefits and risks, incorporate qualitative considerations, account for uncertainty, and make clear whose preferences/priorities are being used. Each quantitative method performs differently across these criteria and little is known about how BRA estimates and conclusions vary by approach. While no specific quantitative method is likely to be the strongest in all of the important areas, quantitative methods may have a place in BRA of medical devices and radiology. Quantitative BRA approaches have been more widely applied in medicines, with fewer BRAs in devices. Despite substantial differences in characteristics of pharmaceuticals and devices, BRA methods may be as applicable to medical devices and imaging technologies as they are to pharmaceuticals. Further research to guide the development and selection of quantitative BRA methods for medical devices and imaging technologies is needed. Copyright © 2014 AUR. Published by Elsevier Inc. All rights

  15. Human body region enhancement method based on Kinect infrared imaging

    Science.gov (United States)

    Yang, Lei; Fan, Yubo; Song, Xiaowei; Cai, Wenjing

    2016-10-01

    To effectively improve the low contrast of human body region in the infrared images, a combing method of several enhancement methods is utilized to enhance the human body region. Firstly, for the infrared images acquired by Kinect, in order to improve the overall contrast of the infrared images, an Optimal Contrast-Tone Mapping (OCTM) method with multi-iterations is applied to balance the contrast of low-luminosity infrared images. Secondly, to enhance the human body region better, a Level Set algorithm is employed to improve the contour edges of human body region. Finally, to further improve the human body region in infrared images, Laplacian Pyramid decomposition is adopted to enhance the contour-improved human body region. Meanwhile, the background area without human body region is processed by bilateral filtering to improve the overall effect. With theoretical analysis and experimental verification, the results show that the proposed method could effectively enhance the human body region of such infrared images.

  16. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

    Science.gov (United States)

    Osipov, Gennady

    2013-04-01

    We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode

  17. 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.

  18. Recent advances in computational methods and clinical applications for spine imaging

    CERN Document Server

    Glocker, Ben; Klinder, Tobias; Li, Shuo

    2015-01-01

    This book contains the full papers presented at the MICCAI 2014 workshop on Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together scientists and clinicians in the field of computational spine imaging. The chapters included in this book present and discuss the new advances and challenges in these fields, using several methods and techniques in order to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modeling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis. The book also includes papers and reports from the first challenge on vertebra segmentation held at the workshop.

  19. Colonic polyp detection method from 3D abdominal CT images based on local intensity analysis

    International Nuclear Information System (INIS)

    Oda, M.; Nakada, Y.; Kitasaka, T.; Mori, K.; Suenaga, Y.; Takayama, T.; Takabatake, H.; Mori, M.; Natori, H.; Nawano, S.

    2007-01-01

    This paper presents a detection method of colonic polyps from 3D abdominal CT images based on local intensity analysis. Recently, virtual colonoscopy (VC) has widely received attention as a new colon diagnostic method. VC is considered as a less-invasive inspection method which reduces patient load. However, since the colon has many haustra and its shape is long and convoluted, a physician has to change the viewpoint and the viewing direction of the virtual camera of VC many times while diagnosis. Additionally, there is a risk to overlook lesions existing in blinded areas caused by haustra. This paper proposes an automated colonic polyp detection method from 3D abdominal CT images. Colonic polyps are located on the colonic wall. Their CT values are higher than those of colonic lumen regions and lower than those of fecal materials tagged by an X-ray opaque contrast agent. CT values inside polyps which exist outside the tagged fecal materials tend to gradually increase from outward to inward (blob-like structure). CT values inside polyps that exist inside the tagged fecal materials tend to gradually decrease from outward to inward (inv-blob-like structure). We employ the blob and the inv-blob structure enhancement filters based on the eigenvalues of the Hessian matrix to detect polyps using intensity characteristic of polyps. Connected components with low output values of the enhancement filter are eliminated in false positive reduction process. Small connected components are also eliminated. We applied the proposed method to 44 cases of abdominal CT images. Sensitivity for polyps of 6 mm or larger was 80% with 4.7 false positives per case. (orig.)

  20. Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

    Directory of Open Access Journals (Sweden)

    Amy M. Ashman

    2017-01-01

    Full Text Available Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete, median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05, and for micronutrients both including (r = 0.47–0.94, all p < 0.05 and excluding (r = 0.40–0.85, all p < 0.05 supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women.

  1. 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

  2. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  3. Level set method for image segmentation based on moment competition

    Science.gov (United States)

    Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

    2015-05-01

    We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

  4. #fitspo on Instagram: A mixed-methods approach using Netlytic and photo analysis, uncovering the online discussion and author/image characteristics.

    Science.gov (United States)

    Santarossa, Sara; Coyne, Paige; Lisinski, Carly; Woodruff, Sarah J

    2016-11-01

    The #fitspo 'tag' is a recent trend on Instagram, which is used on posts to motivate others towards a healthy lifestyle through exercise/eating habits. This study used a mixed-methods approach consisting of text and network analysis via the Netlytic program ( N = 10,000 #fitspo posts), and content analysis of #fitspo images ( N = 122) was used to examine author and image characteristics. Results suggest that #fitspo posts may motivate through appearance-mediated themes, as the largest content categories (based on the associated text) were 'feeling good' and 'appearance'. Furthermore, #fitspo posts may create peer influence/support as personal (opposed to non-personal) accounts were associated with higher popularity of images (i.e. number of likes/followers). Finally, most images contained posed individuals with some degree of objectification.

  5. Critical analysis of imaging methods for the detection and diagnosis of breast cancer

    International Nuclear Information System (INIS)

    Mendonca, Maria Helena Siqueira

    1999-01-01

    Breast cancer is a significant health problem. Early diagnosis of the disease is mandatory to increase the effectiveness of the treatment, to augment the chances of cure and to permit conservative surgery. The use of imaging methods is essential in the early diagnosis of the disease. Imaging methods advantages and disadvantages, use and limitations, specificity and sensitivity are presented and discussed. (author)

  6. 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.

  7. Advanced methods for image registration applied to JET videos

    Energy Technology Data Exchange (ETDEWEB)

    Craciunescu, Teddy, E-mail: teddy.craciunescu@jet.uk [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Murari, Andrea [Consorzio RFX, Associazione EURATOM-ENEA per la Fusione, Padova (Italy); Gelfusa, Michela [Associazione EURATOM-ENEA – University of Rome “Tor Vergata”, Roma (Italy); Tiseanu, Ion; Zoita, Vasile [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Arnoux, Gilles [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon (United Kingdom)

    2015-10-15

    Graphical abstract: - Highlights: • Development of an image registration method for JET IR and fast visible cameras. • Method based on SIFT descriptors and coherent point drift points set registration technique. • Method able to deal with extremely noisy images and very low luminosity images. • Computation time compatible with the inter-shot analysis. - Abstract: The last years have witnessed a significant increase in the use of digital cameras on JET. They are routinely applied for imaging in the IR and visible spectral regions. One of the main technical difficulties in interpreting the data of camera based diagnostics is the presence of movements of the field of view. Small movements occur due to machine shaking during normal pulses while large ones may arise during disruptions. Some cameras show a correlation of image movement with change of magnetic field strength. For deriving unaltered information from the videos and for allowing correct interpretation an image registration method, based on highly distinctive scale invariant feature transform (SIFT) descriptors and on the coherent point drift (CPD) points set registration technique, has been developed. The algorithm incorporates a complex procedure for rejecting outliers. The method has been applied for vibrations correction to videos collected by the JET wide angle infrared camera and for the correction of spurious rotations in the case of the JET fast visible camera (which is equipped with an image intensifier). The method has proved to be able to deal with the images provided by this camera frequently characterized by low contrast and a high level of blurring and noise.

  8. 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.

  9. 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.

  10. 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.

  11. MR imaging of articular cartilage in the ankle: comparison of available imaging sequences and methods of measurement in cadavers

    Energy Technology Data Exchange (ETDEWEB)

    Tan, T.C.F. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States)]|[Department of Radiology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan (Taiwan, Province of China); Wilcox, D.M. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States); Frank, L. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States); Shih, C. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States)]|[Department of Radiology, Veterans General Hospital-Taipei (Taiwan, Province of China); Trudell, D.J. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States); Sartoris, D.J. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States); Resnick, D. [Department of Radiology, Veterans Administrative Medical Center, San Diego, CA (United States)]|[University of California Medical Center, San Diego, CA (United States)

    1996-11-01

    Objective. To assess hyaline cartilage of cadaveric ankles using different magnetic resonance (MR) imaging techniques and various methods of measurement. Design and patients. Cartilage thicknesses of the talus and tibia were measured in ten cadaveric ankles by naked eye and by digitized image analysis from MR images of fat-suppressed T1-weighted gradient recalled (FS-SPGR), sequences and pulsed transfer saturation sequences with (FS-STS) and without fat-suppression (STS); these measurements were compared with those derived from direct inspection of cadaveric sections. The accuracy and precision errors were evaluated statistically for each imaging technique as well as measuring method. Contrast-to-noise ratios of cartilage versus joint fluid and marrow were compared for each of the imaging sequences. Results. Statistically, measurements from FS-SPGR images were associated with the smallest estimation error. Precision error of measurements derived from digitized image analysis was found to be smaller than that derived from naked eye measurements. Cartilage thickness measurements in images from STS and FS-STS sequences revealed larger errors in both accuracy and precision. Interobserver variance was larger in naked eye assessment of the cartilage. Contrast-to-noise ratio of cartilage versus joint fluid and marrow was higher with FS-SPGR than with FS-STS or STS sequences. Conclusion. Of the sequences and measurement techniques studied, the FS-SPGR sequence combined with the use of digitized image analysis provides the most accurate method for the assessment of ankle hyaline cartilage. (orig.). With 3 figs., 2 tabs.

  12. MR imaging of articular cartilage in the ankle: comparison of available imaging sequences and methods of measurement in cadavers

    International Nuclear Information System (INIS)

    Tan, T.C.F.; Wilcox, D.M.; Frank, L.; Shih, C.; Trudell, D.J.; Sartoris, D.J.; Resnick, D.

    1996-01-01

    Objective. To assess hyaline cartilage of cadaveric ankles using different magnetic resonance (MR) imaging techniques and various methods of measurement. Design and patients. Cartilage thicknesses of the talus and tibia were measured in ten cadaveric ankles by naked eye and by digitized image analysis from MR images of fat-suppressed T1-weighted gradient recalled (FS-SPGR), sequences and pulsed transfer saturation sequences with (FS-STS) and without fat-suppression (STS); these measurements were compared with those derived from direct inspection of cadaveric sections. The accuracy and precision errors were evaluated statistically for each imaging technique as well as measuring method. Contrast-to-noise ratios of cartilage versus joint fluid and marrow were compared for each of the imaging sequences. Results. Statistically, measurements from FS-SPGR images were associated with the smallest estimation error. Precision error of measurements derived from digitized image analysis was found to be smaller than that derived from naked eye measurements. Cartilage thickness measurements in images from STS and FS-STS sequences revealed larger errors in both accuracy and precision. Interobserver variance was larger in naked eye assessment of the cartilage. Contrast-to-noise ratio of cartilage versus joint fluid and marrow was higher with FS-SPGR than with FS-STS or STS sequences. Conclusion. Of the sequences and measurement techniques studied, the FS-SPGR sequence combined with the use of digitized image analysis provides the most accurate method for the assessment of ankle hyaline cartilage. (orig.). With 3 figs., 2 tabs

  13. Digital images segmentation: a state of art of the different methods ...

    African Journals Online (AJOL)

    An image is a planar representation of a scene or a 3 D object. The primary information associated to each point of the image is transcribed in grey level or in colour. Image analysis is the set of methods which permits the extraction of pertinent information from the image according to the concerned application, to treat them ...

  14. Methods for modeling and quantification in functional imaging by positron emissions tomography and magnetic resonance imaging

    International Nuclear Information System (INIS)

    Costes, Nicolas

    2017-01-01

    This report presents experiences and researches in the field of in vivo medical imaging by positron emission tomography (PET) and magnetic resonance imaging (MRI). In particular, advances in terms of reconstruction, quantification and modeling in PET are described. The validation of processing and analysis methods is supported by the creation of data by simulation of the imaging process in PET. The recent advances of combined PET/MRI clinical cameras, allowing simultaneous acquisition of molecular/metabolic PET information, and functional/structural MRI information opens the door to unique methodological innovations, exploiting spatial alignment and simultaneity of the PET and MRI signals. It will lead to an increase in accuracy and sensitivity in the measurement of biological phenomena. In this context, the developed projects address new methodological issues related to quantification, and to the respective contributions of MRI or PET information for a reciprocal improvement of the signals of the two modalities. They open perspectives for combined analysis of the two imaging techniques, allowing optimal use of synchronous, anatomical, molecular and functional information for brain imaging. These innovative concepts, as well as data correction and analysis methods, will be easily translated into other areas of investigation using combined PET/MRI. (author) [fr

  15. CALIPSO: an interactive image analysis software package for desktop PACS workstations

    Science.gov (United States)

    Ratib, Osman M.; Huang, H. K.

    1990-07-01

    The purpose of this project is to develop a low cost workstation for quantitative analysis of multimodality images using a Macintosh II personal computer. In the current configuration the Macintosh operates as a stand alone workstation where images are imported either from a central PACS server through a standard Ethernet network or recorded through video digitizer board. The CALIPSO software developed contains a large variety ofbasic image display and manipulation tools. We focused our effort however on the design and implementation ofquantitative analysis methods that can be applied to images from different imaging modalities. Analysis modules currently implemented include geometric and densitometric volumes and ejection fraction calculation from radionuclide and cine-angiograms Fourier analysis ofcardiac wall motion vascular stenosis measurement color coded parametric display of regional flow distribution from dynamic coronary angiograms automatic analysis ofmyocardial distribution ofradiolabelled tracers from tomoscintigraphic images. Several of these analysis tools were selected because they use similar color coded andparametric display methods to communicate quantitative data extracted from the images. 1. Rationale and objectives of the project Developments of Picture Archiving and Communication Systems (PACS) in clinical environment allow physicians and radiologists to assess radiographic images directly through imaging workstations (''). This convenient access to the images is often limited by the number of workstations available due in part to their high cost. There is also an increasing need for quantitative analysis ofthe images. During thepast decade

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

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

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

  17. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  18. Quantitative Methods for Molecular Diagnostic and Therapeutic Imaging

    OpenAIRE

    Li, Quanzheng

    2013-01-01

    This theme issue provides an overview on the basic quantitative methods, an in-depth discussion on the cutting-edge quantitative analysis approaches as well as their applications for both static and dynamic molecular diagnostic and therapeutic imaging.

  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. A method for analysis of lipid vesicle domain structure from confocal image data

    DEFF Research Database (Denmark)

    Husen, Peter Rasmussen; Fidorra, Matthias; Hartel, Steffen

    2012-01-01

    Quantitative characterization of the lateral structure of curved membranes based on fluorescence microscopy requires knowledge of the fluorophore distribution on the surface. We present an image analysis approach for extraction of the fluorophore distribution on a spherical lipid vesicle from...... confocal imaging stacks. The technique involves projection of volumetric image data onto a triangulated surface mesh representation of the membrane, correction of photoselection effects and global motion of the vesicle during image acquisition and segmentation of the surface into domains using histograms...

  1. 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...

  2. 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.

  3. Critical analysis of the images methods in detection and diagnosis in breast cancer

    International Nuclear Information System (INIS)

    Mendonca, Maria H.S.

    1995-01-01

    The female breast cancer is a relevant health issue among female population, due its incidence and remarkable effects in the biological, psychological and social levels. Its early diagnosis is important because it allows more effective treatments and enhances changes of cure, even allowing conservative surgical procedures. To make this possible it is essential the periodic breast imaging exams. The available imaging methods to date are: mammography, ultrasonography, thermography, nuclear medicine, computed tomography and MRI. All these methods have their advantages and disadvantages, applications and limitations and some are even in experimental stages. These methods must exercised in association to become more effective. Mammography is still, beyond and doubt the elected breast exam. even though imperfect. It must be performed repeatedly at periodic intervals depending upon the intrinsic conditions of the patient. The other methods complement the mammographic findings, clearing some of them. In this paper, the imaging methods available in our environmental for detected diagnosis of the early breast cancer are analyzed with emphasis in mammography and ultrasonography. Their advantages, disadvantages, indications and limitations are discussed. (author)

  4. 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...

  5. MEASUREMENTS OF STRAIN FIELDS DUE TO NANOSCALE PRECIPITATES USING THE PHASE IMAGE METHOD

    Directory of Open Access Journals (Sweden)

    Patricia Donnadieu

    2011-05-01

    Full Text Available Owing the phase image method (Hytch, 1998, strain fields can be derived from HREM images. The method is here applied to the nanoscale precipitates responsible for hardening in Aluminum alloys. Since the method is a very sensitive one, we have examined the impact of several aspects of the image quality (noise, fluctuations, distortion. The strain field information derived from the HREM image analysis is further introduced in a simulation of the dislocation motion in the matrix.

  6. 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...

  7. 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

  8. 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.)

  9. Methods for evaluating imaging methods of limited reproducibility

    International Nuclear Information System (INIS)

    Krummenauer, F.

    2005-01-01

    Just like new drugs, new or modified imaging methods must be subjected to objective clinical tests, including tests on humans. In this, it must be ensured that the principle of Good Clinical Practice (GCP) are followed with regard to medical, administrative and methodical quality. Innovative methods fo clinical epidemiology and medical biometry should be applied from the planning stage to the final statistical evaluation. The author presents established and new methods for planning, evaluation and reporting of clinical tests of diagnostic methods, and especially imaging methods, in clinical medicine and illustrates these by means of current research projects in the various medical disciplines. The strategies presented are summarized in a recommendation based on the concept of phases I - IV of clinical drug testing in order to enable standardisation of the clinical evaluation of imaging methods. (orig.)

  10. Advanced image based methods for structural integrity monitoring: Review and prospects

    Science.gov (United States)

    Farahani, Behzad V.; Sousa, Pedro José; Barros, Francisco; Tavares, Paulo J.; Moreira, Pedro M. G. P.

    2018-02-01

    There is a growing trend in engineering to develop methods for structural integrity monitoring and characterization of in-service mechanical behaviour of components. The fast growth in recent years of image processing techniques and image-based sensing for experimental mechanics, brought about a paradigm change in phenomena sensing. Hence, several widely applicable optical approaches are playing a significant role in support of experiment. The current review manuscript describes advanced image based methods for structural integrity monitoring, and focuses on methods such as Digital Image Correlation (DIC), Thermoelastic Stress Analysis (TSA), Electronic Speckle Pattern Interferometry (ESPI) and Speckle Pattern Shearing Interferometry (Shearography). These non-contact full-field techniques rely on intensive image processing methods to measure mechanical behaviour, and evolve even as reviews such as this are being written, which justifies a special effort to keep abreast of this progress.

  11. 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...

  12. X-ray fluorescence method for trace analysis and imaging

    International Nuclear Information System (INIS)

    Hayakawa, Shinjiro

    2000-01-01

    X-ray fluorescence analysis has a long history as conventional bulk elemental analysis with medium sensitivity. However, with the use of synchrotron radiation x-ray fluorescence method has become a unique analytical technique which can provide tace elemental information with the spatial resolution. To obtain quantitative information of trace elemental distribution by using the x-ray fluorescence method, theoretical description of x-ray fluorescence yield is described. Moreover, methods and instruments for trace characterization with a scanning x-ray microprobe are described. (author)

  13. Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

    Science.gov (United States)

    Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

    2015-08-01

    A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as 1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

  14. 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...

  15. 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.

  16. A new method for lumbar herniated inter-vertebral disc diagnosis based on image analysis of transverse sections.

    Science.gov (United States)

    Tsai, Ming Dar; Jou, Shyan Bin; Hsieh, Ming Shium

    2002-01-01

    This paper describes an image analysis method that uses automatic algorithms for the evaluation of herniation classification and geometry in the diagnosis of lumbar herniated inter-vertebral disc (HIVD). The method uses boundary approximation that uses a B-spline curve to approximate circle-like disc boundary and excludes the herniation from other normal parts of the disc boundary and, feature recognition that classifies the herniation, and herniation shape reconstruction that infers the 3D geometry from one or more transverse sections. This method can be used as a qualitative and quantitative tool for the diagnosis of lumbar HIVD using transverse sections.

  17. Quantification and characterization of zirconium hydrides in Zircaloy-4 by the image analysis method

    International Nuclear Information System (INIS)

    Zhang, J.H.; Groos, M.; Bredel, T.; Trotabas, M.; Combette, P.

    1992-01-01

    The image analysis method is used to determine the hydrogen content in specimens of Zircaloy-4. Two parameters, surface density of hydride, S v , and degree of orientation, Ω, are defined to represent separately the hydrogen content and the orientation of hydrides. By analysing the stress-relieved Zircaloy-4 specimens with known hydrogen content from 100 to 1000 ppm, a relationship is established between the parameter S v and the hydrogen content when the magnifications of the optical microscope are 1000 and 250. The degree of orientation for the hydride in the stress-relieved Zircaloy-4 cladding is about 0.3. (orig.)

  18. An Image Analysis Method for the Precise Selection and Quantitation of Fluorescently Labeled Cellular Constituents

    Science.gov (United States)

    Agley, Chibeza C.; Velloso, Cristiana P.; Lazarus, Norman R.

    2012-01-01

    The accurate measurement of the morphological characteristics of cells with nonuniform conformations presents difficulties. We report here a straightforward method using immunofluorescent staining and the commercially available imaging program Adobe Photoshop, which allows objective and precise information to be gathered on irregularly shaped cells. We have applied this measurement technique to the analysis of human muscle cells and their immunologically marked intracellular constituents, as these cells are prone to adopting a highly branched phenotype in culture. Use of this method can be used to overcome many of the long-standing limitations of conventional approaches for quantifying muscle cell size in vitro. In addition, wider applications of Photoshop as a quantitative and semiquantitative tool in immunocytochemistry are explored. PMID:22511600

  19. 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.

  20. 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.

  1. Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

    Science.gov (United States)

    Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

    2018-04-01

    Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

  2. Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method.

    Science.gov (United States)

    Chan, Leo Li-Ying; Kuksin, Dmitry; Laverty, Daniel J; Saldi, Stephanie; Qiu, Jean

    2015-05-01

    The ability to accurately determine cell viability is essential to performing a well-controlled biological experiment. Typical experiments range from standard cell culturing to advanced cell-based assays that may require cell viability measurement for downstream experiments. The traditional cell viability measurement method has been the trypan blue (TB) exclusion assay. However, since the introduction of fluorescence-based dyes for cell viability measurement using flow or image-based cytometry systems, there have been numerous publications comparing the two detection methods. Although previous studies have shown discrepancies between TB exclusion and fluorescence-based viability measurements, image-based morphological analysis was not performed in order to examine the viability discrepancies. In this work, we compared TB exclusion and fluorescence-based viability detection methods using image cytometry to observe morphological changes due to the effect of TB on dead cells. Imaging results showed that as the viability of a naturally-dying Jurkat cell sample decreased below 70 %, many TB-stained cells began to exhibit non-uniform morphological characteristics. Dead cells with these characteristics may be difficult to count under light microscopy, thus generating an artificially higher viability measurement compared to fluorescence-based method. These morphological observations can potentially explain the differences in viability measurement between the two methods.

  3. [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.

  4. 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.

  5. Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

    Science.gov (United States)

    Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

    2009-07-01

    Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

  6. Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

    Science.gov (United States)

    Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

    2009-01-01

    Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  8. Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

    International Nuclear Information System (INIS)

    Chen, Q G; Xu, Y; Zhu, H H; Chen, H; Lin, B

    2015-01-01

    A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565–750 nm. The spectral parameter, defined as the ratio of wavebands at 565–750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66–1.06, 1.06–1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems. (paper)

  9. Image splitting and remapping method for radiological image compression

    Science.gov (United States)

    Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

    1990-07-01

    A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

  10. A rapid method for counting nucleated erythrocytes on stained blood smears by digital image analysis

    Science.gov (United States)

    Gering, E.; Atkinson, C.T.

    2004-01-01

    Measures of parasitemia by intraerythrocytic hematozoan parasites are normally expressed as the number of infected erythrocytes per n erythrocytes and are notoriously tedious and time consuming to measure. We describe a protocol for generating rapid counts of nucleated erythrocytes from digital micrographs of thin blood smears that can be used to estimate intensity of hematozoan infections in nonmammalian vertebrate hosts. This method takes advantage of the bold contrast and relatively uniform size and morphology of erythrocyte nuclei on Giemsa-stained blood smears and uses ImageJ, a java-based image analysis program developed at the U.S. National Institutes of Health and available on the internet, to recognize and count these nuclei. This technique makes feasible rapid and accurate counts of total erythrocytes in large numbers of microscope fields, which can be used in the calculation of peripheral parasitemias in low-intensity infections.

  11. Methods of digital image processing

    International Nuclear Information System (INIS)

    Doeler, W.

    1985-01-01

    Increasing use of computerized methods for diagnostical imaging of radiological problems will open up a wide field of applications for digital image processing. The requirements set by routine diagnostics in medical radiology point to picture data storage and documentation and communication as the main points of interest for application of digital image processing. As to the purely radiological problems, the value of digital image processing is to be sought in the improved interpretability of the image information in those cases where the expert's experience and image interpretation by human visual capacities do not suffice. There are many other domains of imaging in medical physics where digital image processing and evaluation is very useful. The paper reviews the various methods available for a variety of problem solutions, and explains the hardware available for the tasks discussed. (orig.) [de

  12. Automated Image Analysis of Offshore Infrastructure Marine Biofouling

    Directory of Open Access Journals (Sweden)

    Kate Gormley

    2018-01-01

    Full Text Available In the UK, some of the oldest oil and gas installations have been in the water for over 40 years and have considerable colonisation by marine organisms, which may lead to both industry challenges and/or potential biodiversity benefits (e.g., artificial reefs. The project objective was to test the use of an automated image analysis software (CoralNet on images of marine biofouling from offshore platforms on the UK continental shelf, with the aim of (i training the software to identify the main marine biofouling organisms on UK platforms; (ii testing the software performance on 3 platforms under 3 different analysis criteria (methods A–C; (iii calculating the percentage cover of marine biofouling organisms and (iv providing recommendations to industry. Following software training with 857 images, and testing of three platforms, results showed that diversity of the three platforms ranged from low (in the central North Sea to moderate (in the northern North Sea. The two central North Sea platforms were dominated by the plumose anemone Metridium dianthus; and the northern North Sea platform showed less obvious species domination. Three different analysis criteria were created, where the method of selection of points, number of points assessed and confidence level thresholds (CT varied: (method A random selection of 20 points with CT 80%, (method B stratified random of 50 points with CT of 90% and (method C a grid approach of 100 points with CT of 90%. Performed across the three platforms, the results showed that there were no significant differences across the majority of species and comparison pairs. No significant difference (across all species was noted between confirmed annotations methods (A, B and C. It was considered that the software performed well for the classification of the main fouling species in the North Sea. Overall, the study showed that the use of automated image analysis software may enable a more efficient and consistent

  13. 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.

  14. Image registration method for medical image sequences

    Science.gov (United States)

    Gee, Timothy F.; Goddard, James S.

    2013-03-26

    Image registration of low contrast image sequences is provided. In one aspect, a desired region of an image is automatically segmented and only the desired region is registered. Active contours and adaptive thresholding of intensity or edge information may be used to segment the desired regions. A transform function is defined to register the segmented region, and sub-pixel information may be determined using one or more interpolation methods.

  15. APPLICATION OF IMAGE ANALYSIS METHODS FOR ISOCENTER QUALITY ASSURANCE IN RADIOTHERAPY

    Directory of Open Access Journals (Sweden)

    Michał Niedźwiecki

    2017-03-01

    Full Text Available One of the major procedures for testing the geometrical accuracy of devices used in radiotherapy treatments is the test of the geometrical position of the radiation isocenter. The importance of the test reflects the fact that geometrical position of the radiation isocenter generally affects the tumor targeting. At present the geometric accuracy is assessed with the Winston-Lutz test which checks the position of an image of a ball marker with the respect to the center of the radiation field as projected on a detector plane. Obviously, determination of coordinates of a single marker is not sufficient to fully account for a complicated geometry of a therapeutic device. The purpose of the study was to design a new image analysis tool to better determine the isocenter. The proposed automated procedure for determining isocenter position uses projection data acquired for a special cube phantom. The projection images of a phantom are acquired for various angles of rotation of the gantry. A procedure is proposed to extract some geometric characteristics of a therapeutic device from the projection images.

  16. 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

  17. Bubble parameters analysis of gas-liquid two-phase sparse bubbly flow based on image method

    International Nuclear Information System (INIS)

    Zhou Yunlong; Zhou Hongjuan; Song Lianzhuang; Liu Qian

    2012-01-01

    The sparse rising bubbles of gas-liquid two-phase flow in vertical pipe were measured and studied based on image method. The bubble images were acquired by high-speed video camera systems, the characteristic parameters of bubbles were extracted by using image processing techniques. Then velocity variation of rising bubbles were drawn. Area and centroid variation of single bubble were also drawn. And then parameters and movement law of bubbles were analyzed and studied. The test results showed that parameters of bubbles had been analyzed well by using image method. (authors)

  18. Evaluation of auto-assessment method for C-D analysis based on support vector machine

    International Nuclear Information System (INIS)

    Takei, Takaaki; Ikeda, Mitsuru; Imai, Kuniharu; Kamihira, Hiroaki; Kishimoto, Tomonari; Goto, Hiroya

    2010-01-01

    Contrast-Detail (C-D) analysis is one of the visual quality assessment methods in medical imaging, and many auto-assessment methods for C-D analysis have been developed in recent years. However, for the auto-assessment method for C-D analysis, the effects of nonlinear image processing are not clear. So, we have made an auto-assessment method for C-D analysis using a support vector machine (SVM), and have evaluated its performance for the images processed with a noise reduction method. The feature indexes used in the SVM were the normalized cross correlation (NCC) coefficient on each signal between the noise-free and noised image, the contrast to noise ratio (CNR) on each signal, the radius of each signal, and the Student's t-test statistic for the mean difference between the signal and background pixel values. The results showed that the auto-assessment method for C-D analysis by using Student's t-test statistic agreed well with the visual assessment for the non-processed images, but disagreed for the images processed with the noise reduction method. Our results also showed that the auto-assessment method for C-D analysis by the SVM made of NCC and CNR agreed well with the visual assessment for the non-processed and noise-reduced images. Therefore, the auto-assessment method for C-D analysis by the SVM will be expected to have the robustness for the non-linear image processing. (author)

  19. Application of Image Texture Analysis for Evaluation of X-Ray Images of Fungal-Infected Maize Kernels

    DEFF Research Database (Denmark)

    Orina, Irene; Manley, Marena; Kucheryavskiy, Sergey V.

    2018-01-01

    The feasibility of image texture analysis to evaluate X-ray images of fungal-infected maize kernels was investigated. X-ray images of maize kernels infected with Fusarium verticillioides and control kernels were acquired using high-resolution X-ray micro-computed tomography. After image acquisition...... developed using partial least squares discriminant analysis (PLS-DA), and accuracies of 67 and 73% were achieved using first-order statistical features and GLCM extracted features, respectively. This work provides information on the possible application of image texture as method for analysing X-ray images......., homogeneity and contrast) were extracted from the side, front and top views of each kernel and used as inputs for principal component analysis (PCA). The first-order statistical image features gave a better separation of the control from infected kernels on day 8 post-inoculation. Classification models were...

  20. 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)

  1. DAFS measurements using the image-plate Weissenberg method

    International Nuclear Information System (INIS)

    Sugioka, N.; Matsumoto, K.; Sasaki, S.; Tanaka, M.; Mori, T.

    1998-01-01

    An instrumental technique for DAFS measurements which can provide site-specific information is proposed. The approach uses (i) focusing optics with parabolic mirrors and a double-crystal monochromator, (ii) the Laue and Bragg settings and (iii) data collection by the image-plate Weissenberg method. Six image exposures are recorded per plate at five intrinsic energies and one reference energy. The single-crystal measurements were performed at the Co K-absorption edge, and the 200, 220 and 311 reflections of CoO and 511 and 911 reflections of Co 3 O 4 were used for analysis. The regression analysis of χ(k), Fourier transforms of k 3 χ(k) and back-Fourier filtering have been performed

  2. Multi-scale image segmentation method with visual saliency constraints and its application

    Science.gov (United States)

    Chen, Yan; Yu, Jie; Sun, Kaimin

    2018-03-01

    Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works

  3. A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-11-01

    Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

  4. Twin-Foucault imaging method

    Science.gov (United States)

    Harada, Ken

    2012-02-01

    A method of Lorentz electron microscopy, which enables observation two Foucault images simultaneously by using an electron biprism instead of an objective aperture, was developed. The electron biprism is installed between two electron beams deflected by 180° magnetic domains. Potential applied to the biprism deflects the two electron beams further, and two Foucault images with reversed contrast are then obtained in one visual field. The twin Foucault images are able to extract the magnetic domain structures and to reconstruct an ordinary electron micrograph. The developed Foucault method was demonstrated with a 180° domain structure of manganite La0.825Sr0.175MnO3.

  5. 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

  6. Objectivity of two methods of differentiating fibre types and repeatability of measurements by application of the TEMA image analysis system.

    Science.gov (United States)

    Henckel, P; Ducro, B; Oksbjerg, N; Hassing, L

    1998-01-01

    The objectivity of two of the most widely used methods for differentiation of fibre types, i.e. 1) the myosin ATP-ase method (Brooke and Kaiser, 1970a,b) and 2) the combined method, by which the myosin ATP-ase reaction is used to differentiate between fast and slow twitch fibres and NADH-tetrazolium reductase activity is used to identify the subgroups of fast twitch fibres (Ashmore and Doerr, 1970, Peter et al., 1972), was assessed in muscle samples from horses, calves and pigs. We also assessed the objectivity of the alpha-amylase-PAS preparation for the visualisation of capillaries (Andersen, 1975) in these species. For the purpose of reducing the time costs of histochemical analysis of muscle samples, we have developed an interactive image analysis system which is described. All analyses are performed on this system. In accordance with several other investigations, differences between the two methods of differentiating fibre types were found only for the relative distribution of the fast-twitch fibre subgroups (p 87%), the impact of differences in pre-requisites (varied degrees of overlap between the fibre types) for performing the differentiation by the combined method raises a question of the reliability of this method. Apparently, no general rules for comparison of results of distribution of the two subgroups of fast twitch fibres by the two methods are applicable. The alpha-amylase-PAS method was found to be a fairly objective method to identify capillaries in muscles from horses, calves and pigs. However, as capillarity described in combination with other traits to give an indication of diffusion characteristics is significantly influenced by person, it is recommended that the same person perform all the analysis of a project. In addition to the methodological results in this study, we have shown that by application of the TEMA image analysis system, which is more rapid compared with the time-consuming traditional method for evaluation of histochemical

  7. Various imaging methods in the detection of small hepatomas

    International Nuclear Information System (INIS)

    Nakatsuka, Haruki; Kaminou, Toshio; Takemoto, Kazumasa; Takashima, Sumio; Kobayashi, Nobuyuki; Nakamura, Kenji; Onoyama, Yasuto; Kurioka, Naruto

    1985-01-01

    Fifty-one patients with small hepatomas under 5 cm in diameter were studied to compare the detectability of various imaging methods. Positive finding was obtained in 50 % of the patients by scintigraphy, in 74 % by ultrasonography and in 79 % by CT during screening tests. Rate of detection in retrospective analysis, after the site of the tumor had been known, were 73 %, 93 % and 87 % respectively. Rate of detection was 92 % by celiac arteriography and 98 % by selective hepatic arteriography. In 21 patients, who had the tumor under 3 cm, the rate was 32 % for scintigraphy, 74 % for ultrasonography and 65 % for CT during screening, whereas it was 58 %, 84 % and 75 % retrospectively. By celiac arteriography, it was 85 %, and by hepatic arteriography, 95 %. Rate of detection of small hepatomas in screening tests differed remarkably from that in retrospective analysis. No single method of imaging can disclose reliably the presense of small hepatoma, therefore more than one method should be used in screening. (author)

  8. 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/.

  9. 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...

  10. On Plant Detection of Intact Tomato Fruits Using Image Analysis and Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Kyosuke Yamamoto

    2014-07-01

    Full Text Available Fully automated yield estimation of intact fruits prior to harvesting provides various benefits to farmers. Until now, several studies have been conducted to estimate fruit yield using image-processing technologies. However, most of these techniques require thresholds for features such as color, shape and size. In addition, their performance strongly depends on the thresholds used, although optimal thresholds tend to vary with images. Furthermore, most of these techniques have attempted to detect only mature and immature fruits, although the number of young fruits is more important for the prediction of long-term fluctuations in yield. In this study, we aimed to develop a method to accurately detect individual intact tomato fruits including mature, immature and young fruits on a plant using a conventional RGB digital camera in conjunction with machine learning approaches. The developed method did not require an adjustment of threshold values for fruit detection from each image because image segmentation was conducted based on classification models generated in accordance with the color, shape, texture and size of the images. The results of fruit detection in the test images showed that the developed method achieved a recall of 0.80, while the precision was 0.88. The recall values of mature, immature and young fruits were 1.00, 0.80 and 0.78, respectively.

  11. Image processing methods and architectures in diagnostic pathology.

    Directory of Open Access Journals (Sweden)

    Oscar DĂŠniz

    2010-05-01

    Full Text Available Grid technology has enabled the clustering and the efficient and secure access to and interaction among a wide variety of geographically distributed resources such as: supercomputers, storage systems, data sources, instruments and special devices and services. Their main applications include large-scale computational and data intensive problems in science and engineering. General grid structures and methodologies for both software and hardware in image analysis for virtual tissue-based diagnosis has been considered in this paper. This methods are focus on the user level middleware. The article describes the distributed programming system developed by the authors for virtual slide analysis in diagnostic pathology. The system supports different image analysis operations commonly done in anatomical pathology and it takes into account secured aspects and specialized infrastructures with high level services designed to meet application requirements. Grids are likely to have a deep impact on health related applications, and therefore they seem to be suitable for tissue-based diagnosis too. The implemented system is a joint application that mixes both Web and Grid Service Architecture around a distributed architecture for image processing. It has shown to be a successful solution to analyze a big and heterogeneous group of histological images under architecture of massively parallel processors using message passing and non-shared memory.

  12. New Analysis Method Application in Metallographic Images through the Construction of Mosaics Via Speeded Up Robust Features and Scale Invariant Feature Transform

    Directory of Open Access Journals (Sweden)

    Pedro Pedrosa Rebouças Filho

    2015-06-01

    Full Text Available In many applications in metallography and analysis, many regions need to be considered and not only the current region. In cases where there are analyses with multiple images, the specialist should also evaluate neighboring areas. For example, in metallurgy, welding technology is derived from conventional testing and metallographic analysis. In welding, these tests allow us to know the features of the metal, especially in the Heat-Affected Zone (HAZ; the region most likely for natural metallurgical problems to occur in welding. The expanse of the Heat-Affected Zone exceeds the size of the area observed through a microscope and typically requires multiple images to be mounted on a larger picture surface to allow for the study of the entire heat affected zone. This image stitching process is performed manually and is subject to all the inherent flaws of the human being due to results of fatigue and distraction. The analyzing of grain growth is also necessary in the examination of multiple regions, although not necessarily neighboring regions, but this analysis would be a useful tool to aid a specialist. In areas such as microscopic metallography, which study metallurgical products with the aid of a microscope, the assembly of mosaics is done manually, which consumes a lot of time and is also subject to failures due to human limitations. The mosaic technique is used in the construct of environment or scenes with corresponding characteristics between themselves. Through several small images, and with corresponding characteristics between themselves, a new model is generated in a larger size. This article proposes the use of Digital Image Processing for the automatization of the construction of these mosaics in metallographic images. The use of this proposed method is meant to significantly reduce the time required to build the mosaic and reduce the possibility of failures in assembling the final image; therefore increasing efficiency in obtaining

  13. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    Science.gov (United States)

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Published by Elsevier B.V.

  14. Image correlation method for DNA sequence alignment.

    Science.gov (United States)

    Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

    2012-01-01

    The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

  15. MO-FG-202-06: Improving the Performance of Gamma Analysis QA with Radiomics- Based Image Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wootton, L; Nyflot, M; Ford, E [University of Washington Department of Radiation Oncology, Seattle, WA (United States); Chaovalitwongse, A [University of Washington Department of Industrial and Systems Engineering, Seattle, Washington (United States); University of Washington Department of Radiology, Seattle, WA (United States); Li, N [University of Washington Department of Industrial and Systems Engineering, Seattle, Washington (United States)

    2016-06-15

    Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributed (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for

  16. 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

  17. A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images.

    Science.gov (United States)

    Gao, Han; Tang, Yunwei; Jing, Linhai; Li, Hui; Ding, Haifeng

    2017-10-24

    The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods.

  18. A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Han Gao

    2017-10-01

    Full Text Available The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA. Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods.

  19. 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.

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

    International Nuclear Information System (INIS)

    Beier, J.

    2001-01-01

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

  1. The method for objective evaluation of the intensity of radial bone lesions in rheumatoid arthritis using digital image analysis

    International Nuclear Information System (INIS)

    Zielinski, K.W.; Krekora, K.

    2004-01-01

    The semiquantitative methods used in everyday diagnostic practice for scoring the intensity of bone lesions in rheumatoid arthritis are susceptible to a subjective error. The paper describes the original algorithm for an image analysis as a method for quantitative and objective evaluation of the intensity of radiological lesions in rheumatoid arthritis. 75 plain radiograms of the hand of patients diagnosed with rheumatoid arthritis, in various stages of bone pathology, were evaluated. The analysis focused on the signs of pathological rebuilding of the affected bone, especially in the distal epiphysis of the radial bone. The plain radiograms of the hand were digitally analysed based on the modified method, formerly used for quantitative assessment of bone trabeculation. The method allowed us to objectively verify various scoring systems of radiograms widely used in rheumatological diagnosis. (author)

  2. A statistically harmonized alignment-classification in image space enables accurate and robust alignment of noisy images in single particle analysis.

    Science.gov (United States)

    Kawata, Masaaki; Sato, Chikara

    2007-06-01

    In determining the three-dimensional (3D) structure of macromolecular assemblies in single particle analysis, a large representative dataset of two-dimensional (2D) average images from huge number of raw images is a key for high resolution. Because alignments prior to averaging are computationally intensive, currently available multireference alignment (MRA) software does not survey every possible alignment. This leads to misaligned images, creating blurred averages and reducing the quality of the final 3D reconstruction. We present a new method, in which multireference alignment is harmonized with classification (multireference multiple alignment: MRMA). This method enables a statistical comparison of multiple alignment peaks, reflecting the similarities between each raw image and a set of reference images. Among the selected alignment candidates for each raw image, misaligned images are statistically excluded, based on the principle that aligned raw images of similar projections have a dense distribution around the correctly aligned coordinates in image space. This newly developed method was examined for accuracy and speed using model image sets with various signal-to-noise ratios, and with electron microscope images of the Transient Receptor Potential C3 and the sodium channel. In every data set, the newly developed method outperformed conventional methods in robustness against noise and in speed, creating 2D average images of higher quality. This statistically harmonized alignment-classification combination should greatly improve the quality of single particle analysis.

  3. 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...

  4. 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

  5. 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

  6. Digital image processing mathematical and computational methods

    CERN Document Server

    Blackledge, J M

    2005-01-01

    This authoritative text (the second part of a complete MSc course) provides mathematical methods required to describe images, image formation and different imaging systems, coupled with the principle techniques used for processing digital images. It is based on a course for postgraduates reading physics, electronic engineering, telecommunications engineering, information technology and computer science. This book relates the methods of processing and interpreting digital images to the 'physics' of imaging systems. Case studies reinforce the methods discussed, with examples of current research

  7. A single-image method of aberration retrieval for imaging systems under partially coherent illumination

    International Nuclear Information System (INIS)

    Xu, Shuang; Liu, Shiyuan; Zhang, Chuanwei; Wei, Haiqing

    2014-01-01

    We propose a method for retrieving small lens aberrations in optical imaging systems under partially coherent illumination, which only requires to measure one single defocused image of intensity. By deriving a linear theory of imaging systems, we obtain a generalized formulation of aberration sensitivity in a matrix form, which provides a set of analytic kernels that relate the measured intensity distribution directly to the unknown Zernike coefficients. Sensitivity analysis is performed and test patterns are optimized to ensure well-posedness of the inverse problem. Optical lithography simulations have validated the theoretical derivation and confirmed its simplicity and superior performance in retrieving small lens aberrations. (fast track communication)

  8. Quantitative evaluation method of the bubble structure of sponge cake by using morphology image processing

    Science.gov (United States)

    Tatebe, Hironobu; Kato, Kunihito; Yamamoto, Kazuhiko; Katsuta, Yukio; Nonaka, Masahiko

    2005-12-01

    Now a day, many evaluation methods for the food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that are using for the quality evaluation. An advantage of the image processing is to be able to evaluate objectively. The goal of our research is structure evaluation of sponge cake by using image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner. Because the depth of field of this type scanner is very shallow, the bubble region of the surface has low gray scale values, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. First, input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

  9. 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.

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

    Science.gov (United States)

    Zhu, Xiaokun; Jia, Yonghong

    2005-10-01

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

  11. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

    Science.gov (United States)

    Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C

    2015-02-01

    Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  12. Computerized image analysis: Texture-field orientation method for pectoral muscle identification on MLO-view mammograms

    International Nuclear Information System (INIS)

    Zhou Chuan; Wei Jun; Chan, Heang-Ping; Paramagul, Chintana; Hadjiiski, Lubomir M.; Sahiner, Berkman; Douglas, Julie A.

    2010-01-01

    Purpose: To develop a new texture-field orientation (TFO) method that combines a priori knowledge, local and global information for the automated identification of pectoral muscle on mammograms. Methods: The authors designed a gradient-based directional kernel (GDK) filter to enhance the linear texture structures, and a gradient-based texture analysis to extract a texture orientation image that represented the dominant texture orientation at each pixel. The texture orientation image was enhanced by a second GDK filter for ridge point extraction. The extracted ridge points were validated and the ridges that were less likely to lie on the pectoral boundary were removed automatically. A shortest-path finding method was used to generate a probability image that represented the likelihood that each remaining ridge point lay on the true pectoral boundary. Finally, the pectoral boundary was tracked by searching for the ridge points with the highest probability lying on the pectoral boundary. A data set of 130 MLO-view digitized film mammograms (DFMs) from 65 patients was used to train the TFO algorithm. An independent data set of 637 MLO-view DFMs from 562 patients was used to evaluate its performance. Another independent data set of 92 MLO-view full field digital mammograms (FFDMs) from 92 patients was used to assess the adaptability of the TFO algorithm to FFDMs. The pectoral boundary detection accuracy of the TFO method was quantified by comparison with an experienced radiologist's manually drawn pectoral boundary using three performance metrics: The percent overlap area (POA), the Hausdorff distance (Hdist), and the average distance (AvgDist). Results: The mean and standard deviation of POA, Hdist, and AvgDist were 95.0±3.6%, 3.45±2.16 mm, and 1.12±0.82 mm, respectively. For the POA measure, 91.5%, 97.3%, and 98.9% of the computer detected pectoral muscles had POA larger than 90%, 85%, and 80%, respectively. For the distance measures, 85.4% and 98.0% of the

  13. Biexponential analysis of diffusion-weighted imaging: comparison of three different calculation methods in transplanted kidneys.

    Science.gov (United States)

    Heusch, Philipp; Wittsack, Hans-Jörg; Pentang, Gael; Buchbender, Christian; Miese, Falk; Schek, Julia; Kröpil, Patric; Antoch, Gerald; Lanzman, Rotem S

    2013-12-01

    Biexponential analysis has been used increasingly to obtain contributions of both diffusion and microperfusion to the signal decay in diffusion-weighted imaging DWI of different parts of the body. To compare biexponential diffusion parameters of transplanted kidneys obtained with three different calculation methods. DWI was acquired in 15 renal allograft recipients (eight men, seven women; mean age, 52.4 ± 14.3 years) using a paracoronal EPI sequence with 16 b-values (b = 0-750 s/mm(2)) and six averages at 1.5T. No respiratory gating was used. Three different calculation methods were used for the calculation of biexponential diffusion parameters: Fp, ADCP, and ADCD were calculated without fixing any parameter a priori (calculation method 1); ADCP was fixed to 12.0 µm(2)/ms, whereas Fp and ADCD were calculated using the biexponential model (calculation method 2); multistep approach with monoexponential fitting of the high b-value portion (b ≥ 250 s/mm(2)) for determination of ADCD and assessment of the low b intercept for determination of Fp (calculation method 3). For quantitative analysis, ROI measurements were performed on the according parameter maps. Mean ADCD values of the renal cortex using calculation method 1 were significantly lower than using calculation methods 2 and 3 (P < 0.001). There was a significant correlation between calculation methods 1 and 2 (r = 0.69 (P < 0.005) and calculation methods 1 and 3 (r = 0.59; P < 0.05) as well as calculation methods 2 and 3 (r = 0.98; P < 0.001). Mean Fp values of the renal cortex were higher with calculation method 1 than with calculation methods 2 and 3 (P < 0.001). For Fp, only the correlation between calculation methods 2 and 3 was significant (r = 0.98; P < 0.001). Biexponential diffusion parameters differ significantly depending on the calculation methods used for their calculation.

  14. Detailed analysis of latencies in image-based dynamic MLC tracking

    International Nuclear Information System (INIS)

    Poulsen, Per Rugaard; Cho, Byungchul; Sawant, Amit; Ruan, Dan; Keall, Paul J.

    2010-01-01

    Purpose: Previous measurements of the accuracy of image-based real-time dynamic multileaf collimator (DMLC) tracking show that the major contributor to errors is latency, i.e., the delay between target motion and MLC response. Therefore the purpose of this work was to develop a method for detailed analysis of latency contributions during image-based DMLC tracking. Methods: A prototype DMLC tracking system integrated with a linear accelerator was used for tracking a phantom with an embedded fiducial marker during treatment delivery. The phantom performed a sinusoidal motion. Real-time target localization was based on x-ray images acquired either with a portal imager or a kV imager mounted orthogonal to the treatment beam. Each image was stored in a file on the imaging workstation. A marker segmentation program opened the image file, determined the marker position in the image, and transferred it to the DMLC tracking program. This program estimated the three-dimensional target position by a single-imager method and adjusted the MLC aperture to the target position. Imaging intervals ΔT image from 150 to 1000 ms were investigated for both kV and MV imaging. After the experiments, the recorded images were synchronized with MLC log files generated by the MLC controller and tracking log files generated by the tracking program. This synchronization allowed temporal analysis of the information flow for each individual image from acquisition to completed MLC adjustment. The synchronization also allowed investigation of the MLC adjustment dynamics on a considerably finer time scale than the 50 ms time resolution of the MLC log files. Results: For ΔT image =150 ms, the total time from image acquisition to completed MLC adjustment was 380±9 ms for MV and 420±12 ms for kV images. The main part of this time was from image acquisition to completed image file writing (272 ms for MV and 309 ms for kV). Image file opening (38 ms), marker segmentation (4 ms), MLC position

  15. Detailed analysis of latencies in image-based dynamic MLC tracking

    Energy Technology Data Exchange (ETDEWEB)

    Poulsen, Per Rugaard; Cho, Byungchul; Sawant, Amit; Ruan, Dan; Keall, Paul J. [Department of Radiation Oncology, Stanford University, Stanford, California 94305 and Department of Oncology and Department of Medical Physics, Aarhus University Hospital, 8000 Aarhus (Denmark); Department of Radiation Oncology, Stanford University, Stanford, California 94305 and Department of Radiation Oncology, Asan Medical Center, Seoul 138-736 (Korea, Republic of); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States)

    2010-09-15

    Purpose: Previous measurements of the accuracy of image-based real-time dynamic multileaf collimator (DMLC) tracking show that the major contributor to errors is latency, i.e., the delay between target motion and MLC response. Therefore the purpose of this work was to develop a method for detailed analysis of latency contributions during image-based DMLC tracking. Methods: A prototype DMLC tracking system integrated with a linear accelerator was used for tracking a phantom with an embedded fiducial marker during treatment delivery. The phantom performed a sinusoidal motion. Real-time target localization was based on x-ray images acquired either with a portal imager or a kV imager mounted orthogonal to the treatment beam. Each image was stored in a file on the imaging workstation. A marker segmentation program opened the image file, determined the marker position in the image, and transferred it to the DMLC tracking program. This program estimated the three-dimensional target position by a single-imager method and adjusted the MLC aperture to the target position. Imaging intervals {Delta}T{sub image} from 150 to 1000 ms were investigated for both kV and MV imaging. After the experiments, the recorded images were synchronized with MLC log files generated by the MLC controller and tracking log files generated by the tracking program. This synchronization allowed temporal analysis of the information flow for each individual image from acquisition to completed MLC adjustment. The synchronization also allowed investigation of the MLC adjustment dynamics on a considerably finer time scale than the 50 ms time resolution of the MLC log files. Results: For {Delta}T{sub image}=150 ms, the total time from image acquisition to completed MLC adjustment was 380{+-}9 ms for MV and 420{+-}12 ms for kV images. The main part of this time was from image acquisition to completed image file writing (272 ms for MV and 309 ms for kV). Image file opening (38 ms), marker segmentation (4 ms

  16. Estimate of the melanin content in human hairs by the inverse Monte-Carlo method using a system for digital image analysis

    International Nuclear Information System (INIS)

    Bashkatov, A N; Genina, Elina A; Kochubei, V I; Tuchin, Valerii V

    2006-01-01

    Based on the digital image analysis and inverse Monte-Carlo method, the proximate analysis method is deve-loped and the optical properties of hairs of different types are estimated in three spectral ranges corresponding to three colour components. The scattering and absorption properties of hairs are separated for the first time by using the inverse Monte-Carlo method. The content of different types of melanin in hairs is estimated from the absorption coefficient. It is shown that the dominating type of melanin in dark hairs is eumelanin, whereas in light hairs pheomelanin dominates. (special issue devoted to multiple radiation scattering in random media)

  17. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    OpenAIRE

    Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Kuncic, Zdenka; Keall, Paul J.

    2014-01-01

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An inv...

  18. On a selection method of imaging condition in scintigraphy

    International Nuclear Information System (INIS)

    Ikeda, Hozumi; Kishimoto, Kenji; Shimonishi, Yoshihiro; Ohmura, Masahiro; Kosakai, Kazuhisa; Ochi, Hironobu

    1992-01-01

    Selection of imaging condition in scintigraphy was evaluated using analytic hierarchy process. First, a method of the selection was led by determining at the points of image quantity and imaging time. Influence of image quality was thought to depend on changes of system resolution, count density, image size, and image density. Also influence of imaging time was thought to depend on changes of system sensitivity and data acquisition time. Phantom study was done for paired comparison of these selection factors, and relations of sample data and the factors, that is Rollo phantom images were taken by changing count density, image size, and image density. Image quality was shown by calculating the score of visual evaluation that done by comparing of a pair of images in clearer cold lesion on the scintigrams. Imaging time was shown by relative values for changes of count density. However, system resolution and system sensitivity were constant in this study. Next, using these values analytic hierarchy process was adapted for this selection of imaging conditions. We conclude that this selection of imaging conditions can be analyzed quantitatively using analytic hierarchy process and this analysis develops theoretical consideration of imaging technique. (author)

  19. Beyond the transect: An alternative microchemical imaging method for fine scale analysis of trace elements in fish otoliths during early life

    International Nuclear Information System (INIS)

    McGowan, Nicole; Fowler, Ashley M.; Parkinson, Kerryn; Bishop, David P.; Ganio, Katherine; Doble, Philip A.; Booth, David J.; Hare, Dominic J.

    2014-01-01

    Microchemical analysis of otolith (calcified ‘ear stones’ used for balance and orientation) of fishes is an important tool for studying their environmental history and management. However, the spatial resolution achieved is often too coarse to examine short-term events occurring in early life. Current methods rely on single points or transects across the otolith surface, which may provide a limited view of elemental distributions, a matter that has not previously been investigated. Imaging by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) permits microchemical analyses of short-term events in early life with high (< 10 μm) resolution, two-dimensional (2D) visualization of elemental distributions. To demonstrate the potential of this method, we mapped the concentrations of Sr and Ba, two key trace elements, in a small number of juvenile otoliths of neon damselfish (Pomacentrus coelestis) using an 8 μm beam diameter (laser fluence of 13.8 ± 3.5 J cm −2 ). Quantification was performed using the established method by Longerich et al. (1996), which is applied to 2D imaging of a biological matrix here for the first time. Accuracy of > 97% was achieved using a multi-point non matrix-matched calibration of National Institute of Standards and Technology (NIST) 610 and 612 (trace elements in glass) using Longerich's calculation method against the matrix-matched standard FEBS-1 (powdered red snapper [Lutjanus campechanus] otolith). The spatial resolution achieved in the otolith corresponded to a time period of 2 ± 1 days during the larval phase, and 4 ± 1 days during the post-settlement juvenile phase. This method has the potential to improve interpretations of early life-history events at scales corresponding to specific events. While the images showed gradients in Sr and Ba across the larval settlement zone more clearly than single transects, the method proved sample homogeneity throughout the structure; demonstrating that 2D

  20. Beyond the transect: An alternative microchemical imaging method for fine scale analysis of trace elements in fish otoliths during early life

    Energy Technology Data Exchange (ETDEWEB)

    McGowan, Nicole [Elemental Bio-imaging Facility, University of Technology, Sydney, New South Wales (Australia); CCFS ARC Centre of Excellence, Department of Earth and Planetary Sciences, Macquarie University, Sydney (Australia); Fowler, Ashley M.; Parkinson, Kerryn [Fish Ecology Laboratory, School of the Environment, University of Technology, Sydney, New South Wales (Australia); Bishop, David P. [Elemental Bio-imaging Facility, University of Technology, Sydney, New South Wales (Australia); Ganio, Katherine [Florey Department of Neuroscience and Mental Health, University of Melbourne, Victoria (Australia); Doble, Philip A. [Elemental Bio-imaging Facility, University of Technology, Sydney, New South Wales (Australia); Booth, David J. [Fish Ecology Laboratory, School of the Environment, University of Technology, Sydney, New South Wales (Australia); Hare, Dominic J., E-mail: dominic.hare@uts.edu.au [Elemental Bio-imaging Facility, University of Technology, Sydney, New South Wales (Australia); Florey Department of Neuroscience and Mental Health, University of Melbourne, Victoria (Australia)

    2014-10-01

    Microchemical analysis of otolith (calcified ‘ear stones’ used for balance and orientation) of fishes is an important tool for studying their environmental history and management. However, the spatial resolution achieved is often too coarse to examine short-term events occurring in early life. Current methods rely on single points or transects across the otolith surface, which may provide a limited view of elemental distributions, a matter that has not previously been investigated. Imaging by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) permits microchemical analyses of short-term events in early life with high (< 10 μm) resolution, two-dimensional (2D) visualization of elemental distributions. To demonstrate the potential of this method, we mapped the concentrations of Sr and Ba, two key trace elements, in a small number of juvenile otoliths of neon damselfish (Pomacentrus coelestis) using an 8 μm beam diameter (laser fluence of 13.8 ± 3.5 J cm{sup −2}). Quantification was performed using the established method by Longerich et al. (1996), which is applied to 2D imaging of a biological matrix here for the first time. Accuracy of > 97% was achieved using a multi-point non matrix-matched calibration of National Institute of Standards and Technology (NIST) 610 and 612 (trace elements in glass) using Longerich's calculation method against the matrix-matched standard FEBS-1 (powdered red snapper [Lutjanus campechanus] otolith). The spatial resolution achieved in the otolith corresponded to a time period of 2 ± 1 days during the larval phase, and 4 ± 1 days during the post-settlement juvenile phase. This method has the potential to improve interpretations of early life-history events at scales corresponding to specific events. While the images showed gradients in Sr and Ba across the larval settlement zone more clearly than single transects, the method proved sample homogeneity throughout the structure; demonstrating that 2D

  1. Development of a quantitative assessment method of pigmentary skin disease using ultraviolet optical imaging.

    Science.gov (United States)

    Lee, Onseok; Park, Sunup; Kim, Jaeyoung; Oh, Chilhwan

    2017-11-01

    The visual scoring method has been used as a subjective evaluation of pigmentary skin disorders. Severity of pigmentary skin disease, especially melasma, is evaluated using a visual scoring method, the MASI (melasma area severity index). This study differentiates between epidermal and dermal pigmented disease. The study was undertaken to determine methods to quantitatively measure the severity of pigmentary skin disorders under ultraviolet illumination. The optical imaging system consists of illumination (white LED, UV-A lamp) and image acquisition (DSLR camera, air cooling CMOS CCD camera). Each camera is equipped with a polarizing filter to remove glare. To analyze images of visible and UV light, images are divided into frontal, cheek, and chin regions of melasma patients. Each image must undergo image processing. To reduce the curvature error in facial contours, a gradient mask is used. The new method of segmentation of front and lateral facial images is more objective for face-area-measurement than the MASI score. Image analysis of darkness and homogeneity is adequate to quantify the conventional MASI score. Under visible light, active lesion margins appear in both epidermal and dermal melanin, whereas melanin is found in the epidermis under UV light. This study objectively analyzes severity of melasma and attempts to develop new methods of image analysis with ultraviolet optical imaging equipment. Based on the results of this study, our optical imaging system could be used as a valuable tool to assess the severity of pigmentary skin disease. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Improved sampling and analysis of images in corneal confocal microscopy.

    Science.gov (United States)

    Schaldemose, E L; Fontain, F I; Karlsson, P; Nyengaard, J R

    2017-10-01

    Corneal confocal microscopy (CCM) is a noninvasive clinical method to analyse and quantify corneal nerve fibres in vivo. Although the CCM technique is in constant progress, there are methodological limitations in terms of sampling of images and objectivity of the nerve quantification. The aim of this study was to present a randomized sampling method of the CCM images and to develop an adjusted area-dependent image analysis. Furthermore, a manual nerve fibre analysis method was compared to a fully automated method. 23 idiopathic small-fibre neuropathy patients were investigated using CCM. Corneal nerve fibre length density (CNFL) and corneal nerve fibre branch density (CNBD) were determined in both a manual and automatic manner. Differences in CNFL and CNBD between (1) the randomized and the most common sampling method, (2) the adjusted and the unadjusted area and (3) the manual and automated quantification method were investigated. The CNFL values were significantly lower when using the randomized sampling method compared to the most common method (p = 0.01). There was not a statistical significant difference in the CNBD values between the randomized and the most common sampling method (p = 0.85). CNFL and CNBD values were increased when using the adjusted area compared to the standard area. Additionally, the study found a significant increase in the CNFL and CNBD values when using the manual method compared to the automatic method (p ≤ 0.001). The study demonstrated a significant difference in the CNFL values between the randomized and common sampling method indicating the importance of clear guidelines for the image sampling. The increase in CNFL and CNBD values when using the adjusted cornea area is not surprising. The observed increases in both CNFL and CNBD values when using the manual method of nerve quantification compared to the automatic method are consistent with earlier findings. This study underlines the importance of improving the analysis of the

  3. 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

  4. Quantitative comparison of two particle tracking methods in fluorescence microscopy images

    CSIR Research Space (South Africa)

    Mabaso, M

    2013-09-01

    Full Text Available that cannot be analysed efficiently by means of manual analysis. In this study we compare the performance of two computer-based tracking methods for tracking of bright particles in fluorescence microscopy image sequences. The methods under comparison are...

  5. 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.

  6. Tridimensional ultrasonic images analysis for the in service inspection of fast breeder reactors

    International Nuclear Information System (INIS)

    Dancre, M.

    1999-11-01

    Tridimensional image analysis provides a set of methods for the intelligent extraction of information in order to visualize, recognize or inspect objects in volumetric images. In this field of research, we are interested in algorithmic and methodological aspects to extract surface visual information embedded in volume ultrasonic images. The aim is to help a non-acoustician operator, possibly the system itself, to inspect surfaces of vessel and internals in Fast Breeder Reactors (FBR). Those surfaces are immersed in liquid metal, what justifies the ultrasonic technology choice. We expose firstly a state of the art on the visualization of volume ultrasonic images, the methods of noise analysis, the geometrical modelling for surface analysis and finally curves and surfaces matching. These four points are then inserted in a global analysis strategy that relies on an acoustical analysis (echoes recognition), an object analysis (object recognition and reconstruction) and a surface analysis (surface defects detection). Few literature can be found on ultrasonic echoes recognition through image analysis. We suggest an original method that can be generalized to all images with structured and non-structured noise. From a technical point of view, this methodology applied to echoes recognition turns out to be a cooperative approach between morphological mathematics and snakes (active contours). An entropy maximization technique is required for volumetric data binarization. (author)

  7. An improved level set method for brain MR images segmentation and bias correction.

    Science.gov (United States)

    Chen, Yunjie; Zhang, Jianwei; Macione, Jim

    2009-10-01

    Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.

  8. 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

  9. Comparison of Two Methods for Evaluation of the Image Quality of Lumbar Spine Radiographs

    International Nuclear Information System (INIS)

    Tingberg, A.; Herrmann, C.; Lanhede, B.; Almn, A.; Besjakov, J.; Mattsson, S.; Sund, P.; Kheddache, S.; Maasson, L.G.

    2000-01-01

    Two methods for visual evaluation of image quality of clinical radiographs have been compared. In visual grading analysis (VGA) specified anatomical structures in an image are visually compared with the same structures in a reference image, and in a free-response forced error (FFE) experiment - an extension of conventional ROC (receiver operating characteristics) analysis - the objective is to localise known lesions correctly. The spatial resolution and noise of digitised clinical radiographs of the lumbar spine were altered by image processing, and pathological structures were added to the images for the FFE experiment. The images were printed to film and evaluated by seven European expert radiologists using VGA and FFE. The results of these two different methods showed a very good agreement. VGA methodology can be made as solid as the FFE experiment for evaluating image quality. The simplicity of VGA makes it very suitable for implementation in clinical practice. (author)

  10. 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

  11. 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.

  12. An Image Registration Method for Colposcopic Images

    Directory of Open Access Journals (Sweden)

    Efrén Mezura-Montes

    2013-01-01

    sequence and a division of such image into small windows. A search process is then carried out to find the window with the highest affinity in each image of the sequence and replace it with the window in the reference image. The affinity value is based on polynomial approximation of the time series computed and the search is bounded by a search radius which defines the neighborhood of each window. The proposed approach is tested in ten 310-frame real cases in two experiments: the first one to determine the best values for the window size and the search radius and the second one to compare the best obtained results with respect to four registration methods found in the specialized literature. The obtained results show a robust and competitive performance of the proposed approach with a significant lower time with respect to the compared methods.

  13. A method of evaluating facial pores using optical 2D images and analysis of age-dependent changes in facial pores in Koreans.

    Science.gov (United States)

    Jang, S I; Kim, E J; Lee, H K

    2018-05-01

    Enlarged facial pores and changes in pore area are of concern for cosmetic reasons. To evaluate pores, measuring tools based on 3D methodology are used. Yet, these methods are limited by their measuring ranges. In this study, we performed pore analysis by measuring the whole face using 2D optical images. We further sought to understand how the pores of Korean women change with age. One hundred sixteen Korean female subjects aged 20-60 years were recruited for this study. Facial images were taken using the VISIA-CR ® adjusted light source. Images were processed using Image-Pro Plus 9.2. Statistical significance was assumed when P pore area, as indicated by pixel count, gradually increased in patients through their 40s, but decreased through their 50s and 60s. Facial pores generally exhibited directionality through the patients' 30s, but this isotropic feature was more prominent in their 50s. Pore elongation increased stepwise. The first increase occurred during the transition from patients' 30s to their 40s and the second increase occurred during the transition from patients' 50s to their 60s. This indicated that the pores deformed from a circular shape to a long elliptic shape over time. A new evaluation method using 2D optical images facilitates the analysis of pore distribution and elongation throughout the entire cheek. This is an improvement over an analysis of pores over a narrow region of interest. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. Two-dimensional imaging of Debye-Scherrer ring for tri-axial stress analysis of industrial materials

    International Nuclear Information System (INIS)

    Sasaki, T; Maruyama, Y; Ohba, H; Ejiri, S

    2014-01-01

    In this study, an application of the two-dimensional imaging technology to the X ray tri-axial stress analysis was studied. An image plate (IP) was used to obtain a Debye-Scherre ring and the image data was analized for determining stress. A new principle for stress analysis which is suitable to two-dimensional imaging data was used. For the verification of this two-dimensional imaging type X-ray stress measurement method, an experiment was conducted using a ferritic steel sample which was processed with a surface grinder. Tri-axial stress analysis was conducted to evaluate the sample. The conventional method for X-ray tri-axial stress analysis proposed by Dölle and Hauk was used to evaluate residual stress in order to compare with the present method. As a result, it was confirmed that a sufficiently highly precise and high-speed stress measurement was enabled with the two-dimensional imaging technology compared with the conventional method

  15. 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.

  16. 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...

  17. 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.

  18. 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.

  19. Feasibility analysis of high resolution tissue image registration using 3-D synthetic data

    Directory of Open Access Journals (Sweden)

    Yachna Sharma

    2011-01-01

    Full Text Available Background: Registration of high-resolution tissue images is a critical step in the 3D analysis of protein expression. Because the distance between images (~4-5μm thickness of a tissue section is nearly the size of the objects of interest (~10-20μm cancer cell nucleus, a given object is often not present in both of two adjacent images. Without consistent correspondence of objects between images, registration becomes a difficult task. This work assesses the feasibility of current registration techniques for such images. Methods: We generated high resolution synthetic 3-D image data sets emulating the constraints in real data. We applied multiple registration methods to the synthetic image data sets and assessed the registration performance of three techniques (i.e., mutual information (MI, kernel density estimate (KDE method [1], and principal component analysis (PCA at various slice thicknesses (with increments of 1μm in order to quantify the limitations of each method. Results: Our analysis shows that PCA, when combined with the KDE method based on nuclei centers, aligns images corresponding to 5μm thick sections with acceptable accuracy. We also note that registration error increases rapidly with increasing distance between images, and that the choice of feature points which are conserved between slices improves performance. Conclusions: We used simulation to help select appropriate features and methods for image registration by estimating best-case-scenario errors for given data constraints in histological images. The results of this study suggest that much of the difficulty of stained tissue registration can be reduced to the problem of accurately identifying feature points, such as the center of nuclei.

  20. Bispectral methods of signal processing applications in radar, telecommunications and digital image restoration

    CERN Document Server

    Totsky, Alexander V; Kravchenko, Victor F

    2015-01-01

    By studying applications in radar, telecommunications and digital image restoration, this monograph discusses signal processing techniques based on bispectral methods. Improved robustness against different forms of noise as well as preservation of phase information render this method a valuable alternative to common power-spectrum analysis used in radar object recognition, digital wireless communications, and jitter removal in images.

  1. Deriving Quantitative Crystallographic Information from the Wavelength-Resolved Neutron Transmission Analysis Performed in Imaging Mode

    Directory of Open Access Journals (Sweden)

    Hirotaka Sato

    2017-12-01

    Full Text Available Current status of Bragg-edge/dip neutron transmission analysis/imaging methods is presented. The method can visualize real-space distributions of bulk crystallographic information in a crystalline material over a large area (~10 cm with high spatial resolution (~100 μm. Furthermore, by using suitable spectrum analysis methods for wavelength-dependent neutron transmission data, quantitative visualization of the crystallographic information can be achieved. For example, crystallographic texture imaging, crystallite size imaging and crystalline phase imaging with texture/extinction corrections are carried out by the Rietveld-type (wide wavelength bandwidth profile fitting analysis code, RITS (Rietveld Imaging of Transmission Spectra. By using the single Bragg-edge analysis mode of RITS, evaluations of crystal lattice plane spacing (d-spacing relating to macro-strain and d-spacing distribution’s FWHM (full width at half maximum relating to micro-strain can be achieved. Macro-strain tomography is performed by a new conceptual CT (computed tomography image reconstruction algorithm, the tensor CT method. Crystalline grains and their orientations are visualized by a fast determination method of grain orientation for Bragg-dip neutron transmission spectrum. In this paper, these imaging examples with the spectrum analysis methods and the reliabilities evaluated by optical/electron microscope and X-ray/neutron diffraction, are presented. In addition, the status at compact accelerator driven pulsed neutron sources is also presented.

  2. Improved radionuclide bone imaging agent injection needle withdrawal method can improve image quality

    International Nuclear Information System (INIS)

    Qin Yongmei; Wang Laihao; Zhao Lihua; Guo Xiaogang; Kong Qingfeng

    2009-01-01

    Objective: To investigate the improvement of radionuclide bone imaging agent injection needle withdrawal method on whole body bone scan image quality. Methods: Elbow vein injection syringe needle directly into the bone imaging agent in the routine group of 117 cases, with a cotton swab needle injection method for the rapid pull out the needle puncture point pressing, pressing moment. Improvement of 117 cases of needle injection method to put two needles into the skin swabs and blood vessels, pull out the needle while pressing two or more entry point 5min. After 2 hours underwent whole body bone SPECT imaging plane. Results: The conventional group at the injection site imaging agents uptake rate was 16.24%, improved group was 2.56%. Conclusion: The modified bone imaging agent injection needle withdrawal method, injection-site imaging agent uptake were significantly decreased whole body bone imaging can improve image quality. (authors)

  3. Spatial compression algorithm for the analysis of very large multivariate images

    Science.gov (United States)

    Keenan, Michael R [Albuquerque, NM

    2008-07-15

    A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

  4. Quantitative Nuclear Medicine Imaging: Concepts, Requirements and Methods

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2014-01-15

    The absolute quantification of radionuclide distribution has been a goal since the early days of nuclear medicine. Nevertheless, the apparent complexity and sometimes limited accuracy of these methods have prevented them from being widely used in important applications such as targeted radionuclide therapy or kinetic analysis. The intricacy of the effects degrading nuclear medicine images and the lack of availability of adequate methods to compensate for these effects have frequently been seen as insurmountable obstacles in the use of quantitative nuclear medicine in clinical institutions. In the last few decades, several research groups have consistently devoted their efforts to the filling of these gaps. As a result, many efficient methods are now available that make quantification a clinical reality, provided appropriate compensation tools are used. Despite these efforts, many clinical institutions still lack the knowledge and tools to adequately measure and estimate the accumulated activities in the human body, thereby using potentially outdated protocols and procedures. The purpose of the present publication is to review the current state of the art of image quantification and to provide medical physicists and other related professionals facing quantification tasks with a solid background of tools and methods. It describes and analyses the physical effects that degrade image quality and affect the accuracy of quantification, and describes methods to compensate for them in planar, single photon emission computed tomography (SPECT) and positron emission tomography (PET) images. The fast paced development of the computational infrastructure, both hardware and software, has made drastic changes in the ways image quantification is now performed. The measuring equipment has evolved from the simple blind probes to planar and three dimensional imaging, supported by SPECT, PET and hybrid equipment. Methods of iterative reconstruction have been developed to allow for

  5. Comparative analysis of methods for extracting vessel network on breast MRI images

    Science.gov (United States)

    Gaizer, Bence T.; Vassiou, Katerina G.; Lavdas, Eleftherios; Arvanitis, Dimitrios L.; Fezoulidis, Ioannis V.; Glotsos, Dimitris T.

    2017-11-01

    Digital processing of MRI images aims to provide an automatized diagnostic evaluation of regular health screenings. Cancerous lesions are proven to cause an alteration in the vessel structure of the diseased organ. Currently there are several methods used for extraction of the vessel network in order to quantify its properties. In this work MRI images (Signa HDx 3.0T, GE Healthcare, courtesy of University Hospital of Larissa) of 30 female breasts were subjected to three different vessel extraction algorithms to determine the location of their vascular network. The first method is an experiment to build a graph over known points of the vessel network; the second algorithm aims to determine the direction and diameter of vessels at these points; the third approach is a seed growing algorithm, spreading selection to neighbors of the known vessel pixels. The possibilities shown by the different methods were analyzed, and quantitative measurements were performed. The data provided by these measurements showed no clear correlation with the presence or malignancy of tumors, based on the radiological diagnosis of skilled physicians.

  6. Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

    Directory of Open Access Journals (Sweden)

    Tushar H Jaware

    2013-10-01

    Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

  7. Multifractal analysis of 2D gray soil images

    Science.gov (United States)

    González-Torres, Ivan; Losada, Juan Carlos; Heck, Richard; Tarquis, Ana M.

    2015-04-01

    Soil structure, understood as the spatial arrangement of soil pores, is one of the key factors in soil modelling processes. Geometric properties of individual and interpretation of the morphological parameters of pores can be estimated from thin sections or 3D Computed Tomography images (Tarquis et al., 2003), but there is no satisfactory method to binarized these images and quantify the complexity of their spatial arrangement (Tarquis et al., 2008, Tarquis et al., 2009; Baveye et al., 2010). The objective of this work was to apply a multifractal technique, their singularities (α) and f(α) spectra, to quantify it without applying any threshold (Gónzalez-Torres, 2014). Intact soil samples were collected from four horizons of an Argisol, formed on the Tertiary Barreiras group of formations in Pernambuco state, Brazil (Itapirema Experimental Station). The natural vegetation of the region is tropical, coastal rainforest. From each horizon, showing different porosities and spatial arrangements, three adjacent samples were taken having a set of twelve samples. The intact soil samples were imaged using an EVS (now GE Medical. London, Canada) MS-8 MicroCT scanner with 45 μm pixel-1 resolution (256x256 pixels). Though some samples required paring to fit the 64 mm diameter imaging tubes, field orientation was maintained. References Baveye, P.C., M. Laba, W. Otten, L. Bouckaert, P. Dello, R.R. Goswami, D. Grinev, A. Houston, Yaoping Hu, Jianli Liu, S. Mooney, R. Pajor, S. Sleutel, A. Tarquis, Wei Wang, Qiao Wei, Mehmet Sezgin. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data. Geoderma, 157, 51-63, 2010. González-Torres, Iván. Theory and application of multifractal analysis methods in images for the study of soil structure. Master thesis, UPM, 2014. Tarquis, A.M., R.J. Heck, J.B. Grau; J. Fabregat, M.E. Sanchez and J.M. Antón. Influence of Thresholding in Mass and Entropy Dimension of 3-D

  8. An imaging method of wavefront coding system based on phase plate rotation

    Science.gov (United States)

    Yi, Rigui; Chen, Xi; Dong, Liquan; Liu, Ming; Zhao, Yuejin; Liu, Xiaohua

    2018-01-01

    Wave-front coding has a great prospect in extending the depth of the optical imaging system and reducing optical aberrations, but the image quality and noise performance are inevitably reduced. According to the theoretical analysis of the wave-front coding system and the phase function expression of the cubic phase plate, this paper analyzed and utilized the feature that the phase function expression would be invariant in the new coordinate system when the phase plate rotates at different angles around the z-axis, and we proposed a method based on the rotation of the phase plate and image fusion. First, let the phase plate rotated at a certain angle around the z-axis, the shape and distribution of the PSF obtained on the image surface remain unchanged, the rotation angle and direction are consistent with the rotation angle of the phase plate. Then, the middle blurred image is filtered by the point spread function of the rotation adjustment. Finally, the reconstruction images were fused by the method of the Laplacian pyramid image fusion and the Fourier transform spectrum fusion method, and the results were evaluated subjectively and objectively. In this paper, we used Matlab to simulate the images. By using the Laplacian pyramid image fusion method, the signal-to-noise ratio of the image is increased by 19% 27%, the clarity is increased by 11% 15% , and the average gradient is increased by 4% 9% . By using the Fourier transform spectrum fusion method, the signal-to-noise ratio of the image is increased by 14% 23%, the clarity is increased by 6% 11% , and the average gradient is improved by 2% 6%. The experimental results show that the image processing by the above method can improve the quality of the restored image, improving the image clarity, and can effectively preserve the image information.

  9. 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.

  10. 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.

  11. Evaluation of methods for MR imaging of human right ventricular heart volumes and mass

    International Nuclear Information System (INIS)

    Jauhiainen, T.; Jaervinen, V.M.; Hekali, P.E.

    2002-01-01

    Purpose: To assess the utility of two different imaging directions in the evaluation of human right ventricular (RV) heart volumes and mass with MR imaging; to compare breath-hold vs. non-breath-hold imaging in volume analysis; and to compare turbo inversion recovery imaging (TIR) with gradient echo imaging in RV mass measurement. Material and Methods: We examined 12 healthy volunteers (age 27-59 years). Breath-hold gradient echo MR imaging was performed in two imaging planes: 1) perpendicular to the RV inflow tract (RVIT view), and 2) in the transaxial view (TA view). The imaging was repeated in the TA view while the subjects were breathing freely. To analyze RV mass using TIR images, the RV was again imaged at end-diastole using the two views. The RV end-diastolic cavity (RVEDV) and muscle volume as well as end-systolic cavity volume (RVESV) were determined with the method of discs. All measurements were done blindly twice to assess repeatability of image analysis. To assess reproducibility of the measurements, 6 of the subjects were imaged twice at an interval of 5-9 weeks. Results: RVEDV averaged 133.2 ml, RVESV 61.5 ml and the RVmass 46.2 g in the RVIT view and 119.9 ml, 56.9 ml and 38.3 g in the TA view, respectively. The volumes obtained with breath-holding were slightly but not significantly smaller than the volumes obtained during normal breathing. There were no marked differences in the RV muscle mass obtained with gradient echo imaging compared to TIR imaging in either views. Repeatability of volume analysis was better in TA than RVIT view: the mean differences were 0.7±4.0 ml and 5.4±14.0 ml in end-diastole and 1.6±3.1 ml and 1.5±13.9 ml in end-systole, respectively. Repeatability of mass analysis was good in both TIR and cine images in the RVIT view but slightly better in TIR images: 0.5±2.4 g compared to 0.8±2.9 g in cine images. Reproducibility of imaging was good, mean differences for RVEDV and RVESV were 1.0±4.8 ml and 0.8±2.8 ml

  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. 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

  14. 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....

  15. Progression Analysis and Stage Discovery in Continuous Physiological Processes Using Image Computing

    Directory of Open Access Journals (Sweden)

    Ferrucci Luigi

    2010-01-01

    Full Text Available We propose an image computing-based method for quantitative analysis of continuous physiological processes that can be sensed by medical imaging and demonstrate its application to the analysis of morphological alterations of the bone structure, which correlate with the progression of osteoarthritis (OA. The purpose of the analysis is to quantitatively estimate OA progression in a fashion that can assist in understanding the pathophysiology of the disease. Ultimately, the texture analysis will be able to provide an alternative OA scoring method, which can potentially reflect the progression of the disease in a more direct fashion compared to the existing clinically utilized classification schemes based on radiology. This method can be useful not just for studying the nature of OA, but also for developing and testing the effect of drugs and treatments. While in this paper we demonstrate the application of the method to osteoarthritis, its generality makes it suitable for the analysis of other progressive clinical conditions that can be diagnosed and prognosed by using medical imaging.

  16. 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

  17. Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations.

    Science.gov (United States)

    Midulla, Marco; Moreno, Ramiro; Baali, Adil; Chau, Ming; Negre-Salvayre, Anne; Nicoud, Franck; Pruvo, Jean-Pierre; Haulon, Stephan; Rousseau, Hervé

    2012-10-01

    In the last decade, there was been increasing interest in finding imaging techniques able to provide a functional vascular imaging of the thoracic aorta. The purpose of this paper is to present an imaging method combining magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) to obtain a patient-specific haemodynamic analysis of patients treated by thoracic endovascular aortic repair (TEVAR). MRI was used to obtain boundary conditions. MR angiography (MRA) was followed by cardiac-gated cine sequences which covered the whole thoracic aorta. Phase contrast imaging provided the inlet and outlet profiles. A CFD mesh generator was used to model the arterial morphology, and wall movements were imposed according to the cine imaging. CFD runs were processed using the finite volume (FV) method assuming blood as a homogeneous Newtonian fluid. Twenty patients (14 men; mean age 62.2 years) with different aortic lesions were evaluated. Four-dimensional mapping of velocity and wall shear stress were obtained, depicting different patterns of flow (laminar, turbulent, stenosis-like) and local alterations of parietal stress in-stent and along the native aorta. A computational method using a combined approach with MRI appears feasible and seems promising to provide detailed functional analysis of thoracic aorta after stent-graft implantation. • Functional vascular imaging of the thoracic aorta offers new diagnostic opportunities • CFD can model vascular haemodynamics for clinical aortic problems • Combining CFD with MRI offers patient specific method of aortic analysis • Haemodynamic analysis of stent-grafts could improve clinical management and follow-up.

  18. OpenComet: An automated tool for comet assay image analysis

    Directory of Open Access Journals (Sweden)

    Benjamin M. Gyori

    2014-01-01

    Full Text Available Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.

  19. 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...

  20. A new method using multiphoton imaging and morphometric analysis for differentiating chromophobe renal cell carcinoma and oncocytoma kidney tumors

    Science.gov (United States)

    Wu, Binlin; Mukherjee, Sushmita; Jain, Manu

    2016-03-01

    Distinguishing chromophobe renal cell carcinoma (chRCC) from oncocytoma on hematoxylin and eosin images may be difficult and require time-consuming ancillary procedures. Multiphoton microscopy (MPM), an optical imaging modality, was used to rapidly generate sub-cellular histological resolution images from formalin-fixed unstained tissue sections from chRCC and oncocytoma.Tissues were excited using 780nm wavelength and emission signals (including second harmonic generation and autofluorescence) were collected in different channels between 390 nm and 650 nm. Granular structure in the cell cytoplasm was observed in both chRCC and oncocytoma. Quantitative morphometric analysis was conducted to distinguish chRCC and oncocytoma. To perform the analysis, cytoplasm and granules in tumor cells were segmented from the images. Their area and fluorescence intensity were found in different channels. Multiple features were measured to quantify the morphological and fluorescence properties. Linear support vector machine (SVM) was used for classification. Re-substitution validation, cross validation and receiver operating characteristic (ROC) curve were implemented to evaluate the efficacy of the SVM classifier. A wrapper feature algorithm was used to select the optimal features which provided the best predictive performance in separating the two tissue types (classes). Statistical measures such as sensitivity, specificity, accuracy and area under curve (AUC) of ROC were calculated to evaluate the efficacy of the classification. Over 80% accuracy was achieved as the predictive performance. This method, if validated on a larger and more diverse sample set, may serve as an automated rapid diagnostic tool to differentiate between chRCC and oncocytoma. An advantage of such automated methods are that they are free from investigator bias and variability.

  1. Impact of PET/CT image reconstruction methods and liver uptake normalization strategies on quantitative image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kuhnert, Georg; Sterzer, Sergej; Kahraman, Deniz; Dietlein, Markus; Drzezga, Alexander; Kobe, Carsten [University Hospital of Cologne, Department of Nuclear Medicine, Cologne (Germany); Boellaard, Ronald [VU University Medical Centre, Department of Radiology and Nuclear Medicine, Amsterdam (Netherlands); Scheffler, Matthias; Wolf, Juergen [University Hospital of Cologne, Lung Cancer Group Cologne, Department I of Internal Medicine, Center for Integrated Oncology Cologne Bonn, Cologne (Germany)

    2016-02-15

    In oncological imaging using PET/CT, the standardized uptake value has become the most common parameter used to measure tracer accumulation. The aim of this analysis was to evaluate ultra high definition (UHD) and ordered subset expectation maximization (OSEM) PET/CT reconstructions for their potential impact on quantification. We analyzed 40 PET/CT scans of lung cancer patients who had undergone PET/CT. Standardized uptake values corrected for body weight (SUV) and lean body mass (SUL) were determined in the single hottest lesion in the lung and normalized to the liver for UHD and OSEM reconstruction. Quantitative uptake values and their normalized ratios for the two reconstruction settings were compared using the Wilcoxon test. The distribution of quantitative uptake values and their ratios in relation to the reconstruction method used were demonstrated in the form of frequency distribution curves, box-plots and scatter plots. The agreement between OSEM and UHD reconstructions was assessed through Bland-Altman analysis. A significant difference was observed after OSEM and UHD reconstruction for SUV and SUL data tested (p < 0.0005 in all cases). The mean values of the ratios after OSEM and UHD reconstruction showed equally significant differences (p < 0.0005 in all cases). Bland-Altman analysis showed that the SUV and SUL and their normalized values were, on average, up to 60 % higher after UHD reconstruction as compared to OSEM reconstruction. OSEM and HD reconstruction brought a significant difference for SUV and SUL, which remained constantly high after normalization to the liver, indicating that standardization of reconstruction and the use of comparable SUV measurements are crucial when using PET/CT. (orig.)

  2. An age estimation method using brain local features for T1-weighted images.

    Science.gov (United States)

    Kondo, Chihiro; Ito, Koichi; Kai Wu; Sato, Kazunori; Taki, Yasuyuki; Fukuda, Hiroshi; Aoki, Takafumi

    2015-08-01

    Previous statistical analysis studies using large-scale brain magnetic resonance (MR) image databases have examined that brain tissues have age-related morphological changes. This fact indicates that one can estimate the age of a subject from his/her brain MR image by evaluating morphological changes with healthy aging. This paper proposes an age estimation method using local features extracted from T1-weighted MR images. The brain local features are defined by volumes of brain tissues parcellated into local regions defined by the automated anatomical labeling atlas. The proposed method selects optimal local regions to improve the performance of age estimation. We evaluate performance of the proposed method using 1,146 T1-weighted images from a Japanese MR image database. We also discuss the medical implication of selected optimal local regions.

  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. An automated image analysis system to measure and count organisms in laboratory microcosms.

    Directory of Open Access Journals (Sweden)

    François Mallard

    Full Text Available 1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms.

  6. Digital image envelope: method and evaluation

    Science.gov (United States)

    Huang, H. K.; Cao, Fei; Zhou, Michael Z.; Mogel, Greg T.; Liu, Brent J.; Zhou, Xiaoqiang

    2003-05-01

    Health data security, characterized in terms of data privacy, authenticity, and integrity, is a vital issue when digital images and other patient information are transmitted through public networks in telehealth applications such as teleradiology. Mandates for ensuring health data security have been extensively discussed (for example The Health Insurance Portability and Accountability Act, HIPAA) and health informatics guidelines (such as the DICOM standard) are beginning to focus on issues of data continue to be published by organizing bodies in healthcare; however, there has not been a systematic method developed to ensure data security in medical imaging Because data privacy and authenticity are often managed primarily with firewall and password protection, we have focused our research and development on data integrity. We have developed a systematic method of ensuring medical image data integrity across public networks using the concept of the digital envelope. When a medical image is generated regardless of the modality, three processes are performed: the image signature is obtained, the DICOM image header is encrypted, and a digital envelope is formed by combining the signature and the encrypted header. The envelope is encrypted and embedded in the original image. This assures the security of both the image and the patient ID. The embedded image is encrypted again and transmitted across the network. The reverse process is performed at the receiving site. The result is two digital signatures, one from the original image before transmission, and second from the image after transmission. If the signatures are identical, there has been no alteration of the image. This paper concentrates in the method and evaluation of the digital image envelope.

  7. 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

  8. On the Importance of Mathematical Methods for Analysis of MALDI-Imaging Mass Spectrometry Data

    Directory of Open Access Journals (Sweden)

    Trede Dennis

    2012-03-01

    Full Text Available In the last decade, matrix-assisted laser desorption/ionization (MALDI imaging mass spectrometry (IMS, also called as MALDI-imaging, has proven its potential in proteomics and was successfully applied to various types of biomedical problems, in particular to histopathological label-free analysis of tissue sections. In histopathology, MALDI-imaging is used as a general analytic tool revealing the functional proteomic structure of tissue sections, and as a discovery tool for detecting new biomarkers discriminating a region annotated by an experienced histologist, in particular, for cancer studies.

  9. Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

    Science.gov (United States)

    Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

    2017-12-01

    In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

  10. 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.

  11. 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.

  12. 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

  13. A novel method of estimating dose responses for polymer gels using texture analysis of scanning electron microscopy images.

    Directory of Open Access Journals (Sweden)

    Cheng-Ting Shih

    Full Text Available Polymer gels are regarded as a potential dosimeter for independent validation of absorbed doses in clinical radiotherapy. Several imaging modalities have been used to convert radiation-induced polymerization to absorbed doses from a macro-scale viewpoint. This study developed a novel dose conversion mechanism by texture analysis of scanning electron microscopy (SEM images. The modified N-isopropyl-acrylamide (NIPAM gels were prepared under normoxic conditions, and were administered radiation doses from 5 to 20 Gy. After freeze drying, the gel samples were sliced for SEM scanning with 50×, 500×, and 3500× magnifications. Four texture indices were calculated based on the gray level co-occurrence matrix (GLCM. The results showed that entropy and homogeneity were more suitable than contrast and energy as dose indices for higher linearity and sensitivity of the dose response curves. After parameter optimization, an R (2 value of 0.993 can be achieved for homogeneity using 500× magnified SEM images with 27 pixel offsets and no outlier exclusion. For dose verification, the percentage errors between the prescribed dose and the measured dose for 5, 10, 15, and 20 Gy were -7.60%, 5.80%, 2.53%, and -0.95%, respectively. We conclude that texture analysis can be applied to the SEM images of gel dosimeters to accurately convert micro-scale structural features to absorbed doses. The proposed method may extend the feasibility of applying gel dosimeters in the fields of diagnostic radiology and radiation protection.

  14. Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.

    Science.gov (United States)

    Matelsky, Jordan; Kiar, Gregory; Johnson, Erik; Rivera, Corban; Toma, Michael; Gray-Roncal, William

    2018-05-08

    Medical imaging analysis depends on the reproducibility of complex computation. Linux containers enable the abstraction, installation, and configuration of environments so that software can be both distributed in self-contained images and used repeatably by tool consumers. While several initiatives in neuroimaging have adopted approaches for creating and sharing more reliable scientific methods and findings, Linux containers are not yet mainstream in clinical settings. We explore related technologies and their efficacy in this setting, highlight important shortcomings, demonstrate a simple use-case, and endorse the use of Linux containers for medical image analysis.

  15. An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images.

    Science.gov (United States)

    Cavalcanti, Pablo G; Scharcanski, Jacob; Di Persia, Leandro E; Milone, Diego H

    2011-01-01

    Segmentation is an important step in computer-aided diagnostic systems for pigmented skin lesions, since that a good definition of the lesion area and its boundary at the image is very important to distinguish benign from malignant cases. In this paper a new skin lesion segmentation method is proposed. This method uses Independent Component Analysis to locate skin lesions in the image, and this location information is further refined by a Level-set segmentation method. Our method was evaluated in 141 images and achieved an average segmentation error of 16.55%, lower than the results for comparable state-of-the-art methods proposed in literature.

  16. Progress toward the development and testing of source reconstruction methods for NIF neutron imaging.

    Science.gov (United States)

    Loomis, E N; Grim, G P; Wilde, C; Wilson, D C; Morgan, G; Wilke, M; Tregillis, I; Merrill, F; Clark, D; Finch, J; Fittinghoff, D; Bower, D

    2010-10-01

    Development of analysis techniques for neutron imaging at the National Ignition Facility is an important and difficult task for the detailed understanding of high-neutron yield inertial confinement fusion implosions. Once developed, these methods must provide accurate images of the hot and cold fuels so that information about the implosion, such as symmetry and areal density, can be extracted. One method under development involves the numerical inversion of the pinhole image using knowledge of neutron transport through the pinhole aperture from Monte Carlo simulations. In this article we present results of source reconstructions based on simulated images that test the methods effectiveness with regard to pinhole misalignment.

  17. X-ray photon-in/photon-out methods for chemical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Marcus, Matthew A.

    2010-03-24

    Most interesting materials in nature are heterogeneous, so it is useful to have analytical techniques with spatial resolution sufficient to resolve these heterogeneities.This article presents the basics of X-ray photon-in/photon-out chemical imaging. This family of methods allows one to derive images reflectingthe chemical state of a given element in a complex sample, at micron or deep sub-micron scale. X-ray chemical imaging is relatively non-destructiveand element-selective, and requires minimal sample preparation. The article presents the basic concepts and some considerations of data takingand data analysis, along with some examples.

  18. Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

    Science.gov (United States)

    Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

    2017-03-01

    Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

  19. The application of computer image analysis in life sciences and environmental engineering

    Science.gov (United States)

    Mazur, R.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.; Boniecki, P.; Mueller, W.; Raba, B.

    2014-04-01

    The main aim of the article was to present research on the application of computer image analysis in Life Science and Environmental Engineering. The authors used different methods of computer image analysis in developing of an innovative biotest in modern biomonitoring of water quality. Created tools were based on live organisms such as bioindicators Lemna minor L. and Hydra vulgaris Pallas as well as computer image analysis method in the assessment of negatives reactions during the exposition of the organisms to selected water toxicants. All of these methods belong to acute toxicity tests and are particularly essential in ecotoxicological assessment of water pollutants. Developed bioassays can be used not only in scientific research but are also applicable in environmental engineering and agriculture in the study of adverse effects on water quality of various compounds used in agriculture and industry.

  20. Apparatus and method X-ray image processing

    International Nuclear Information System (INIS)

    1984-01-01

    The invention relates to a method for X-ray image processing. The radiation passed through the object is transformed into an electric image signal from which the logarithmic value is determined and displayed by a display device. Its main objective is to provide a method and apparatus that renders X-ray images or X-ray subtraction images with strong reduction of stray radiation. (Auth.)

  1. 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.

  2. 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

  3. The use of artificial intelligence methods for visual analysis of properties of surface layers

    Directory of Open Access Journals (Sweden)

    Tomasz Wójcicki

    2014-12-01

    Full Text Available [b]Abstract[/b]. The article presents a selected area of research on the possibility of automatic prediction of material properties based on the analysis of digital images. Original, holistic model of forecasting properties of surface layers based on a multi-step process that includes the selected methods of processing and analysis of images, inference with the use of a priori knowledge bases and multi-valued fuzzy logic, and simulation with the use of finite element methods is presented. Surface layers characteristics and core technologies of their production processes such as mechanical, thermal, thermo-mechanical, thermo-chemical, electrochemical, physical are discussed. Developed methods used in the model for the classification of images of the surface layers are shown. The objectives of the use of selected methods of processing and analysis of digital images, including techniques for improving the quality of images, segmentation, morphological transformation, pattern recognition and simulation of physical phenomena in the structures of materials are described.[b]Keywords[/b]: image analysis, surface layer, artificial intelligence, fuzzy logic

  4. A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS

    Directory of Open Access Journals (Sweden)

    Taiji Lan

    2017-10-01

    Full Text Available The digital time delay integration (digital TDI technology of the complementary metal-oxide-semiconductor (CMOS image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low illumination or low contrast in scenarios of high contrast are often drowned out because of the superposition of multi-stage images in digital domain multiplies the read noise and the dark noise, thus limiting the imaging dynamic range. Through an in-depth analysis of the information transfer model of digital TDI, this paper attempts to explore effective ways to overcome this issue. Based on the evaluation and analysis of multi-stage images, the entropy-maximized adaptive histogram equalization (EMAHE algorithm is proposed to improve the ability of images to express the details of dark or low-contrast targets. Furthermore, in this paper, an image fusion method is utilized based on gradient pyramid decomposition and entropy weighting of different TDI stage images, which can improve the detection ability of the digital TDI CMOS for complex scenes with high contrast, and obtain images that are suitable for recognition by the human eye. The experimental results show that the proposed methods can effectively improve the high-dynamic-range imaging (HDRI capability of the digital TDI CMOS. The obtained images have greater entropy and average gradients.

  5. A psychophysical imaging method evidencing auditory cue extraction during speech perception: a group analysis of auditory classification images.

    Science.gov (United States)

    Varnet, Léo; Knoblauch, Kenneth; Serniclaes, Willy; Meunier, Fanny; Hoen, Michel

    2015-01-01

    Although there is a large consensus regarding the involvement of specific acoustic cues in speech perception, the precise mechanisms underlying the transformation from continuous acoustical properties into discrete perceptual units remains undetermined. This gap in knowledge is partially due to the lack of a turnkey solution for isolating critical speech cues from natural stimuli. In this paper, we describe a psychoacoustic imaging method known as the Auditory Classification Image technique that allows experimenters to estimate the relative importance of time-frequency regions in categorizing natural speech utterances in noise. Importantly, this technique enables the testing of hypotheses on the listening strategies of participants at the group level. We exemplify this approach by identifying the acoustic cues involved in da/ga categorization with two phonetic contexts, Al- or Ar-. The application of Auditory Classification Images to our group of 16 participants revealed significant critical regions on the second and third formant onsets, as predicted by the literature, as well as an unexpected temporal cue on the first formant. Finally, through a cluster-based nonparametric test, we demonstrate that this method is sufficiently sensitive to detect fine modifications of the classification strategies between different utterances of the same phoneme.

  6. Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

    Science.gov (United States)

    Borodinov, A. A.; Myasnikov, V. V.

    2018-04-01

    The present work is devoted to comparing the accuracy of the known qualification algorithms in the task of recognizing local objects on radar images for various image preprocessing methods. Preprocessing involves speckle noise filtering and normalization of the object orientation in the image by the method of image moments and by a method based on the Hough transform. In comparison, the following classification algorithms are used: Decision tree; Support vector machine, AdaBoost, Random forest. The principal component analysis is used to reduce the dimension. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.

  7. Technical considerations on scanning and image analysis for amyloid PET in dementia

    International Nuclear Information System (INIS)

    Akamatsu, Go; Ohnishi, Akihito; Aita, Kazuki; Ikari, Yasuhiko; Senda, Michio; Yamamoto, Yasuji

    2017-01-01

    Brain imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), and positron emission tomography (PET), can provide essential and objective information for the early and differential diagnosis of dementia. Amyloid PET is especially useful to evaluate the amyloid-β pathological process as a biomarker of Alzheimer's disease. This article reviews critical points about technical considerations on the scanning and image analysis methods for amyloid PET. Each amyloid PET agent has its own proper administration instructions and recommended uptake time, scan duration, and the method of image display and interpretation. In addition, we have introduced general scanning information, including subject positioning, reconstruction parameters, and quantitative and statistical image analysis. We believe that this article could make amyloid PET a more reliable tool in clinical study and practice. (author)

  8. Technical Considerations on Scanning and Image Analysis for Amyloid PET in Dementia.

    Science.gov (United States)

    Akamatsu, Go; Ohnishi, Akihito; Aita, Kazuki; Ikari, Yasuhiko; Yamamoto, Yasuji; Senda, Michio

    2017-01-01

    Brain imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), and positron emission tomography (PET), can provide essential and objective information for the early and differential diagnosis of dementia. Amyloid PET is especially useful to evaluate the amyloid-β pathological process as a biomarker of Alzheimer's disease. This article reviews critical points about technical considerations on the scanning and image analysis methods for amyloid PET. Each amyloid PET agent has its own proper administration instructions and recommended uptake time, scan duration, and the method of image display and interpretation. In addition, we have introduced general scanning information, including subject positioning, reconstruction parameters, and quantitative and statistical image analysis. We believe that this article could make amyloid PET a more reliable tool in clinical study and practice.

  9. Quantitative analysis of elastography images in the detection of breast cancer

    International Nuclear Information System (INIS)

    Landoni, V.; Francione, V.; Marzi, S.; Pasciuti, K.; Ferrante, F.; Saracca, E.; Pedrini, M.; Strigari, L.; Crecco, M.; Di Nallo, A.

    2012-01-01

    Purpose: The aim of this study was to develop a quantitative method for breast cancer diagnosis based on elastosonography images in order to reduce whenever possible unnecessary biopsies. The proposed method was validated by correlating the results of quantitative analysis with the diagnosis assessed by histopathologic exam. Material and methods: 109 images of breast lesions (50 benign and 59 malignant) were acquired with the traditional B-mode technique and with elastographic modality. Images in Digital Imaging and COmmunications in Medicine format (DICOM) were exported into a software, written in Visual Basic, especially developed to perform this study. The lesion was contoured and the mean grey value and softness inside the region of interest (ROI) were calculated. The correlations between variables were investigated and receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of the proposed method. Pathologic results were used as standard reference. Results: Both the mean grey value and the softness inside the ROI resulted statistically different at the t test for the two populations of lesions (i.e., benign versus malignant): p < 0.0001. The area under the curve (AUC) was 0.924 (0.834–0.973) and 0.917 (0.826–0.970) for the mean grey value and for the softness respectively. Conclusions: Quantitative elastosonography is a promising ultrasound technique in the detection of breast cancer but large prospective trials are necessary to determine whether quantitative analysis of images can help to overcome some pitfalls of the methodic.

  10. Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles

    NARCIS (Netherlands)

    Laksmana, F.L.; Van Vliet, L.J.; Hartman Kok, P.J.A.; Vromans, H.; Frijlink, H.W.; Van der Voort Maarschalk, K.

    2008-01-01

    Purpose This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. Methods The method applies the MATLAB image processing toolbox to images of coated

  11. A NEW IMAGE REGISTRATION METHOD FOR GREY IMAGES

    Institute of Scientific and Technical Information of China (English)

    Nie Xuan; Zhao Rongchun; Jiang Zetao

    2004-01-01

    The proposed algorithm relies on a group of new formulas for calculating tangent slope so as to address angle feature of edge curves of image. It can utilize tangent angle features to estimate automatically and fully the rotation parameters of geometric transform and enable rough matching of images with huge rotation difference. After angle compensation, it can search for matching point sets by correlation criterion, then calculate parameters of affine transform, enable higher-precision emendation of rotation and transferring. Finally, it fulfills precise matching for images with relax-tense iteration method. Compared with the registration approach based on wavelet direction-angle features, the matching algorithm with tangent feature of image edge is more robust and realizes precise registration of various images. Furthermore, it is also helpful in graphics matching.

  12. Enhancing the (MSLDIP) image steganographic method (ESLDIP method)

    Science.gov (United States)

    Seddik Saad, Al-hussien

    2011-10-01

    Message transmissions over the Internet still have data security problem. Therefore, secure and secret communication methods are needed for transmitting messages over the Internet. Cryptography scrambles the message so that it cannot be understood. However, it makes the message suspicious enough to attract eavesdropper's attention. Steganography hides the secret message within other innocuous-looking cover files (i.e. images, music and video files) so that it cannot be observed [1].The term steganography originates from the Greek root words "steganos'' and "graphein'' which literally mean "covered writing''. It is defined as the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio text and video files [3].Steganographic techniques allow one party to communicate information to another without a third party even knowing that the communication is occurring. The ways to deliver these "secret messages" vary greatly [3].Our proposed method called Enhanced SLDIP (ESLDIP). In which the maximmum hiding capacity (MHC) of proposed ESLDIP method is higher than the previously proposed MSLDIP methods and the PSNR of the ESLDIP method is higher than the MSLDIP PSNR values', which means that the image quality of the ESLDIP method will be better than MSLDIP method and the maximmum hiding capacity (MHC) also improved. The rest of this paper is organized as follows. In section 2, steganography has been discussed; lingo, carriers and types. In section 3, related works are introduced. In section 4, the proposed method will be discussed in details. In section 5, the simulation results are given and Section 6 concludes the paper.

  13. A comparative study of 2 computer-assisted methods of quantifying brightfield microscopy images.

    Science.gov (United States)

    Tse, George H; Marson, Lorna P

    2013-10-01

    Immunohistochemistry continues to be a powerful tool for the detection of antigens. There are several commercially available software packages that allow image analysis; however, these can be complex, require relatively high level of computer skills, and can be expensive. We compared 2 commonly available software packages, Adobe Photoshop CS6 and ImageJ, in their ability to quantify percentage positive area after picrosirius red (PSR) staining and 3,3'-diaminobenzidine (DAB) staining. On analysis of DAB-stained B cells in the mouse spleen, with a biotinylated primary rat anti-mouse-B220 antibody, there was no significant difference on converting images from brightfield microscopy to binary images to measure black and white pixels using ImageJ compared with measuring a range of brown pixels with Photoshop (Student t test, P=0.243, correlation r=0.985). When analyzing mouse kidney allografts stained with PSR, Photoshop achieved a greater interquartile range while maintaining a lower 10th percentile value compared with analysis with ImageJ. A lower 10% percentile reflects that Photoshop analysis is better at analyzing tissues with low levels of positive pixels; particularly relevant for control tissues or negative controls, whereas after ImageJ analysis the same images would result in spuriously high levels of positivity. Furthermore comparing the 2 methods by Bland-Altman plot revealed that these 2 methodologies did not agree when measuring images with a higher percentage of positive staining and correlation was poor (r=0.804). We conclude that for computer-assisted analysis of images of DAB-stained tissue there is no difference between using Photoshop or ImageJ. However, for analysis of color images where differentiation into a binary pattern is not easy, such as with PSR, Photoshop is superior at identifying higher levels of positivity while maintaining differentiation of low levels of positive staining.

  14. Numerical methods for image registration

    CERN Document Server

    Modersitzki, Jan

    2003-01-01

    Based on the author's lecture notes and research, this well-illustrated and comprehensive text is one of the first to provide an introduction to image registration with particular emphasis on numerical methods in medical imaging. Ideal for researchers in industry and academia, it is also a suitable study guide for graduate mathematicians, computer scientists, engineers, medical physicists, and radiologists.Image registration is utilised whenever information obtained from different viewpoints needs to be combined or compared and unwanted distortion needs to be eliminated. For example, CCTV imag

  15. [Research on fast implementation method of image Gaussian RBF interpolation based on CUDA].

    Science.gov (United States)

    Chen, Hao; Yu, Haizhong

    2014-04-01

    Image interpolation is often required during medical image processing and analysis. Although interpolation method based on Gaussian radial basis function (GRBF) has high precision, the long calculation time still limits its application in field of image interpolation. To overcome this problem, a method of two-dimensional and three-dimensional medical image GRBF interpolation based on computing unified device architecture (CUDA) is proposed in this paper. According to single instruction multiple threads (SIMT) executive model of CUDA, various optimizing measures such as coalesced access and shared memory are adopted in this study. To eliminate the edge distortion of image interpolation, natural suture algorithm is utilized in overlapping regions while adopting data space strategy of separating 2D images into blocks or dividing 3D images into sub-volumes. Keeping a high interpolation precision, the 2D and 3D medical image GRBF interpolation achieved great acceleration in each basic computing step. The experiments showed that the operative efficiency of image GRBF interpolation based on CUDA platform was obviously improved compared with CPU calculation. The present method is of a considerable reference value in the application field of image interpolation.

  16. Improved Method of Detection Falsification Results the Digital Image in Conditions of Attacks

    Directory of Open Access Journals (Sweden)

    Kobozeva A.A.

    2016-08-01

    Full Text Available The modern level of information technologies development has led to unheard ease embodiments hitherto unauthorized modifications of digital content. At the moment, very important question is the effective expert examination of authenticity of digital images, video, audio, development of the methods for identification and localization of violations of their integrity using these contents for purposes other than entertainment. Present paper deals with the improvement of the detection method of the cloning results in digital images - one of the most frequently used in the software tools falsification realized in all modern graphics editors. The method is intended for clone detection areas and pre-image in terms of additional disturbing influences in the image after the cloning operation for "masking" of the results, which complicates the search process. The improvement is aimed at reducing the number of "false alarms", when the area of the clone / pre-image detected in the original image or the localization of the identified areas do not correspond to the real clone and pre-image. The proposed improvement, based on analysis of different sizes per-pixel image blocks with the least difference from each other, has made it possible efficient functioning of the method, regardless of the specificity of the analyzed digital image.

  17. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    International Nuclear Information System (INIS)

    Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka

    2014-01-01

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

  18. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    Energy Technology Data Exchange (ETDEWEB)

    Shieh, Chun-Chien [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006, Australia and Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia); Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J., E-mail: paul.keall@sydney.edu.au [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006 (Australia); Kuncic, Zdenka [Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia)

    2014-04-15

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

  19. Video retrieval by still-image analysis with ImageMiner

    Science.gov (United States)

    Kreyss, Jutta; Roeper, M.; Alshuth, Peter; Hermes, Thorsten; Herzog, Otthein

    1997-01-01

    The large amount of available multimedia information (e.g. videos, audio, images) requires efficient and effective annotation and retrieval methods. As videos start playing a more important role in the frame of multimedia, we want to make these available for content-based retrieval. The ImageMiner-System, which was developed at the University of Bremen in the AI group, is designed for content-based retrieval of single images by a new combination of techniques and methods from computer vision and artificial intelligence. In our approach to make videos available for retrieval in a large database of videos and images there are two necessary steps: First, the detection and extraction of shots from a video, which is done by a histogram based method and second, the construction of the separate frames in a shot to one still single images. This is performed by a mosaicing-technique. The resulting mosaiced image gives a one image visualization of the shot and can be analyzed by the ImageMiner-System. ImageMiner has been tested on several domains, (e.g. landscape images, technical drawings), which cover a wide range of applications.

  20. 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)

  1. Image restoration and processing methods

    International Nuclear Information System (INIS)

    Daniell, G.J.

    1984-01-01

    This review will stress the importance of using image restoration techniques that deal with incomplete, inconsistent, and noisy data and do not introduce spurious features into the processed image. No single image is equally suitable for both the resolution of detail and the accurate measurement of intensities. A good general purpose technique is the maximum entropy method and the basis and use of this will be explained. (orig.)

  2. 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)

  3. 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

  4. A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

    Science.gov (United States)

    Hsu, Kuo-Hsien

    2012-11-01

    Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

  5. Wave-equation Migration Velocity Analysis Using Plane-wave Common Image Gathers

    KAUST Repository

    Guo, Bowen

    2017-06-01

    Wave-equation migration velocity analysis (WEMVA) based on subsurface-offset, angle domain or time-lag common image gathers (CIGs) requires significant computational and memory resources because it computes higher dimensional migration images in the extended image domain. To mitigate this problem, a WEMVA method using plane-wave CIGs is presented. Plane-wave CIGs reduce the computational cost and memory storage because they are directly calculated from prestack plane-wave migration, and the number of plane waves is often much smaller than the number of shots. In the case of an inaccurate migration velocity, the moveout of plane-wave CIGs is automatically picked by a semblance analysis method, which is then linked to the migration velocity update by a connective function. Numerical tests on two synthetic datasets and a field dataset validate the efficiency and effectiveness of this method.

  6. 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.

  7. Superresolution Imaging Using Resonant Multiples and Plane-wave Migration Velocity Analysis

    KAUST Repository

    Guo, Bowen

    2017-08-28

    Seismic imaging is a technique that uses seismic echoes to map and detect underground geological structures. The conventional seismic image has the resolution limit of λ/2, where λ is the wavelength associated with the seismic waves propagating in the subsurface. To exceed this resolution limit, this thesis develops a new imaging method using resonant multiples, which produces superresolution images with twice or even more the spatial resolution compared to the conventional primary reflection image. A resonant multiple is defined as a seismic reflection that revisits the same subsurface location along coincident reflection raypath. This reverberated raypath is the reason for superresolution imaging because it increases the differences in reflection times associated with subtle changes in the spatial location of the reflector. For the practical implementation of superresolution imaging, I develop a post-stack migration technique that first enhances the signal-to-noise ratios (SNRs) of resonant multiples by a moveout-correction stacking method, and then migrates the post-stacked resonant multiples with the associated Kirchhoff or wave-equation migration formula. I show with synthetic and field data examples that the first-order resonant multiple image has about twice the spatial resolution compared to the primary reflection image. Besides resolution, the correct estimate of the subsurface velocity is crucial for determining the correct depth of reflectors. Towards this goal, wave-equation migration velocity analysis (WEMVA) is an image-domain method which inverts for the velocity model that maximizes the similarity of common image gathers (CIGs). Conventional WEMVA based on subsurface-offset, angle domain or time-lag CIGs requires significant computational and memory resources because it computes higher dimensional migration images in the extended image domain. To mitigate this problem, I present a new WEMVA method using plane-wave CIGs. Plane-wave CIGs reduce the

  8. 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

  9. Spiking cortical model-based nonlocal means method for speckle reduction in optical coherence tomography images

    Science.gov (United States)

    Zhang, Xuming; Li, Liu; Zhu, Fei; Hou, Wenguang; Chen, Xinjian

    2014-06-01

    Optical coherence tomography (OCT) images are usually degraded by significant speckle noise, which will strongly hamper their quantitative analysis. However, speckle noise reduction in OCT images is particularly challenging because of the difficulty in differentiating between noise and the information components of the speckle pattern. To address this problem, the spiking cortical model (SCM)-based nonlocal means method is presented. The proposed method explores self-similarities of OCT images based on rotation-invariant features of image patches extracted by SCM and then restores the speckled images by averaging the similar patches. This method can provide sufficient speckle reduction while preserving image details very well due to its effectiveness in finding reliable similar patches under high speckle noise contamination. When applied to the retinal OCT image, this method provides signal-to-noise ratio improvements of >16 dB with a small 5.4% loss of similarity.

  10. 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.

  11. 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.

  12. Prognostic aspects of imaging method development

    International Nuclear Information System (INIS)

    Steinhart, L.

    1987-01-01

    A survey is presented of X-ray diagnostic methods and techniques and possibilities of their further development. Promising methods include direct imaging using digital radiography. In connection with computer technology these methods achieve higher resolution. The storage of obtained images in the computer memory will allow automated processing and evaluation and the use of expert systems. Development is expected to take place especially in computerized tomography using magnetic resonance, and positron computed tomography and other non-radioactive diagnostic methods. (J.B.). 5 figs., 1 tab., 1 ref

  13. A comparative study on generating simulated Landsat NDVI images using data fusion and regression method-the case of the Korean Peninsula.

    Science.gov (United States)

    Lee, Mi Hee; Lee, Soo Bong; Eo, Yang Dam; Kim, Sun Woong; Woo, Jung-Hun; Han, Soo Hee

    2017-07-01

    Landsat optical images have enough spatial and spectral resolution to analyze vegetation growth characteristics. But, the clouds and water vapor degrade the image quality quite often, which limits the availability of usable images for the time series vegetation vitality measurement. To overcome this shortcoming, simulated images are used as an alternative. In this study, weighted average method, spatial and temporal adaptive reflectance fusion model (STARFM) method, and multilinear regression analysis method have been tested to produce simulated Landsat normalized difference vegetation index (NDVI) images of the Korean Peninsula. The test results showed that the weighted average method produced the images most similar to the actual images, provided that the images were available within 1 month before and after the target date. The STARFM method gives good results when the input image date is close to the target date. Careful regional and seasonal consideration is required in selecting input images. During summer season, due to clouds, it is very difficult to get the images close enough to the target date. Multilinear regression analysis gives meaningful results even when the input image date is not so close to the target date. Average R 2 values for weighted average method, STARFM, and multilinear regression analysis were 0.741, 0.70, and 0.61, respectively.

  14. 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.

  15. Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

    2015-01-01

    Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

  16. Distributed MIMO-ISAR Sub-image Fusion Method

    Directory of Open Access Journals (Sweden)

    Gu Wenkun

    2017-02-01

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

  17. A three-dimensional correlation method for registration of medical images in radiology

    Energy Technology Data Exchange (ETDEWEB)

    Georgiou, Michalakis; Sfakianakis, George N [Department of Radiology, University of Miami, Jackson Memorial Hospital, Miami, FL 33136 (United States); Nagel, Joachim H [Institute of Biomedical Engineering, University of Stuttgart, Stuttgart 70174 (Germany)

    1999-12-31

    The availability of methods to register multi-modality images in order to `fuse` them to correlate their information is increasingly becoming an important requirement for various diagnostic and therapeutic procedures. A variety of image registration methods have been developed but they remain limited to specific clinical applications. Assuming rigid body transformation, two images can be registered if their differences are calculated in terms of translation, rotation and scaling. This paper describes the development and testing of a new correlation based approach for three-dimensional image registration. First, the scaling factors introduced by the imaging devices are calculated and compensated for. Then, the two images become translation invariant by computing their three-dimensional Fourier magnitude spectra. Subsequently, spherical coordinate transformation is performed and then the three-dimensional rotation is computed using a novice approach referred to as {sup p}olar Shells{sup .} The method of polar shells maps the three angles of rotation into one rotation and two translations of a two-dimensional function and then proceeds to calculate them using appropriate transformations based on the Fourier invariance properties. A basic assumption in the method is that the three-dimensional rotation is constrained to one large and two relatively small angles. This assumption is generally satisfied in normal clinical settings. The new three-dimensional image registration method was tested with simulations using computer generated phantom data as well as actual clinical data. Performance analysis and accuracy evaluation of the method using computer simulations yielded errors in the sub-pixel range. (authors) 6 refs., 3 figs.

  18. A three-dimensional correlation method for registration of medical images in radiology

    International Nuclear Information System (INIS)

    Georgiou, Michalakis; Sfakianakis, George N.; Nagel, Joachim H.

    1998-01-01

    The availability of methods to register multi-modality images in order to 'fuse' them to correlate their information is increasingly becoming an important requirement for various diagnostic and therapeutic procedures. A variety of image registration methods have been developed but they remain limited to specific clinical applications. Assuming rigid body transformation, two images can be registered if their differences are calculated in terms of translation, rotation and scaling. This paper describes the development and testing of a new correlation based approach for three-dimensional image registration. First, the scaling factors introduced by the imaging devices are calculated and compensated for. Then, the two images become translation invariant by computing their three-dimensional Fourier magnitude spectra. Subsequently, spherical coordinate transformation is performed and then the three-dimensional rotation is computed using a novice approach referred to as p olar Shells . The method of polar shells maps the three angles of rotation into one rotation and two translations of a two-dimensional function and then proceeds to calculate them using appropriate transformations based on the Fourier invariance properties. A basic assumption in the method is that the three-dimensional rotation is constrained to one large and two relatively small angles. This assumption is generally satisfied in normal clinical settings. The new three-dimensional image registration method was tested with simulations using computer generated phantom data as well as actual clinical data. Performance analysis and accuracy evaluation of the method using computer simulations yielded errors in the sub-pixel range. (authors)

  19. Quantitative analysis of Tl-201 myocardial perfusion image with special reference to circumferential profile method

    Energy Technology Data Exchange (ETDEWEB)

    Miyanaga, Hajime [Kyoto Prefectural Univ. of Medicine (Japan)

    1982-08-01

    A quantitative analysis of thallium-201 myocardial perfusion image (MPI) was attempted by using circumferential profile method (CPM) and the first purpose of this study is to assess the clinical utility of this method for the detection of myocardial ischemia. In patients with coronary artery disease, CPM analysis to exercise T1-MPI showed high sensitivity (9/12, 75%) and specificity (9/9, 100%), whereas exercise ECG showed high sensitivity (9/12, 75%), but relatively low specificity (7/9, 78%). In patients with myocardial infarction, CPM also showed high sensitivity (34/38, 89%) for the detection of myocardial necrosis, compared with visual interpretation (31/38, 81%) and with ECG (31/38, 81%). Defect score was correlated well with the number of abnormal Q waves. In exercise study, CPM was also sensitive to the change of perfusion defect in T1-MPI produced by exercise. So the results indicate that CPM is a good method not only quantitatively but also objectively to analyze T1-MPI. Although ECG is the most commonly used diagnostic tool for ischemic heart disease, several exercise induced ischemic changes in ECG have been still on discussion as criteria. So the second purpose of this study is to evaluate these ischemic ECG changes by exercise T1-MPI analized quantitatively. ST depression (ischemic 1 mm and junctional 2 mm or more), ST elevation (1 mm or more), and coronary T wave reversion in exercise ECG were though to be ischemic changes.

  20. General Staining and Segmentation Procedures for High Content Imaging and Analysis.

    Science.gov (United States)

    Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

    2018-01-01

    Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

  1. Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson's disease patients

    International Nuclear Information System (INIS)

    Chang Icheng; Lue Kunhan; Hsieh Hungjen; Liu Shuhsin; Kao, Chinhao K.

    2011-01-01

    6-[ 18 F]Fluoro-L-DOPA (FDOPA) is a radiopharmaceutical valuable for assessing the presynaptic dopaminergic function when used with positron emission tomography (PET). More specifically, the striatal-to-occipital ratio (SOR) of FDOPA uptake images has been extensively used as a quantitative parameter in these PET studies. Our aim was to develop an easy, automated method capable of performing objective analysis of SOR in FDOPA PET images of Parkinson's disease (PD) patients. Brain images from FDOPA PET studies of 21 patients with PD and 6 healthy subjects were included in our automated striatal analyses. Images of each individual were spatially normalized into an FDOPA template. Subsequently, the image slice with the highest level of basal ganglia activity was chosen among the series of normalized images. Also, the immediate preceding and following slices of the chosen image were then selected. Finally, the summation of these three images was used to quantify and calculate the SOR values. The results obtained by automated analysis were compared with manual analysis by a trained and experienced image processing technologist. The SOR values obtained from the automated analysis had a good agreement and high correlation with manual analysis. The differences in caudate, putamen, and striatum were -0.023, -0.029, and -0.025, respectively; correlation coefficients 0.961, 0.957, and 0.972, respectively. We have successfully developed a method for automated striatal uptake analysis of FDOPA PET images. There was no significant difference between the SOR values obtained from this method and using manual analysis. Yet it is an unbiased time-saving and cost-effective program and easy to implement on a personal computer. (author)

  2. 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...

  3. A psychophysical imaging method evidencing auditory cue extraction during speech perception: a group analysis of auditory classification images.

    Directory of Open Access Journals (Sweden)

    Léo Varnet

    Full Text Available Although there is a large consensus regarding the involvement of specific acoustic cues in speech perception, the precise mechanisms underlying the transformation from continuous acoustical properties into discrete perceptual units remains undetermined. This gap in knowledge is partially due to the lack of a turnkey solution for isolating critical speech cues from natural stimuli. In this paper, we describe a psychoacoustic imaging method known as the Auditory Classification Image technique that allows experimenters to estimate the relative importance of time-frequency regions in categorizing natural speech utterances in noise. Importantly, this technique enables the testing of hypotheses on the listening strategies of participants at the group level. We exemplify this approach by identifying the acoustic cues involved in da/ga categorization with two phonetic contexts, Al- or Ar-. The application of Auditory Classification Images to our group of 16 participants revealed significant critical regions on the second and third formant onsets, as predicted by the literature, as well as an unexpected temporal cue on the first formant. Finally, through a cluster-based nonparametric test, we demonstrate that this method is sufficiently sensitive to detect fine modifications of the classification strategies between different utterances of the same phoneme.

  4. Current imaging methods for evaluation of metabolic risk in pediatric patients

    International Nuclear Information System (INIS)

    Balev, B.; Lateva, M.; Popova, R.; Teneva, Ts.; Iotova, V.

    2013-01-01

    Full text: Introduction: The incidence of cardio - metabolic diseases increase in an increasingly early age is one of the challenges of the 21st century. This phenomenon is attributed largely of the obesity epidemic, it is particularly significant when the obesity occurs in childhood - obese children have a greater probability of developing cardiovascular disease and diabetes earlier. What you will learn: The significance of the obesity epidemic in childhood and metabolic risk increase; The compartment of adipose tissue and their role in maintaining metabolic balance and its breach; The importance of imaging methods in recent studies related to obesity and cardio - metabolic diseases in children; New imaging methods for proofing of pathological fat accumulation in other tissues and organs and their role in the study of metabolic disorders. Discussion: Various studies of pathology at obesity prove that obesity indicators are not sufficient for individualized assessment of cardio - metabolic risk. Only by imaging methods, information about the accumulated fat in metabolically more active visceral and ectopic adipose tissue depots has been obtained. The most common imaging techniques for analysis of body composition and adiposity in children - dual-energy X-ray absorptiometry (DXA), ultrasound , computed tomography ( CT) scan , magnetic resonance imaging ( MRI), magnetic resonance spectroscopy (MRS) will be presented. Conclusion: The imaging methods are widely used in the obesity and metabolic risk studies, as the trend is to be applied increasingly into practice. The results from Imaging studies affect not only to therapeutic approach, but also to the motivation of parents and patients to comply prescribed measures

  5. Separation method of heavy-ion particle image from gamma-ray mixed images using an imaging plate

    CERN Document Server

    Yamadera, A; Ohuchi, H; Nakamura, T; Fukumura, A

    1999-01-01

    We have developed a separation method of alpha-ray and gamma-ray images using the imaging plate (IP). The IP from which the first image was read out by an image reader was annealed at 50 deg. C for 2 h in a drying oven and the second image was read out by the image reader. It was found out that an annealing ratio, k, which is defined as a ratio of the photo-stimulated luminescence (PSL) density at the first measurement to that at the second measurement, was different for alpha rays and gamma rays. By subtracting the second image multiplied by a factor of k from the first image, the alpha-ray image was separated from the alpha and gamma-ray mixed images. This method was applied to identify the images of helium, carbon and neon particles of high energies using the heavy-ion medical accelerator, HIMAC. (author)

  6. Wavelet imaging cleaning method for atmospheric Cherenkov telescopes

    Science.gov (United States)

    Lessard, R. W.; Cayón, L.; Sembroski, G. H.; Gaidos, J. A.

    2002-07-01

    We present a new method of image cleaning for imaging atmospheric Cherenkov telescopes. The method is based on the utilization of wavelets to identify noise pixels in images of gamma-ray and hadronic induced air showers. This method selects more signal pixels with Cherenkov photons than traditional image processing techniques. In addition, the method is equally efficient at rejecting pixels with noise alone. The inclusion of more signal pixels in an image of an air shower allows for a more accurate reconstruction, especially at lower gamma-ray energies that produce low levels of light. We present the results of Monte Carlo simulations of gamma-ray and hadronic air showers which show improved angular resolution using this cleaning procedure. Data from the Whipple Observatory's 10-m telescope are utilized to show the efficacy of the method for extracting a gamma-ray signal from the background of hadronic generated images.

  7. A novel method of the image processing on irregular triangular meshes

    Science.gov (United States)

    Vishnyakov, Sergey; Pekhterev, Vitaliy; Sokolova, Elizaveta

    2018-04-01

    The paper describes a novel method of the image processing based on irregular triangular meshes implementation. The triangular mesh is adaptive to the image content, least mean square linear approximation is proposed for the basic interpolation within the triangle. It is proposed to use triangular numbers to simplify using of the local (barycentric) coordinates for the further analysis - triangular element of the initial irregular mesh is to be represented through the set of the four equilateral triangles. This allows to use fast and simple pixels indexing in local coordinates, e.g. "for" or "while" loops for access to the pixels. Moreover, representation proposed allows to use discrete cosine transform of the simple "rectangular" symmetric form without additional pixels reordering (as it is used for shape-adaptive DCT forms). Furthermore, this approach leads to the simple form of the wavelet transform on triangular mesh. The results of the method application are presented. It is shown that advantage of the method proposed is a combination of the flexibility of the image-adaptive irregular meshes with the simple form of the pixel indexing in local triangular coordinates and the using of the common forms of the discrete transforms for triangular meshes. Method described is proposed for the image compression, pattern recognition, image quality improvement, image search and indexing. It also may be used as a part of video coding (intra-frame or inter-frame coding, motion detection).

  8. Image change detection systems, methods, and articles of manufacture

    Science.gov (United States)

    Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

    2010-01-05

    Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

  9. X-CT imaging method for large objects using double offset scan mode

    International Nuclear Information System (INIS)

    Fu Jian; Lu Hongnian; Li Bing; Zhang Lei; Sun Jingjing

    2007-01-01

    In X-ray computed tomography (X-CT) inspection, rotate-only scanner is commonly used because this configuration offers the highest imaging speed and best utilization of X-ray dose. But it requires that the imaging region of the scanned object must fit within the X-ray beam. Another configuration, transverse-rotate scanner, has a bigger field of view, but it is much more time consuming. In this paper, a two-dimensional X-CT imaging method for large objects is proposed to overcome the existing disadvantages. The scan principle of this method has been described and the reconstruction algorithm has been deduced. The results of the computer simulation and the experiments show the validity of the new method. Analysis shows that the scan field of view of this method is 1.8 times larger than that of rotate-only X-CT. The scan speed of this method is also much quicker than transverse-rotate X-CT

  10. Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

    Science.gov (United States)

    Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

    2010-01-01

    An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

  11. V-SIPAL - A VIRTUAL LABORATORY FOR SATELLITE IMAGE PROCESSING AND ANALYSIS

    Directory of Open Access Journals (Sweden)

    K. M. Buddhiraju

    2012-09-01

    Full Text Available In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

  12. Universal Image Steganalytic Method

    Directory of Open Access Journals (Sweden)

    V. Banoci

    2014-12-01

    Full Text Available In the paper we introduce a new universal steganalytic method in JPEG file format that is detecting well-known and also newly developed steganographic methods. The steganalytic model is trained by MHF-DZ steganographic algorithm previously designed by the same authors. The calibration technique with the Feature Based Steganalysis (FBS was employed in order to identify statistical changes caused by embedding a secret data into original image. The steganalyzer concept utilizes Support Vector Machine (SVM classification for training a model that is later used by the same steganalyzer in order to identify between a clean (cover and steganographic image. The aim of the paper was to analyze the variety in accuracy of detection results (ACR while detecting testing steganographic algorithms as F5, Outguess, Model Based Steganography without deblocking, JP Hide and Seek which represent the generally used steganographic tools. The comparison of four feature vectors with different lengths FBS (22, FBS (66 FBS(274 and FBS(285 shows promising results of proposed universal steganalytic method comparing to binary methods.

  13. Transfer function analysis of positron-emitting tracer imaging system (PETIS) data

    International Nuclear Information System (INIS)

    Keutgen, N.; Matsuhashi, S.; Mizuniwa, C.; Ito, T.; Fujimura, T.; Ishioka, N.S.; Watanabe, S.; Sekine, T.; Uchida, H.; Hashimoto, S.

    2002-01-01

    Quantitative analysis of the two-dimensional image data obtained with the positron-emitting tracer imaging system (PETIS) for plant physiology has been carried out using a transfer function analysis method. While a cut leaf base of Chinese chive (Allium tuberosum Rottler) or a cut stem of soybean (Glycine max L.) was immersed in an aqueous solution containing the [ 18 F] F - ion or [ 13 N]NO 3 - ion, tracer images of the leaf of Chinese chive and the trifoliate of soybean were recorded with PETIS. From the time sequence of images, the tracer transfer function was estimated from which the speed of tracer transport and the fraction moved between specified image positions were deduced

  14. An Interactive Method Based on the Live Wire for Segmentation of the Breast in Mammography Images

    Directory of Open Access Journals (Sweden)

    Zhang Zewei

    2014-01-01

    Full Text Available In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two cases of breast segmentation data. Compared with the traditional method of image segmentation, experimental results show that the method achieves more accurate segmentation of breast lumps and provides more accurate objective basis on quantitative and qualitative analysis of breast lumps.

  15. An interactive method based on the live wire for segmentation of the breast in mammography images.

    Science.gov (United States)

    Zewei, Zhang; Tianyue, Wang; Li, Guo; Tingting, Wang; Lu, Xu

    2014-01-01

    In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two cases of breast segmentation data. Compared with the traditional method of image segmentation, experimental results show that the method achieves more accurate segmentation of breast lumps and provides more accurate objective basis on quantitative and qualitative analysis of breast lumps.

  16. Handbook of mathematical methods in imaging

    CERN Document Server

    2015-01-01

    The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. This expanded and revised second edition contains updates to existing chapters and 16 additional entries on important mathematical methods such as graph cuts, morphology, discrete geometry, PDEs, conformal methods, to name a few. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 200 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and com...

  17. SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

    Science.gov (United States)

    Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

    2007-05-01

    (R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

  18. Attenuation correction with region growing method used in the positron emission mammography imaging system

    Science.gov (United States)

    Gu, Xiao-Yue; Li, Lin; Yin, Peng-Fei; Yun, Ming-Kai; Chai, Pei; Huang, Xian-Chao; Sun, Xiao-Li; Wei, Long

    2015-10-01

    The Positron Emission Mammography imaging system (PEMi) provides a novel nuclear diagnosis method dedicated for breast imaging. With a better resolution than whole body PET, PEMi can detect millimeter-sized breast tumors. To address the requirement of semi-quantitative analysis with a radiotracer concentration map of the breast, a new attenuation correction method based on a three-dimensional seeded region growing image segmentation (3DSRG-AC) method has been developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuity property of the segmentation result makes this new method free of activity variation of breast tissues. The threshold value chosen is the key process for the segmentation method. The first valley in the grey level histogram of the reconstruction image is set as the lower threshold, which works well in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probability of detecting small and early breast tumors. Supported by Knowledge Innovation Project of The Chinese Academy of Sciences (KJCX2-EW-N06)

  19. A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

    Science.gov (United States)

    Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

    2018-01-01

    Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Automated analysis of heterogeneous carbon nanostructures by high-resolution electron microscopy and on-line image processing

    International Nuclear Information System (INIS)

    Toth, P.; Farrer, J.K.; Palotas, A.B.; Lighty, J.S.; Eddings, E.G.

    2013-01-01

    High-resolution electron microscopy is an efficient tool for characterizing heterogeneous nanostructures; however, currently the analysis is a laborious and time-consuming manual process. In order to be able to accurately and robustly quantify heterostructures, one must obtain a statistically high number of micrographs showing images of the appropriate sub-structures. The second step of analysis is usually the application of digital image processing techniques in order to extract meaningful structural descriptors from the acquired images. In this paper it will be shown that by applying on-line image processing and basic machine vision algorithms, it is possible to fully automate the image acquisition step; therefore, the number of acquired images in a given time can be increased drastically without the need for additional human labor. The proposed automation technique works by computing fields of structural descriptors in situ and thus outputs sets of the desired structural descriptors in real-time. The merits of the method are demonstrated by using combustion-generated black carbon samples. - Highlights: ► The HRTEM analysis of heterogeneous nanostructures is a tedious manual process. ► Automatic HRTEM image acquisition and analysis can improve data quantity and quality. ► We propose a method based on on-line image analysis for the automation of HRTEM image acquisition. ► The proposed method is demonstrated using HRTEM images of soot particles

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

    Directory of Open Access Journals (Sweden)

    Lu Guo

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

  2. Methods of filtering the graph images of the functions

    Directory of Open Access Journals (Sweden)

    Олександр Григорович Бурса

    2017-06-01

    Full Text Available The theoretical aspects of cleaning raster images of scanned graphs of functions from digital, chromatic and luminance distortions by using computer graphics techniques have been considered. The basic types of distortions characteristic of graph images of functions have been stated. To suppress the distortion several methods, providing for high-quality of the resulting images and saving their topological features, were suggested. The paper describes the techniques developed and improved by the authors: the method of cleaning the image of distortions by means of iterative contrasting, based on the step-by-step increase in image contrast in the graph by 1%; the method of small entities distortion restoring, based on the thinning of the known matrix of contrast increase filter (the allowable dimensions of the nucleus dilution radius convolution matrix, which provide for the retention of the graph lines have been established; integration technique of the noise reduction method by means of contrasting and distortion restoring method of small entities with known σ-filter. Each method in the complex has been theoretically substantiated. The developed methods involve treatment of graph images as the entire image (global processing and its fragments (local processing. The metrics assessing the quality of the resulting image with the global and local processing have been chosen, the substantiation of the choice as well as the formulas have been given. The proposed complex methods of cleaning the graphs images of functions from grayscale image distortions is adaptive to the form of an image carrier, the distortion level in the image and its distribution. The presented results of testing the developed complex of methods for a representative sample of images confirm its effectiveness

  3. Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

    Directory of Open Access Journals (Sweden)

    Mao-Gui Hu

    2009-10-01

    Full Text Available Satellite remote sensing (RS is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intraurban. In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolutionenhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well indetail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics.

  4. Comparison of longitudinal excursion of a nerve-phantom model using quantitative ultrasound imaging and motion analysis system methods: A convergent validity study.

    Science.gov (United States)

    Paquette, Philippe; El Khamlichi, Youssef; Lamontagne, Martin; Higgins, Johanne; Gagnon, Dany H

    2017-08-01

    Quantitative ultrasound imaging is gaining popularity in research and clinical settings to measure the neuromechanical properties of the peripheral nerves such as their capability to glide in response to body segment movement. Increasing evidence suggests that impaired median nerve longitudinal excursion is associated with carpal tunnel syndrome. To date, psychometric properties of longitudinal nerve excursion measurements using quantitative ultrasound imaging have not been extensively investigated. This study investigates the convergent validity of the longitudinal nerve excursion by comparing measures obtained using quantitative ultrasound imaging with those determined with a motion analysis system. A 38-cm long rigid nerve-phantom model was used to assess the longitudinal excursion in a laboratory environment. The nerve-phantom model, immersed in a 20-cm deep container filled with a gelatin-based solution, was moved 20 times using a linear forward and backward motion. Three light-emitting diodes were used to record nerve-phantom excursion with a motion analysis system, while a 5-cm linear transducer allowed simultaneous recording via ultrasound imaging. Both measurement techniques yielded excellent association ( r  = 0.99) and agreement (mean absolute difference between methods = 0.85 mm; mean relative difference between methods = 7.48 %). Small discrepancies were largely found when larger excursions (i.e. > 10 mm) were performed, revealing slight underestimation of the excursion by the ultrasound imaging analysis software. Quantitative ultrasound imaging is an accurate method to assess the longitudinal excursion of an in vitro nerve-phantom model and appears relevant for future research protocols investigating the neuromechanical properties of the peripheral nerves.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    H. Shen

    2012-08-01

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

  7. Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

    Science.gov (United States)

    Karimi, Mohammad H; Asemani, Davud

    2014-05-01

    Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  8. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili, E-mail: wangnsrl@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029 (China); Zhang, Kai [Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Zhu, Peiping; Wu, Ziyu, E-mail: wuzy@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029, China and Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

    2015-02-15

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using the error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.

  9. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    International Nuclear Information System (INIS)

    Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili; Zhang, Kai; Zhu, Peiping; Wu, Ziyu

    2015-01-01

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using the error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations

  10. Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images.

    Science.gov (United States)

    Castro, P; Huerga, C; Chamorro, P; Garayoa, J; Roch, M; Pérez, L

    2018-04-17

    The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18 F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF. Copyright © 2018 Sociedad Española de Medicina Nuclear e Imagen Molecular. Publicado por Elsevier España, S.L.U. All rights reserved.

  11. 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.)

  12. SAMA: A Method for 3D Morphological Analysis.

    Directory of Open Access Journals (Sweden)

    Tessie Paulose

    Full Text Available Three-dimensional (3D culture models are critical tools for understanding tissue morphogenesis. A key requirement for their analysis is the ability to reconstruct the tissue into computational models that allow quantitative evaluation of the formed structures. Here, we present Software for Automated Morphological Analysis (SAMA, a method by which epithelial structures grown in 3D cultures can be imaged, reconstructed and analyzed with minimum human intervention. SAMA allows quantitative analysis of key features of epithelial morphogenesis such as ductal elongation, branching and lumen formation that distinguish different hormonal treatments. SAMA is a user-friendly set of customized macros operated via FIJI (http://fiji.sc/Fiji, an open-source image analysis platform in combination with a set of functions in R (http://www.r-project.org/, an open-source program for statistical analysis. SAMA enables a rapid, exhaustive and quantitative 3D analysis of the shape of a population of structures in a 3D image. SAMA is cross-platform, licensed under the GPLv3 and available at http://montevil.theobio.org/content/sama.

  13. Analysis of bubbly flow using particle image velocimetry

    Energy Technology Data Exchange (ETDEWEB)

    Todd, D.R.; Ortiz-Villafuerte, J.; Schmidl, W.D.; Hassan, Y.A. [Texas A and M University, Nuclear Engineering Dept., College Stagion, TX (United States); Sanchez-Silva, F. [ESIME, INP (Mexico)

    2001-07-01

    The local phasic velocities can be determined in two-phase flows if the phases can be separated during analysis. The continuous liquid velocity field can be captured using standard Particle Image Velocimetry (PIV) techniques in two-phase flows. PIV is now a well-established, standard flow measurement technique, which provides instantaneous velocity fields in a two-dimensional plane of finite thickness. PIV can be extended to three dimensions within the plane with special considerations. A three-dimensional shadow PIV (SPIV) measurement apparatus can be used to capture the dispersed phase flow parameters such as velocity and interfacial area. The SPIV images contain only the bubble images, and can be easily analyzed and the results used to separate the dispersed phase from the continuous phase in PIV data. An experimental system that combines the traditional PIV technique with SPIV will be described and sample data will be analyzed to demonstrate an advanced turbulence measurement method in a two-phase bubbly flow system. Also, a qualitative error analysis method that allows users to reduce the number of erroneous vectors obtained from the PIV measurements will be discussed. (authors)

  14. Analysis of bubbly flow using particle image velocimetry

    International Nuclear Information System (INIS)

    Todd, D.R.; Ortiz-Villafuerte, J.; Schmidl, W.D.; Hassan, Y.A.; Sanchez-Silva, F.

    2001-01-01

    The local phasic velocities can be determined in two-phase flows if the phases can be separated during analysis. The continuous liquid velocity field can be captured using standard Particle Image Velocimetry (PIV) techniques in two-phase flows. PIV is now a well-established, standard flow measurement technique, which provides instantaneous velocity fields in a two-dimensional plane of finite thickness. PIV can be extended to three dimensions within the plane with special considerations. A three-dimensional shadow PIV (SPIV) measurement apparatus can be used to capture the dispersed phase flow parameters such as velocity and interfacial area. The SPIV images contain only the bubble images, and can be easily analyzed and the results used to separate the dispersed phase from the continuous phase in PIV data. An experimental system that combines the traditional PIV technique with SPIV will be described and sample data will be analyzed to demonstrate an advanced turbulence measurement method in a two-phase bubbly flow system. Also, a qualitative error analysis method that allows users to reduce the number of erroneous vectors obtained from the PIV measurements will be discussed. (authors)

  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. Extraction of the number of peroxisomes in yeast cells by automated image analysis.

    Science.gov (United States)

    Niemistö, Antti; Selinummi, Jyrki; Saleem, Ramsey; Shmulevich, Ilya; Aitchison, John; Yli-Harja, Olli

    2006-01-01

    An automated image analysis method for extracting the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local mean-variance space. The watershed transformation is thereafter employed to separate cells that are clustered together. The peroxisomes are detected by thresholding the fluorescent image. The method is tested with several images of a budding yeast Saccharomyces cerevisiae population, and the results are compared with manually obtained results.

  17. 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,

  18. Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles

    NARCIS (Netherlands)

    Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

    This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken

  19. 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.

  20. Terahertz pulse imaging for tree-ring analysis: a preliminary study for dendrochronology applications

    International Nuclear Information System (INIS)

    Jackson, J B; Mourou, M; Whitaker, J F; Labaune, J; Mourou, G A; Duling, I N III; Williamson, S L; Lavier, C; Menu, M

    2009-01-01

    Time-domain terahertz reflection imaging is presented as a novel method of measuring otherwise inaccessible tree rings in wooden cultural heritage for the purpose of tree-ring crossdating. Axial and lateral two-dimensional terahertz images of obscured ring patterns are statistically validated with respect to their corresponding optical photographs via adapted dendrochronological methods. Results are compared to similar analysis of x-ray images of a wood specimen

  1. Analysis and Extension of the Percentile Method, Estimating a Noise Curve from a Single Image

    Directory of Open Access Journals (Sweden)

    Miguel Colom

    2013-12-01

    Full Text Available Given a white Gaussian noise signal on a sampling grid, its variance can be estimated from a small block sample. However, in natural images we observe the combination of the geometry of the scene being photographed and the added noise. In this case, estimating directly the standard deviation of the noise from block samples is not reliable since the measured standard deviation is not explained just by the noise but also by the geometry of the image. The Percentile method tries to estimate the standard deviation of the noise from blocks of a high-passed version of the image and a small p-percentile of these standard deviations. The idea behind is that edges and textures in a block of the image increase the observed standard deviation but they never make it decrease. Therefore, a small percentile (0.5%, for example in the list of standard deviations of the blocks is less likely to be affected by the edges and textures than a higher percentile (50%, for example. The 0.5%-percentile is empirically proven to be adequate for most natural, medical and microscopy images. The Percentile method is adapted to signal-dependent noise, which is realistic with the Poisson noise model obtained by a CCD device in a digital camera.

  2. 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...

  3. Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Robin Wolz

    Full Text Available The role of structural brain magnetic resonance imaging (MRI is becoming more and more emphasized in the early diagnostics of Alzheimer's disease (AD. This study aimed to assess the improvement in classification accuracy that can be achieved by combining features from different structural MRI analysis techniques. Automatically estimated MR features used are hippocampal volume, tensor-based morphometry, cortical thickness and a novel technique based on manifold learning. Baseline MRIs acquired from all 834 subjects (231 healthy controls (HC, 238 stable mild cognitive impairment (S-MCI, 167 MCI to AD progressors (P-MCI, 198 AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI database were used for evaluation. We compared the classification accuracy achieved with linear discriminant analysis (LDA and support vector machines (SVM. The best results achieved with individual features are 90% sensitivity and 84% specificity (HC/AD classification, 64%/66% (S-MCI/P-MCI and 82%/76% (HC/P-MCI with the LDA classifier. The combination of all features improved these results to 93% sensitivity and 85% specificity (HC/AD, 67%/69% (S-MCI/P-MCI and 86%/82% (HC/P-MCI. Compared with previously published results in the ADNI database using individual MR-based features, the presented results show that a comprehensive analysis of MRI images combining multiple features improves classification accuracy and predictive power in detecting early AD. The most stable and reliable classification was achieved when combining all available features.

  4. 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

  5. Development of image analysis software for quantification of viable cells in microchips.

    Science.gov (United States)

    Georg, Maximilian; Fernández-Cabada, Tamara; Bourguignon, Natalia; Karp, Paola; Peñaherrera, Ana B; Helguera, Gustavo; Lerner, Betiana; Pérez, Maximiliano S; Mertelsmann, Roland

    2018-01-01

    Over the past few years, image analysis has emerged as a powerful tool for analyzing various cell biology parameters in an unprecedented and highly specific manner. The amount of data that is generated requires automated methods for the processing and analysis of all the resulting information. The software available so far are suitable for the processing of fluorescence and phase contrast images, but often do not provide good results from transmission light microscopy images, due to the intrinsic variation of the acquisition of images technique itself (adjustment of brightness / contrast, for instance) and the variability between image acquisition introduced by operators / equipment. In this contribution, it has been presented an image processing software, Python based image analysis for cell growth (PIACG), that is able to calculate the total area of the well occupied by cells with fusiform and rounded morphology in response to different concentrations of fetal bovine serum in microfluidic chips, from microscopy images in transmission light, in a highly efficient way.

  6. Convergence analysis for column-action methods in image reconstruction

    DEFF Research Database (Denmark)

    Elfving, Tommy; Hansen, Per Christian; Nikazad, Touraj

    2016-01-01

    Column-oriented versions of algebraic iterative methods are interesting alternatives to their row-version counterparts: they converge to a least squares solution, and they provide a basis for saving computational work by skipping small updates. In this paper we consider the case of noise-free data....... We present a convergence analysis of the column algorithms, we discuss two techniques (loping and flagging) for reducing the work, and we establish some convergence results for methods that utilize these techniques. The performance of the algorithms is illustrated with numerical examples from...

  7. Early Detection of Diabetic Retinopathy in Fluorescent Angiography Retinal Images Using Image Processing Methods

    Directory of Open Access Journals (Sweden)

    Meysam Tavakoli

    2010-12-01

    Full Text Available Introduction: Diabetic retinopathy (DR is the single largest cause of sight loss and blindness in the working age population of Western countries; it is the most common cause of blindness in adults between 20 and 60 years of age. Early diagnosis of DR is critical for preventing vision loss so early detection of microaneurysms (MAs as the first signs of DR is important. This paper addresses the automatic detection of MAs in fluorescein angiography fundus images, which plays a key role in computer assisted diagnosis of DR, a serious and frequent eye disease. Material and Methods: The algorithm can be divided into three main steps. The first step or pre-processing was for background normalization and contrast enhancement of the image. The second step aimed at detecting landmarks, i.e., all patterns possibly corresponding to vessels and the optic nerve head, which was achieved using a local radon transform. Then, MAs were extracted, which were used in the final step to automatically classify candidates into real MA and other objects. A database of 120 fluorescein angiography fundus images was used to train and test the algorithm. The algorithm was compared to manually obtained gradings of those images. Results: Sensitivity of diagnosis for DR was 94%, with specificity of 75%, and sensitivity of precise microaneurysm localization was 92%, at an average number of 8 false positives per image. Discussion and Conclusion: Sensitivity and specificity of this algorithm make it one of the best methods in this field. Using local radon transform in this algorithm eliminates the noise sensitivity for microaneurysm detection in retinal image analysis.

  8. Monitoring a chemical plume remediation via the radio imaging method

    International Nuclear Information System (INIS)

    McCorkle, R.W.; Spence, T.; Linder, K.E.; Betsill, J.D.

    1996-01-01

    In this paper, the authors present the results of a site characterization, monitoring, and remediation effort at Sandia National Laboratories (SNL). The primary objective of the study is to determine the feasibility of using the Radio Imaging Method (RIM) to solve a near-surface waste site characterization problem. The goals are to demonstrate the method during the site characterization phase, then continue with an in-situ monitoring and analysis of the remediation process

  9. A new method for mobile phone image denoising

    Science.gov (United States)

    Jin, Lianghai; Jin, Min; Li, Xiang; Xu, Xiangyang

    2015-12-01

    Images captured by mobile phone cameras via pipeline processing usually contain various kinds of noises, especially granular noise with different shapes and sizes in both luminance and chrominance channels. In chrominance channels, noise is closely related to image brightness. To improve image quality, this paper presents a new method to denoise such mobile phone images. The proposed scheme converts the noisy RGB image to luminance and chrominance images, which are then denoised by a common filtering framework. The common filtering framework processes a noisy pixel by first excluding the neighborhood pixels that significantly deviate from the (vector) median and then utilizing the other neighborhood pixels to restore the current pixel. In the framework, the strength of chrominance image denoising is controlled by image brightness. The experimental results show that the proposed method obviously outperforms some other representative denoising methods in terms of both objective measure and visual evaluation.

  10. 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

  11. Methods for the visualization and analysis of extracellular matrix protein structure and degradation.

    Science.gov (United States)

    Leonard, Annemarie K; Loughran, Elizabeth A; Klymenko, Yuliya; Liu, Yueying; Kim, Oleg; Asem, Marwa; McAbee, Kevin; Ravosa, Matthew J; Stack, M Sharon

    2018-01-01

    This chapter highlights methods for visualization and analysis of extracellular matrix (ECM) proteins, with particular emphasis on collagen type I, the most abundant protein in mammals. Protocols described range from advanced imaging of complex in vivo matrices to simple biochemical analysis of individual ECM proteins. The first section of this chapter describes common methods to image ECM components and includes protocols for second harmonic generation, scanning electron microscopy, and several histological methods of ECM localization and degradation analysis, including immunohistochemistry, Trichrome staining, and in situ zymography. The second section of this chapter details both a common transwell invasion assay and a novel live imaging method to investigate cellular behavior with respect to collagen and other ECM proteins of interest. The final section consists of common electrophoresis-based biochemical methods that are used in analysis of ECM proteins. Use of the methods described herein will enable researchers to gain a greater understanding of the role of ECM structure and degradation in development and matrix-related diseases such as cancer and connective tissue disorders. © 2018 Elsevier Inc. All rights reserved.

  12. 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)

  13. 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.

  14. Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images.

    Science.gov (United States)

    Kimori, Yoshitaka; Baba, Norio; Morone, Nobuhiro

    2010-07-08

    A reliable extraction technique for resolving multiple spots in light or electron microscopic images is essential in investigations of the spatial distribution and dynamics of specific proteins inside cells and tissues. Currently, automatic spot extraction and characterization in complex microscopic images poses many challenges to conventional image processing methods. A new method to extract closely located, small target spots from biological images is proposed. This method starts with a simple but practical operation based on the extended morphological top-hat transformation to subtract an uneven background. The core of our novel approach is the following: first, the original image is rotated in an arbitrary direction and each rotated image is opened with a single straight line-segment structuring element. Second, the opened images are unified and then subtracted from the original image. To evaluate these procedures, model images of simulated spots with closely located targets were created and the efficacy of our method was compared to that of conventional morphological filtering methods. The results showed the better performance of our method. The spots of real microscope images can be quantified to confirm that the method is applicable in a given practice. Our method achieved effective spot extraction under various image conditions, including aggregated target spots, poor signal-to-noise ratio, and large variations in the background intensity. Furthermore, it has no restrictions with respect to the shape of the extracted spots. The features of our method allow its broad application in biological and biomedical image information analysis.

  15. Magnetic imager and method

    Science.gov (United States)

    Powell, James; Reich, Morris; Danby, Gordon

    1997-07-22

    A magnetic imager 10 includes a generator 18 for practicing a method of applying a background magnetic field over a concealed object, with the object being effective to locally perturb the background field. The imager 10 also includes a sensor 20 for measuring perturbations of the background field to detect the object. In one embodiment, the background field is applied quasi-statically. And, the magnitude or rate of change of the perturbations may be measured for determining location, size, and/or condition of the object.

  16. 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.

  17. Fractal analysis in radiological and nuclear medicine perfusion imaging: a systematic review

    Energy Technology Data Exchange (ETDEWEB)

    Michallek, Florian; Dewey, Marc [Humboldt-Universitaet zu Berlin, Freie Universitaet Berlin, Charite - Universitaetsmedizin Berlin, Medical School, Department of Radiology, Berlin (Germany)

    2014-01-15

    To provide an overview of recent research in fractal analysis of tissue perfusion imaging, using standard radiological and nuclear medicine imaging techniques including computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) and to discuss implications for different fields of application. A systematic review of fractal analysis for tissue perfusion imaging was performed by searching the databases MEDLINE (via PubMed), EMBASE (via Ovid) and ISI Web of Science. Thirty-seven eligible studies were identified. Fractal analysis was performed on perfusion imaging of tumours, lung, myocardium, kidney, skeletal muscle and cerebral diseases. Clinically, different aspects of tumour perfusion and cerebral diseases were successfully evaluated including detection and classification. In physiological settings, it was shown that perfusion under different conditions and in various organs can be properly described using fractal analysis. Fractal analysis is a suitable method for quantifying heterogeneity from radiological and nuclear medicine perfusion images under a variety of conditions and in different organs. Further research is required to exploit physiologically proven fractal behaviour in the clinical setting. (orig.)

  18. Fractal analysis in radiological and nuclear medicine perfusion imaging: a systematic review

    International Nuclear Information System (INIS)

    Michallek, Florian; Dewey, Marc

    2014-01-01

    To provide an overview of recent research in fractal analysis of tissue perfusion imaging, using standard radiological and nuclear medicine imaging techniques including computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) and to discuss implications for different fields of application. A systematic review of fractal analysis for tissue perfusion imaging was performed by searching the databases MEDLINE (via PubMed), EMBASE (via Ovid) and ISI Web of Science. Thirty-seven eligible studies were identified. Fractal analysis was performed on perfusion imaging of tumours, lung, myocardium, kidney, skeletal muscle and cerebral diseases. Clinically, different aspects of tumour perfusion and cerebral diseases were successfully evaluated including detection and classification. In physiological settings, it was shown that perfusion under different conditions and in various organs can be properly described using fractal analysis. Fractal analysis is a suitable method for quantifying heterogeneity from radiological and nuclear medicine perfusion images under a variety of conditions and in different organs. Further research is required to exploit physiologically proven fractal behaviour in the clinical setting. (orig.)

  19. Image acquisitions, processing and analysis in the process of obtaining characteristics of horse navicular bone

    Science.gov (United States)

    Zaborowicz, M.; Włodarek, J.; Przybylak, A.; Przybył, K.; Wojcieszak, D.; Czekała, W.; Ludwiczak, A.; Boniecki, P.; Koszela, K.; Przybył, J.; Skwarcz, J.

    2015-07-01

    The aim of this study was investigate the possibility of using methods of computer image analysis for the assessment and classification of morphological variability and the state of health of horse navicular bone. Assumption was that the classification based on information contained in the graphical form two-dimensional digital images of navicular bone and information of horse health. The first step in the research was define the classes of analyzed bones, and then using methods of computer image analysis for obtaining characteristics from these images. This characteristics were correlated with data concerning the animal, such as: side of hooves, number of navicular syndrome (scale 0-3), type, sex, age, weight, information about lace, information about heel. This paper shows the introduction to the study of use the neural image analysis in the diagnosis of navicular bone syndrome. Prepared method can provide an introduction to the study of non-invasive way to assess the condition of the horse navicular bone.

  20. Reliable clarity automatic-evaluation method for optical remote sensing images

    Science.gov (United States)

    Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

    2015-10-01

    Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

  1. 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...

  2. Lattice and strain analysis of atomic resolution Z-contrast images based on template matching

    Energy Technology Data Exchange (ETDEWEB)

    Zuo, Jian-Min, E-mail: jianzuo@uiuc.edu [Department of Materials Science and Engineering, University of Illinois, Urbana, IL 61801 (United States); Seitz Materials Research Laboratory, University of Illinois, Urbana, IL 61801 (United States); Shah, Amish B. [Center for Microanalysis of Materials, Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801 (United States); Kim, Honggyu; Meng, Yifei; Gao, Wenpei [Department of Materials Science and Engineering, University of Illinois, Urbana, IL 61801 (United States); Seitz Materials Research Laboratory, University of Illinois, Urbana, IL 61801 (United States); Rouviére, Jean-Luc [CEA-INAC/UJF-Grenoble UMR-E, SP2M, LEMMA, Minatec, Grenoble 38054 (France)

    2014-01-15

    A real space approach is developed based on template matching for quantitative lattice analysis using atomic resolution Z-contrast images. The method, called TeMA, uses the template of an atomic column, or a group of atomic columns, to transform the image into a lattice of correlation peaks. This is helped by using a local intensity adjusted correlation and by the design of templates. Lattice analysis is performed on the correlation peaks. A reference lattice is used to correct for scan noise and scan distortions in the recorded images. Using these methods, we demonstrate that a precision of few picometers is achievable in lattice measurement using aberration corrected Z-contrast images. For application, we apply the methods to strain analysis of a molecular beam epitaxy (MBE) grown LaMnO{sub 3} and SrMnO{sub 3} superlattice. The results show alternating epitaxial strain inside the superlattice and its variations across interfaces at the spatial resolution of a single perovskite unit cell. Our methods are general, model free and provide high spatial resolution for lattice analysis. - Highlights: • A real space approach is developed for strain analysis using atomic resolution Z-contrast images and template matching. • A precision of few picometers is achievable in the measurement of lattice displacements. • The spatial resolution of a single perovskite unit cell is demonstrated for a LaMnO{sub 3} and SrMnO{sub 3} superlattice grown by MBE.

  3. 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...

  4. A Local Region of Interest Imaging Method for Electrical Impedance Tomography with Internal Electrodes

    Directory of Open Access Journals (Sweden)

    Hyeuknam Kwon

    2013-01-01

    Full Text Available Electrical Impedance Tomography (EIT is a very attractive functional imaging method despite the low sensitivity and resolution. The use of internal electrodes with the conventional reconstruction algorithms was not enough to enhance image resolution and accuracy in the region of interest (ROI. We propose a local ROI imaging method with internal electrodes developed from careful analysis of the sensitivity matrix that is designed to reduce the sensitivity of the voxels outside the local region and optimize the sensitivity of the voxel inside the local region. We perform numerical simulations and physical measurements to demonstrate the localized EIT imaging method. In preliminary results with multiple objects we show the benefits of using an internal electrode and the improved resolution due to the local ROI image reconstruction method. The sensitivity is further increased by allowing the surface electrodes to be unevenly spaced with a higher density of surface electrodes near the ROI. Also, we analyse how much the image quality is improved using several performance parameters for comparison. While these have not yet been studied in depth, it convincingly shows an improvement in local sensitivity in images obtained with an internal electrode in comparison to a standard reconstruction method.

  5. Finite element formulation for a digital image correlation method

    International Nuclear Information System (INIS)

    Sun Yaofeng; Pang, John H. L.; Wong, Chee Khuen; Su Fei

    2005-01-01

    A finite element formulation for a digital image correlation method is presented that will determine directly the complete, two-dimensional displacement field during the image correlation process on digital images. The entire interested image area is discretized into finite elements that are involved in the common image correlation process by use of our algorithms. This image correlation method with finite element formulation has an advantage over subset-based image correlation methods because it satisfies the requirements of displacement continuity and derivative continuity among elements on images. Numerical studies and a real experiment are used to verify the proposed formulation. Results have shown that the image correlation with the finite element formulation is computationally efficient, accurate, and robust

  6. Estimation of physiological parameters using knowledge-based factor analysis of dynamic nuclear medicine image sequences

    International Nuclear Information System (INIS)

    Yap, J.T.; Chen, C.T.; Cooper, M.

    1995-01-01

    The authors have previously developed a knowledge-based method of factor analysis to analyze dynamic nuclear medicine image sequences. In this paper, the authors analyze dynamic PET cerebral glucose metabolism and neuroreceptor binding studies. These methods have shown the ability to reduce the dimensionality of the data, enhance the image quality of the sequence, and generate meaningful functional images and their corresponding physiological time functions. The new information produced by the factor analysis has now been used to improve the estimation of various physiological parameters. A principal component analysis (PCA) is first performed to identify statistically significant temporal variations and remove the uncorrelated variations (noise) due to Poisson counting statistics. The statistically significant principal components are then used to reconstruct a noise-reduced image sequence as well as provide an initial solution for the factor analysis. Prior knowledge such as the compartmental models or the requirement of positivity and simple structure can be used to constrain the analysis. These constraints are used to rotate the factors to the most physically and physiologically realistic solution. The final result is a small number of time functions (factors) representing the underlying physiological processes and their associated weighting images representing the spatial localization of these functions. Estimation of physiological parameters can then be performed using the noise-reduced image sequence generated from the statistically significant PCs and/or the final factor images and time functions. These results are compared to the parameter estimation using standard methods and the original raw image sequences. Graphical analysis was performed at the pixel level to generate comparable parametric images of the slope and intercept (influx constant and distribution volume)

  7. Fast analysis of narcotic drugs by optical chemical imaging

    International Nuclear Information System (INIS)

    Fisher, Michal; Bulatov, Vallery; Schechter, Israel

    2003-01-01

    A new technique is proposed for fast detection, identification and imaging of narcotic drugs in their solid phase. This technique, which requires only a tiny sample of a few microns, is based on microscopic chemical imaging. Minor sample preparation is required, and results are obtained within seconds. As far as we know, this is the most sensitive detection system available today for solid drugs. The technique can be applied for fast analysis of minute drug residues, and therefore is of considerable importance for forensic applications. It is shown that identification of drug traces in realistic matrixes is possible. Two main methods were applied in this study for detection of drugs and drug derivatives. The first method was based on direct detection and chemical imaging of the auto-fluorescence of the analyzed drugs. This method is applicable when the analyzed drug emits fluorescence under the experiment conditions, such as lysergic acid diethylamide (known as LSD). The second method was used for obtaining chemical imaging of drugs that do not fluoresce under the experiment conditions. In these cases fluorescent labeling dyes were applied to the examined samples (including the drug and the matrix). Both methods are simple and rapid, and require minor or no sample preparation at all. Detection limits are very low in the picogram range

  8. Automated daily quality control analysis for mammography in a multi-unit imaging center.

    Science.gov (United States)

    Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

    2018-01-01

    Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

  9. Investigation of innovative radiation imaging method and system for radiological environments

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, H. [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of); Joung, J., E-mail: jinhun.joung@nucaremed.com [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of); Nucare, Inc., Incheon (Korea, Republic of); Kim, Y. [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of); Nucare, Inc., Incheon (Korea, Republic of); Lee, K. [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of)

    2017-03-01

    We have developed a novel imaging method that can be applied to most applications in the field of radiological environment imaging. It resolves either two-dimensional (2D) or three-dimensional (3D) distributions of radioactive sources in applications for homeland security, environmental monitoring, radiation contamination monitoring, baggage inspection, nuclear power plant monitoring, and more. The proposed imaging method uses a simple detector configured as a radiation-counting detector with spectroscopic capabilities. The detector module consists of two components: a flat field-of-view (FOV) collimator with a 30° FOV opening and a typical single-channel radiation detector made of a 2 in.×2 in. NaI(Tl) scintillator coupled to a 2 in photomultiplier tube (PMT). This simple detector module makes it possible to develop a cost-effective imaging system and provide design freedom in extending the system configuration to include one-dimensional (1D) or 2D detector-array shapes to meet the needs of various applications. One of most distinctive features of the new imaging method is that it uses only a pair of 2D projections to obtain a 3D reconstruction. The projections are measured by the proposed detector module at two positions orthogonal to one another; the measured projections are manipulated to enhance the resolution of the reconstructed 3D image. The imaging method comprises several steps performed consecutively: projection measurement, energy re-binning, projection separation, resolution and attenuation recovery, image reconstruction, and image consolidation and quantitative analysis. The resolution and attenuation recovery step provides the most distinctive and important processing by which the poor quality of projection data is enhanced. Such poor quality is mainly due to the use of a simple detector with a wide-opening flat FOV collimator. Simulation and experimental studies have been conducted to validate the proposed method. In this investigation, we

  10. Method of orthogonally splitting imaging pose measurement

    Science.gov (United States)

    Zhao, Na; Sun, Changku; Wang, Peng; Yang, Qian; Liu, Xintong

    2018-01-01

    In order to meet the aviation's and machinery manufacturing's pose measurement need of high precision, fast speed and wide measurement range, and to resolve the contradiction between measurement range and resolution of vision sensor, this paper proposes an orthogonally splitting imaging pose measurement method. This paper designs and realizes an orthogonally splitting imaging vision sensor and establishes a pose measurement system. The vision sensor consists of one imaging lens, a beam splitter prism, cylindrical lenses and dual linear CCD. Dual linear CCD respectively acquire one dimensional image coordinate data of the target point, and two data can restore the two dimensional image coordinates of the target point. According to the characteristics of imaging system, this paper establishes the nonlinear distortion model to correct distortion. Based on cross ratio invariability, polynomial equation is established and solved by the least square fitting method. After completing distortion correction, this paper establishes the measurement mathematical model of vision sensor, and determines intrinsic parameters to calibrate. An array of feature points for calibration is built by placing a planar target in any different positions for a few times. An terative optimization method is presented to solve the parameters of model. The experimental results show that the field angle is 52 °, the focus distance is 27.40 mm, image resolution is 5185×5117 pixels, displacement measurement error is less than 0.1mm, and rotation angle measurement error is less than 0.15°. The method of orthogonally splitting imaging pose measurement can satisfy the pose measurement requirement of high precision, fast speed and wide measurement range.

  11. Body image disturbance in adults treated for cancer - a concept analysis.

    Science.gov (United States)

    Rhoten, Bethany A

    2016-05-01

    To report an analysis of the concept of body image disturbance in adults who have been treated for cancer as a phenomenon of interest to nurses. Although the concept of body image disturbance has been clearly defined in adolescents and adults with eating disorders, adults who have been treated for cancer may also experience body image disturbance. In this context, the concept of body image disturbance has not been clearly defined. Concept analysis. PubMed, Psychological Information Database and Cumulative Index of Nursing and Allied Health Literature were searched for publications from 1937 - 2015. Search terms included body image, cancer, body image disturbance, adult and concept analysis. Walker and Avant's 8-step method of concept analysis was used. The defining attributes of body image disturbance in adults who have been treated for cancer are: (1) self-perception of a change in appearance and displeasure with the change or perceived change in appearance; (2) decline in an area of function; and (3) psychological distress regarding changes in appearance and/or function. This concept analysis provides a foundation for the development of multidimensional assessment tools and interventions to alleviate body image disturbance in this population. A better understanding of body image disturbance in adults treated for cancer will assist nurses and other clinicians in identifying this phenomenon and nurse scientists in developing instruments that accurately measure this condition, along with interventions that will promote a better quality of life for survivors. © 2016 John Wiley & Sons Ltd.

  12. Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

    Science.gov (United States)

    D'Ambra, Pasqua; Tartaglione, Gaetano

    2015-03-01

    Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

  13. 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.

  14. Matrix-based image reconstruction methods for tomography

    International Nuclear Information System (INIS)

    Llacer, J.; Meng, J.D.

    1984-10-01

    Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures

  15. SU-E-I-93: Improved Imaging Quality for Multislice Helical CT Via Sparsity Regularized Iterative Image Reconstruction Method Based On Tensor Framelet

    International Nuclear Information System (INIS)

    Nam, H; Guo, M; Lee, K; Li, R; Xing, L; Gao, H

    2014-01-01

    Purpose: Inspired by compressive sensing, sparsity regularized iterative reconstruction method has been extensively studied. However, its utility pertinent to multislice helical 4D CT for radiotherapy with respect to imaging quality, dose, and time has not been thoroughly addressed. As the beginning of such an investigation, this work carries out the initial comparison of reconstructed imaging quality between sparsity regularized iterative method and analytic method through static phantom studies using a state-of-art 128-channel multi-slice Siemens helical CT scanner. Methods: In our iterative method, tensor framelet (TF) is chosen as the regularization method for its superior performance from total variation regularization in terms of reduced piecewise-constant artifacts and improved imaging quality that has been demonstrated in our prior work. On the other hand, X-ray transforms and its adjoints are computed on-the-fly through GPU implementation using our previous developed fast parallel algorithms with O(1) complexity per computing thread. For comparison, both FDK (approximate analytic method) and Katsevich algorithm (exact analytic method) are used for multislice helical CT image reconstruction. Results: The phantom experimental data with different imaging doses were acquired using a state-of-art 128-channel multi-slice Siemens helical CT scanner. The reconstructed image quality was compared between TF-based iterative method, FDK and Katsevich algorithm with the quantitative analysis for characterizing signal-to-noise ratio, image contrast, and spatial resolution of high-contrast and low-contrast objects. Conclusion: The experimental results suggest that our tensor framelet regularized iterative reconstruction algorithm improves the helical CT imaging quality from FDK and Katsevich algorithm for static experimental phantom studies that have been performed

  16. MELDOQ - astrophysical image and pattern analysis in medicine: early recognition of malignant melanomas of the skin by digital image analysis. Final report

    International Nuclear Information System (INIS)

    Bunk, W.; Pompl, R.; Morfill, G.; Stolz, W.; Abmayr, W.

    1999-01-01

    Dermatoscopy is at present the most powerful clinical method for early detection of malignant melanomas. However, the application requires a lot of expertise and experience. Therefore, a quantitative image analysis system has been developed in order to assist dermatologists in 'on site diagnosis' and to improve the detection efficiency. Based on a very extensive dataset of dermatoscopic images, recorded in a standardized manner, a number of features for quantitative characterization of complex patterns in melanocytic skin lesions has been developed. The derived classifier improved the detection rate of malignant and benign melanocytic lesions to over 90% (sensitivity =91.5% and specificity =93.4% in the test set), using only six measures. A distinguishing feature of the system is the visualization of the quantified chara