Development of Multi-perspective Diagnostics and Analysis Algorithms with Applications to Subsonic and Supersonic Combustors

Science.gov (United States)

Wickersham, Andrew Joseph

There are two critical research needs for the study of hydrocarbon combustion in high speed flows: 1) combustion diagnostics with adequate temporal and spatial resolution, and 2) mathematical techniques that can extract key information from large datasets. The goal of this work is to address these needs, respectively, by the use of high speed and multi-perspective chemiluminescence and advanced mathematical algorithms. To obtain the measurements, this work explored the application of high speed chemiluminescence diagnostics and the use of fiber-based endoscopes (FBEs) for non-intrusive and multi-perspective chemiluminescence imaging up to 20 kHz. Non-intrusive and full-field imaging measurements provide a wealth of information for model validation and design optimization of propulsion systems. However, it is challenging to obtain such measurements due to various implementation difficulties such as optical access, thermal management, and equipment cost. This work therefore explores the application of FBEs for non-intrusive imaging to supersonic propulsion systems. The FBEs used in this work are demonstrated to overcome many of the aforementioned difficulties and provided datasets from multiple angular positions up to 20 kHz in a supersonic combustor. The combustor operated on ethylene fuel at Mach 2 with an inlet stagnation temperature and pressure of approximately 640 degrees Fahrenheit and 70 psia, respectively. The imaging measurements were obtained from eight perspectives simultaneously, providing full-field datasets under such flow conditions for the first time, allowing the possibility of inferring multi-dimensional measurements. Due to the high speed and multi-perspective nature, such new diagnostic capability generates a large volume of data and calls for analysis algorithms that can process the data and extract key physics effectively. To extract the key combustion dynamics from the measurements, three mathematical methods were investigated in this work

Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images

Directory of Open Access Journals (Sweden)

Jianfeng Zhang

2017-01-01

Full Text Available Objective. The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM. Methods. Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digital tongue instrument. Tongue body and tongue coating were separated by the division-merging method and chrominance-threshold method. With extracted color and texture features of the tongue image as input variables, the diagnostic model of diabetes with SVM was trained. After optimizing the combination of SVM kernel parameters and input variables, the influences of the combinations on the model were analyzed. Results. After normalizing parameters of tongue images, the accuracy rate of diabetes predication was increased from 77.83% to 78.77%. The accuracy rate and area under curve (AUC were not reduced after reducing the dimensions of tongue features with principal component analysis (PCA, while substantially saving the training time. During the training for selecting SVM parameters by genetic algorithm (GA, the accuracy rate of cross-validation was grown from 72% or so to 83.06%. Finally, we compare with several state-of-the-art algorithms, and experimental results show that our algorithm has the best predictive accuracy. Conclusions. The diagnostic method of diabetes on the basis of tongue images in Traditional Chinese Medicine (TCM is of great value, indicating the feasibility of digitalized tongue diagnosis.

TH-A-BRF-11: Image Intensity Non-Uniformities Between MRI Simulation and Diagnostic MRI

International Nuclear Information System (INIS)

Paulson, E

2014-01-01

Purpose: MRI simulation for MRI-based radiotherapy demands that patients be setup in treatment position, which frequently involves use of alternative radiofrequency (RF) coil configurations to accommodate immobilized patients. However, alternative RF coil geometries may exacerbate image intensity non-uniformities (IINU) beyond those observed in diagnostic MRI, which may challenge image segmentation and registration accuracy as well as confound studies assessing radiotherapy response when MR simulation images are used as baselines for evaluation. The goal of this work was to determine whether differences in IINU exist between MR simulation and diagnostic MR images. Methods: ACR-MRI phantom images were acquired at 3T using a spin-echo sequence (TE/TR:20/500ms, rBW:62.5kHz, TH/skip:5/5mm). MR simulation images were obtained by wrapping two flexible phased-array RF coils around the phantom. Diagnostic MR images were obtained by placing the phantom into a commercial phased-array head coil. Pre-scan normalization was enabled in both cases. Images were transferred offline and corrected for IINU using the MNI N3 algorithm. Coefficients of variation (CV=σ/μ) were calculated for each slice. Wilcoxon matched-pairs and Mann-Whitney tests compared CV values between original and N3 images and between MR simulation and diagnostic MR images. Results: Significant differences in CV were detected between original and N3 images in both MRI simulation and diagnostic MRI groups (p=0.010, p=0.010). In addition, significant differences in CV were detected between original MR simulation and original and N3 diagnostic MR images (p=0.0256, p=0.0016). However, no significant differences in CV were detected between N3 MR simulation images and original or N3 diagnostic MR images, demonstrating the importance of correcting MR simulation images beyond pre-scan normalization prior to use in radiotherapy. Conclusions: Alternative RF coil configurations used in MRI simulation can Result in

Benchmarking Diagnostic Algorithms on an Electrical Power System Testbed

Science.gov (United States)

Kurtoglu, Tolga; Narasimhan, Sriram; Poll, Scott; Garcia, David; Wright, Stephanie

2009-01-01

Diagnostic algorithms (DAs) are key to enabling automated health management. These algorithms are designed to detect and isolate anomalies of either a component or the whole system based on observations received from sensors. In recent years a wide range of algorithms, both model-based and data-driven, have been developed to increase autonomy and improve system reliability and affordability. However, the lack of support to perform systematic benchmarking of these algorithms continues to create barriers for effective development and deployment of diagnostic technologies. In this paper, we present our efforts to benchmark a set of DAs on a common platform using a framework that was developed to evaluate and compare various performance metrics for diagnostic technologies. The diagnosed system is an electrical power system, namely the Advanced Diagnostics and Prognostics Testbed (ADAPT) developed and located at the NASA Ames Research Center. The paper presents the fundamentals of the benchmarking framework, the ADAPT system, description of faults and data sets, the metrics used for evaluation, and an in-depth analysis of benchmarking results obtained from testing ten diagnostic algorithms on the ADAPT electrical power system testbed.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Science.gov (United States)

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

A novel computer-assisted image analysis of [123I]β-CIT SPECT images improves the diagnostic accuracy of parkinsonian disorders

International Nuclear Information System (INIS)

Goebel, Georg; Seppi, Klaus; Wenning, Gregor K.; Poewe, Werner; Scherfler, Christoph; Donnemiller, Eveline; Warwitz, Boris; Virgolini, Irene

2011-01-01

The purpose of this study was to develop an observer-independent algorithm for the correct classification of dopamine transporter SPECT images as Parkinson's disease (PD), multiple system atrophy parkinson variant (MSA-P), progressive supranuclear palsy (PSP) or normal. A total of 60 subjects with clinically probable PD (n = 15), MSA-P (n = 15) and PSP (n = 15), and 15 age-matched healthy volunteers, were studied with the dopamine transporter ligand [ 123 I]β-CIT. Parametric images of the specific-to-nondisplaceable equilibrium partition coefficient (BP ND ) were generated. Following a voxel-wise ANOVA, cut-off values were calculated from the voxel values of the resulting six post-hoc t-test maps. The percentages of the volume of an individual BP ND image remaining below and above the cut-off values were determined. The higher percentage of image volume from all six cut-off matrices was used to classify an individual's image. For validation, the algorithm was compared to a conventional region of interest analysis. The predictive diagnostic accuracy of the algorithm in the correct assignment of a [ 123 I]β-CIT SPECT image was 83.3% and increased to 93.3% on merging the MSA-P and PSP groups. In contrast the multinomial logistic regression of mean region of interest values of the caudate, putamen and midbrain revealed a diagnostic accuracy of 71.7%. In contrast to a rater-driven approach, this novel method was superior in classifying [ 123 I]β-CIT-SPECT images as one of four diagnostic entities. In combination with the investigator-driven visual assessment of SPECT images, this clinical decision support tool would help to improve the diagnostic yield of [ 123 I]β-CIT SPECT in patients presenting with parkinsonism at their initial visit. (orig.)

A novel computer-assisted image analysis of [123I]β-CIT SPECT images improves the diagnostic accuracy of parkinsonian disorders.

Science.gov (United States)

Goebel, Georg; Seppi, Klaus; Donnemiller, Eveline; Warwitz, Boris; Wenning, Gregor K; Virgolini, Irene; Poewe, Werner; Scherfler, Christoph

2011-04-01

The purpose of this study was to develop an observer-independent algorithm for the correct classification of dopamine transporter SPECT images as Parkinson's disease (PD), multiple system atrophy parkinson variant (MSA-P), progressive supranuclear palsy (PSP) or normal. A total of 60 subjects with clinically probable PD (n = 15), MSA-P (n = 15) and PSP (n = 15), and 15 age-matched healthy volunteers, were studied with the dopamine transporter ligand [(123)I]β-CIT. Parametric images of the specific-to-nondisplaceable equilibrium partition coefficient (BP(ND)) were generated. Following a voxel-wise ANOVA, cut-off values were calculated from the voxel values of the resulting six post-hoc t-test maps. The percentages of the volume of an individual BP(ND) image remaining below and above the cut-off values were determined. The higher percentage of image volume from all six cut-off matrices was used to classify an individual's image. For validation, the algorithm was compared to a conventional region of interest analysis. The predictive diagnostic accuracy of the algorithm in the correct assignment of a [(123)I]β-CIT SPECT image was 83.3% and increased to 93.3% on merging the MSA-P and PSP groups. In contrast the multinomial logistic regression of mean region of interest values of the caudate, putamen and midbrain revealed a diagnostic accuracy of 71.7%. In contrast to a rater-driven approach, this novel method was superior in classifying [(123)I]β-CIT-SPECT images as one of four diagnostic entities. In combination with the investigator-driven visual assessment of SPECT images, this clinical decision support tool would help to improve the diagnostic yield of [(123)I]β-CIT SPECT in patients presenting with parkinsonism at their initial visit.

A parallelizable real-time motion tracking algorithm with applications to ultrasonic strain imaging

International Nuclear Information System (INIS)

Jiang, J; Hall, T J

2007-01-01

Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows (registered) system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s -1 ) that exceed our previous methods

A novel computer-assisted image analysis of [{sup 123}I]{beta}-CIT SPECT images improves the diagnostic accuracy of parkinsonian disorders

Energy Technology Data Exchange (ETDEWEB)

Goebel, Georg [Innsbruck Medical University, Department of Medical Statistics, Informatics and Health Economics, Innsbruck (Austria); Seppi, Klaus; Wenning, Gregor K.; Poewe, Werner; Scherfler, Christoph [Innsbruck Medical University, Department of Neurology, Innsbruck (Austria); Donnemiller, Eveline; Warwitz, Boris; Virgolini, Irene [Innsbruck Medical University, Department of Nuclear Medicine, Innsbruck (Austria)

2011-04-15

The purpose of this study was to develop an observer-independent algorithm for the correct classification of dopamine transporter SPECT images as Parkinson's disease (PD), multiple system atrophy parkinson variant (MSA-P), progressive supranuclear palsy (PSP) or normal. A total of 60 subjects with clinically probable PD (n = 15), MSA-P (n = 15) and PSP (n = 15), and 15 age-matched healthy volunteers, were studied with the dopamine transporter ligand [{sup 123}I]{beta}-CIT. Parametric images of the specific-to-nondisplaceable equilibrium partition coefficient (BP{sub ND}) were generated. Following a voxel-wise ANOVA, cut-off values were calculated from the voxel values of the resulting six post-hoc t-test maps. The percentages of the volume of an individual BP{sub ND} image remaining below and above the cut-off values were determined. The higher percentage of image volume from all six cut-off matrices was used to classify an individual's image. For validation, the algorithm was compared to a conventional region of interest analysis. The predictive diagnostic accuracy of the algorithm in the correct assignment of a [{sup 123}I]{beta}-CIT SPECT image was 83.3% and increased to 93.3% on merging the MSA-P and PSP groups. In contrast the multinomial logistic regression of mean region of interest values of the caudate, putamen and midbrain revealed a diagnostic accuracy of 71.7%. In contrast to a rater-driven approach, this novel method was superior in classifying [{sup 123}I]{beta}-CIT-SPECT images as one of four diagnostic entities. In combination with the investigator-driven visual assessment of SPECT images, this clinical decision support tool would help to improve the diagnostic yield of [{sup 123}I]{beta}-CIT SPECT in patients presenting with parkinsonism at their initial visit. (orig.)

Metal artifact reduction algorithm based on model images and spatial information

Energy Technology Data Exchange (ETDEWEB)

Wu, Jay [Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan (China); Shih, Cheng-Ting [Department of Biomedical Engineering and Environmental Sciences, National Tsing-Hua University, Hsinchu, Taiwan (China); Chang, Shu-Jun [Health Physics Division, Institute of Nuclear Energy Research, Taoyuan, Taiwan (China); Huang, Tzung-Chi [Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan (China); Sun, Jing-Yi [Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan (China); Wu, Tung-Hsin, E-mail: tung@ym.edu.tw [Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No.155, Sec. 2, Linong Street, Taipei 112, Taiwan (China)

2011-10-01

Computed tomography (CT) has become one of the most favorable choices for diagnosis of trauma. However, high-density metal implants can induce metal artifacts in CT images, compromising image quality. In this study, we proposed a model-based metal artifact reduction (MAR) algorithm. First, we built a model image using the k-means clustering technique with spatial information and calculated the difference between the original image and the model image. Then, the projection data of these two images were combined using an exponential weighting function. At last, the corrected image was reconstructed using the filter back-projection algorithm. Two metal-artifact contaminated images were studied. For the cylindrical water phantom image, the metal artifact was effectively removed. The mean CT number of water was improved from -28.95{+-}97.97 to -4.76{+-}4.28. For the clinical pelvic CT image, the dark band and the metal line were removed, and the continuity and uniformity of the soft tissue were recovered as well. These results indicate that the proposed MAR algorithm is useful for reducing metal artifact and could improve the diagnostic value of metal-artifact contaminated CT images.

Management algorithm for images of hepatic incidentalomas, renal and adrenal detected by computed tomography

International Nuclear Information System (INIS)

Montero Gonzalez, Allan

2012-01-01

A literature review has been carried out in the diagnostic and monitoring algorithms for image of incidentalomas of solid abdominal organs (liver, kidney and adrenal glands) detected by computed tomography (CT). The criteria have been unified and updated for a effective diagnosis. Posed algorithms have been made in simplified form. The imaging techniques have been specified for each pathology, showing the advantages and disadvantages of using it and justifying the application in daily practice [es

Speckle imaging algorithms for planetary imaging

Energy Technology Data Exchange (ETDEWEB)

Johansson, E. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

I will discuss the speckle imaging algorithms used to process images of the impact sites of the collision of comet Shoemaker-Levy 9 with Jupiter. The algorithms use a phase retrieval process based on the average bispectrum of the speckle image data. High resolution images are produced by estimating the Fourier magnitude and Fourier phase of the image separately, then combining them and inverse transforming to achieve the final result. I will show raw speckle image data and high-resolution image reconstructions from our recent experiment at Lick Observatory.

Novel medical image enhancement algorithms

Science.gov (United States)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Picosecond image-converter diagnostics

International Nuclear Information System (INIS)

Schelev, M.Ya.

1975-01-01

A brief review is presented of the improvements in picosecond image-converter diagnostics carried out since the previous Congress in 1972. The account is given under the following headings: picosecond image converter cameras for visible and x-ray radiation diagnostics; Nd:glass and ruby mode-locked laser measurements; x-ray plasma emission diagnostics; computer treatment of pictures produced by picosecond cameras. (U.K.)

Diagnostic Imaging Workshop

International Nuclear Information System (INIS)

Sociedad Argentina de Fisica Medica

2012-01-01

The American Association of Physicist in Medicine (AAPM), the International Organization for Medical Physics (IOMP) and the Argentina Society of Medical Physics (SAFIM) was organized the Diagnostic Imaging Workshop 2012, in the city of Buenos Aires, Argentina. This workshop was an oriented training and scientific exchange between professionals and technicians who work in medical physics, especially in the areas of diagnostic imaging, nuclear medicine and radiotherapy, with special emphasis on the use of multimodal imaging for radiation treatment, planning as well of quality assurance associates.

REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICA

Directory of Open Access Journals (Sweden)

О. E. Prokopchenko

2015-09-01

Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article & based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematica may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

Phase-contrast enhanced mammography: A new diagnostic tool for breast imaging

International Nuclear Information System (INIS)

Wang Zhentian; Thuering, Thomas; David, Christian; Roessl, Ewald; Trippel, Mafalda; Kubik-Huch, Rahel A.; Singer, Gad; Hohl, Michael K.; Hauser, Nik; Stampanoni, Marco

2012-01-01

Phase contrast and scattering-based X-ray imaging can potentially revolutionize the radiological approach to breast imaging by providing additional and complementary information to conventional, absorption-based methods. We investigated native, non-fixed whole breast samples using a grating interferometer with an X-ray tube-based configuration. Our approach simultaneously recorded absorption, differential phase contrast and small-angle scattering signals. The results show that this novel technique - combined with a dedicated image fusion algorithm - has the potential to deliver enhanced breast imaging with complementary information for an improved diagnostic process.

Phase-contrast enhanced mammography: A new diagnostic tool for breast imaging

Energy Technology Data Exchange (ETDEWEB)

Wang Zhentian; Thuering, Thomas; David, Christian; Roessl, Ewald; Trippel, Mafalda; Kubik-Huch, Rahel A.; Singer, Gad; Hohl, Michael K.; Hauser, Nik; Stampanoni, Marco [Swiss Light Source, Paul Scherrer Institut, 5232 Villigen (Switzerland); Laboratory for Micro and Nanotechnology, Paul Scherrer Institut, 5232 Villigen (Switzerland); Philips Technologie GmbH, Roentgenstrasse 24, 22335 Hamburg (Germany); Institute of Pathology, Kantonsspital Baden, 5404 Baden (Switzerland); Department of Radiology, Kantonsspital Baden, 5404 Baden (Switzerland); Institute of Pathology, Kantonsspital Baden, 5404 Baden (Switzerland); Department of Gynecology and Obstetrics, Interdisciplinary Breast Center Baden, Kantonsspital Baden, 5404 Baden (Switzerland); Swiss Light Source, Paul Scherrer Institut, 5232 Villigen, Switzerland and Institute for Biomedical Engineering, University and ETH Zuerich, 8092 Zuerich (Switzerland)

2012-07-31

Phase contrast and scattering-based X-ray imaging can potentially revolutionize the radiological approach to breast imaging by providing additional and complementary information to conventional, absorption-based methods. We investigated native, non-fixed whole breast samples using a grating interferometer with an X-ray tube-based configuration. Our approach simultaneously recorded absorption, differential phase contrast and small-angle scattering signals. The results show that this novel technique - combined with a dedicated image fusion algorithm - has the potential to deliver enhanced breast imaging with complementary information for an improved diagnostic process.

Fitting-free algorithm for efficient quantification of collagen fiber alignment in SHG imaging applications.

Science.gov (United States)

Hall, Gunnsteinn; Liang, Wenxuan; Li, Xingde

2017-10-01

Collagen fiber alignment derived from second harmonic generation (SHG) microscopy images can be important for disease diagnostics. Image processing algorithms are needed to robustly quantify the alignment in images with high sensitivity and reliability. Fourier transform (FT) magnitude, 2D power spectrum, and image autocorrelation have previously been used to extract fiber information from images by assuming a certain mathematical model (e.g. Gaussian distribution of the fiber-related parameters) and fitting. The fitting process is slow and fails to converge when the data is not Gaussian. Herein we present an efficient constant-time deterministic algorithm which characterizes the symmetricity of the FT magnitude image in terms of a single parameter, named the fiber alignment anisotropy R ranging from 0 (randomized fibers) to 1 (perfect alignment). This represents an important improvement of the technology and may bring us one step closer to utilizing the technology for various applications in real time. In addition, we present a digital image phantom-based framework for characterizing and validating the algorithm, as well as assessing the robustness of the algorithm against different perturbations.

Primary retroperitoneal soft tissue sarcoma: Imaging appearances, pitfalls and diagnostic algorithm.

Science.gov (United States)

Messiou, C; Moskovic, E; Vanel, D; Morosi, C; Benchimol, R; Strauss, D; Miah, A; Douis, H; van Houdt, W; Bonvalot, S

2017-07-01

Although retroperitoneal sarcomas are rare tumours, they can be encountered by a wide variety of clinicians as they can be incidental findings on imaging or present with non specific symptoms and signs. Surgical resection can offer hope of cure and patient outcomes are improved when patients are managed in high-volume specialist centers. Failure to recognize retroperitoneal sarcomas on imaging can lead to inappropriate management in inexperienced centers. Therefore it is critical that a diagnosis of retroperitoneal sarcoma should be considered in the differential diagnosis of a retroperitoneal mass with prompt referral to a soft tissue sarcoma unit. In particular, the most common retroperitoneal sarcoma subtypes, liposarcoma and leiomyosarcoma, have characteristic imaging appearances which are discussed. This review therefore aims to set the context and guide clinicians through a diagnostic pathway for retroperitoneal masses in adults which arise extrinsic to the solid abdominal viscera. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Abdomen disease diagnosis in CT images using flexiscale curvelet transform and improved genetic algorithm.

Science.gov (United States)

Sethi, Gaurav; Saini, B S

2015-12-01

This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.

REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICS

Directory of Open Access Journals (Sweden)

O. Ye. Prokopchenko

2015-10-01

Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article and based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematics may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve  the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

[Diagnostic imaging and radiation hazards].

Science.gov (United States)

Claudon, Michel; Guillaume, Luc

2015-01-01

For the last 20 years, the exposure of the population to medical radiation has been increased by 600%, mainly due to the extension of new imaging modalities such as CT or interventional radiology. The risk for radio-induced hazards is especially marked for children, because of the high sensivity of tissues to radiation especially during the first decade of the life. Two main ways allow to better control and reduce the mean effective dose per patient in diagnostic imaging: the introduction of recent technical improvement (i.e. low dose CT scans using iterative reconstruction algorithms, low dose technique for pediatric spine), and the substitution to non-radiating techniques such as ultrasound and MRI. The French National institute of Radioprotection and Nuclear Safety periodically publishes dose reference levels for conventional films and CT examinations, for both adults and pediatric patients. A close relationship between clinicians and radiologists remains essential for a better appreciation of the risk/benefit ratio of each individual examination using X-Rays.

Algorithm of imaging modalities in cases of mandibular fractures

International Nuclear Information System (INIS)

Mihailova, H.

2009-01-01

Mandibular fracture is the most common bone fracture of maxillo-facial trauma. Up to now the main method for examination of the mandible is radiography. The aim of the issue is to present an algorithm of imaging modalities for investigation of patients in cases of mandibular trauma. It consists of series of X ray techniques and views of the facial skull named mandibulo-facial. This standardizes mandibulo-facial series includes exactly determined four projections done by conventional X ray techniques: posterior-anterior view of skull (PA or AP), oblique view of the left mandible; oblique view of the right mandible; occipito-mental view. Using these four planned radiograms is obligatory for each mandibular trauma. Panoramic X-ray is obligatory in cases of apparatus availability; this abolish only oblique views (left and right). Occipito-mental view of the skull gives anatomically better the coronoid process of the mandible, the zygoma complex, the orbital edges and maxillar sinus than Waters projection. So mandibulo-facial series of four planned radiograms is not only for diagnostic of mandibular fractures, but as a screening of mandibulo-facial trauma too. Thus using algorithm of imaging modalities in cases of mandibular fracture leads to optimization of diagnostic process in patients with mandibular trauma. (author)

Computer-aided assessment of diagnostic images for epidemiological research

Directory of Open Access Journals (Sweden)

Gange Stephen J

2009-11-01

Full Text Available Abstract Background Diagnostic images are often assessed for clinical outcomes using subjective methods, which are limited by the skill of the reviewer. Computer-aided diagnosis (CAD algorithms that assist reviewers in their decisions concerning outcomes have been developed to increase sensitivity and specificity in the clinical setting. However, these systems have not been well utilized in research settings to improve the measurement of clinical endpoints. Reductions in bias through their use could have important implications for etiologic research. Methods Using the example of cortical cataract detection, we developed an algorithm for assisting a reviewer in evaluating digital images for the presence and severity of lesions. Available image processing and statistical methods that were easily implementable were used as the basis for the CAD algorithm. The performance of the system was compared to the subjective assessment of five reviewers using 60 simulated images. Cortical cataract severity scores from 0 to 16 were assigned to the images by the reviewers and the CAD system, with each image assessed twice to obtain a measure of variability. Image characteristics that affected reviewer bias were also assessed by systematically varying the appearance of the simulated images. Results The algorithm yielded severity scores with smaller bias on images where cataract severity was mild to moderate (approximately ≤ 6/16ths. On high severity images, the bias of the CAD system exceeded that of the reviewers. The variability of the CAD system was zero on repeated images but ranged from 0.48 to 1.22 for the reviewers. The direction and magnitude of the bias exhibited by the reviewers was a function of the number of cataract opacities, the shape and the contrast of the lesions in the simulated images. Conclusion CAD systems are feasible to implement with available software and can be valuable when medical images contain exposure or outcome information for

A Diagnostic Ultrasound Imaging System

International Nuclear Information System (INIS)

Lee, Seong Woo

1999-01-01

The ability to see the internal organs of the human body in a noninvasive way is a powerful diagnostic tool of modern medicine. Among these imaging modalities such as X-ray, MRI, and ultrasound. MRI and ultrasound are presenting much less risk of undesirable damage of both patient and examiner. In fact, no deleterious effects have been reported as a result of clinical examination by using MRI and ultrasound diagnostic equipment. As a result, their market volume has been rapidly increased. MRI has a good resolution. but there are a few disadvantages such as high price. non-real-time imaging capability. and expensive diagnostic cost. On the other hand, the ultrasound imaging system has inherently poor resolution as compared with X-ray and MRI. In spite of its poor resolution, the ultrasound diagnostic equipment is lower in price and has an ability of real-time imaging as compared with the others. As a result, the ultrasound imaging system has become general and essential modality for imaging the internal organs of human body. In this review various researches and developments to enhance the resolution of the ultrasound images are explained and future trends of the ultrasound imaging technology are described

An image fiber based fluorescent probe with associated signal processing scheme for biomedical diagnostics

International Nuclear Information System (INIS)

Vaishakh, M; Murukeshan, V M; Seah, L K

2008-01-01

A dual-modality image fiber based fluorescent probe that can be used for depth sensitive imaging and suppression of fluorescent emissions with nanosecond lifetime difference is proposed and illustrated in this paper. The system can give high optical sectioning and employs an algorithm for obtaining phase sensitive images. The system can find main application in in vivo biomedical diagnostics for detecting biochemical changes for distinguishing malignant tissue from healthy tissue

Algorithms for Image Analysis and Combination of Pattern Classifiers with Application to Medical Diagnosis

Science.gov (United States)

Georgiou, Harris

2009-10-01

Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.

A Robust Automated Cataract Detection Algorithm Using Diagnostic Opinion Based Parameter Thresholding for Telemedicine Application

Directory of Open Access Journals (Sweden)

Shashwat Pathak

2016-09-01

Full Text Available This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images in adult human subjects. Currently, methods available for cataract detection are based on the use of either fundus camera or Digital Single-Lens Reflex (DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of an eye. An algorithm is proposed for cataract screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Finally, a tele-ophthamology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system.

On the performance of SART and ART algorithms for microwave imaging

Science.gov (United States)

Aprilliyani, Ria; Prabowo, Rian Gilang; Basari

2018-02-01

The development of advanced technology leads to the change of human lifestyle in current society. One of the disadvantage impact is arising the degenerative diseases such as cancers and tumors, not just common infectious diseases. Every year, victims of cancers and tumors grow significantly leading to one of the death causes in the world. In early stage, cancer/tumor does not have definite symptoms, but it will grow abnormally as tissue cells and damage normal tissue. Hence, early cancer detection is required. Some common diagnostics modalities such as MRI, CT and PET are quite difficult to be operated in home or mobile environment such as ambulance. Those modalities are also high cost, unpleasant, complex, less safety and harder to move. Hence, this paper proposes a microwave imaging system due to its portability and low cost. In current study, we address on the performance of simultaneous algebraic reconstruction technique (SART) algorithm that was applied in microwave imaging. In addition, SART algorithm performance compared with our previous work on algebraic reconstruction technique (ART), in order to have performance comparison, especially in the case of reconstructed image quality. The result showed that by applying SART algorithm on microwave imaging, suspicious cancer/tumor can be detected with better image quality.

An algorithm for improving the quality of structural images of turbid media in endoscopic optical coherence tomography

Science.gov (United States)

Potlov, A. Yu.; Frolov, S. V.; Proskurin, S. G.

2018-04-01

High-quality OCT structural images reconstruction algorithm for endoscopic optical coherence tomography of biological tissue is described. The key features of the presented algorithm are: (1) raster scanning and averaging of adjacent Ascans and pixels; (2) speckle level minimization. The described algorithm can be used in the gastroenterology, urology, gynecology, otorhinolaryngology for mucous membranes and skin diagnostics in vivo and in situ.

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

Science.gov (United States)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer

Science.gov (United States)

Goto, Atsushi; Nishikawa, Jun; Kiyotoki, Shu; Nakamura, Munetaka; Nishimura, Junichi; Okamoto, Takeshi; Ogihara, Hiroyuki; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

2015-01-01

Hyperspectral imaging (HSI) is a new technology that obtains spectroscopic information and renders it in image form. This study examined the difference in the spectral reflectance (SR) of gastric tumors and normal mucosa recorded with a hyperspectral camera equipped with HSI technology and attempted to determine the specific wavelength that is useful for the diagnosis of gastric cancer. A total of 104 gastric tumors removed by endoscopic submucosal dissection from 96 patients at Yamaguchi University Hospital were recorded using a hyperspectral camera. We determined the optimal wavelength and the cut-off value for differentiating tumors from normal mucosa to establish a diagnostic algorithm. We also attempted to highlight tumors by image processing using the hyperspectral camera's analysis software. A wavelength of 770 nm and a cut-off value of 1/4 the corrected SR were selected as the respective optimal wavelength and cut-off values. The rates of sensitivity, specificity, and accuracy of the algorithm's diagnostic capability were 71%, 98%, and 85%, respectively. It was possible to enhance tumors by image processing at the 770-nm wavelength. HSI can be used to measure the SR in gastric tumors and to differentiate between tumorous and normal mucosa.

Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

Science.gov (United States)

Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

2015-02-01

A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

Enhanced temporal resolution at cardiac CT with a novel CT image reconstruction algorithm: Initial patient experience

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Apfaltrer, Paul, E-mail: paul.apfaltrer@medma.uni-heidelberg.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Schoendube, Harald, E-mail: harald.schoendube@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Schoepf, U. Joseph, E-mail: schoepf@musc.edu [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Allmendinger, Thomas, E-mail: thomas.allmendinger@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Tricarico, Francesco, E-mail: francescotricarico82@gmail.com [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Department of Bioimaging and Radiological Sciences, Catholic University of the Sacred Heart, “A. Gemelli” Hospital, Largo A. Gemelli 8, Rome (Italy); Schindler, Andreas, E-mail: andreas.schindler@campus.lmu.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Vogt, Sebastian, E-mail: sebastian.vogt@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Sunnegårdh, Johan, E-mail: johan.sunnegardh@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); and others

2013-02-15

Objective: To evaluate the effect of a temporal resolution improvement method (TRIM) for cardiac CT on diagnostic image quality for coronary artery assessment. Materials and methods: The TRIM-algorithm employs an iterative approach to reconstruct images from less than 180° of projections and uses a histogram constraint to prevent the occurrence of limited-angle artifacts. This algorithm was applied in 11 obese patients (7 men, 67.2 ± 9.8 years) who had undergone second generation dual-source cardiac CT with 120 kV, 175–426 mAs, and 500 ms gantry rotation. All data were reconstructed with a temporal resolution of 250 ms using traditional filtered-back projection (FBP) and of 200 ms using the TRIM-algorithm. Contrast attenuation and contrast-to-noise-ratio (CNR) were measured in the ascending aorta. The presence and severity of coronary motion artifacts was rated on a 4-point Likert scale. Results: All scans were considered of diagnostic quality. Mean BMI was 36 ± 3.6 kg/m{sup 2}. Average heart rate was 60 ± 9 bpm. Mean effective dose was 13.5 ± 4.6 mSv. When comparing FBP- and TRIM reconstructed series, the attenuation within the ascending aorta (392 ± 70.7 vs. 396.8 ± 70.1 HU, p > 0.05) and CNR (13.2 ± 3.2 vs. 11.7 ± 3.1, p > 0.05) were not significantly different. A total of 110 coronary segments were evaluated. All studies were deemed diagnostic; however, there was a significant (p < 0.05) difference in the severity score distribution of coronary motion artifacts between FBP (median = 2.5) and TRIM (median = 2.0) reconstructions. Conclusion: The algorithm evaluated here delivers diagnostic imaging quality of the coronary arteries despite 500 ms gantry rotation. Possible applications include improvement of cardiac imaging on slower gantry rotation systems or mitigation of the trade-off between temporal resolution and CNR in obese patients.

OPTIMIZATION OF DIAGNOSTIC IMAGING IN BREAST CANCER

Directory of Open Access Journals (Sweden)

S. A. Velichko

2015-01-01

Full Text Available The paper presents the results of breast imaging for 47200 women. Breast cancer was detected in 862 (1.9% patients, fibroadenoma in 1267 (2.7% patients and isolated breast cysts in 1162 (2.4% patients. Different types of fibrocystic breast disease (adenosis, diffuse fibrocystic changes, local fibrosis and others were observed in 60.1% of women. Problems of breast cancer visualization during mammography, characterized by the appearance of fibrocystic mastopathy (sclerosing adenosis, fibrous bands along the ducts have been analyzed. Data on the development of diagnostic algorithms including the modern techniques for ultrasound and interventional radiology aimed at detecting early breast cancer have been presented.  

Recent Advancements in Microwave Imaging Plasma Diagnostics

International Nuclear Information System (INIS)

Park, H.; Chang, C.C.; Deng, B.H.; Domier, C.W.; Donni, A.J.H.; Kawahata, K.; Liang, C.; Liang, X.P.; Lu, H.J.; Luhmann, N.C. Jr.; Mase, A.; Matsuura, H.; Mazzucato, E.; Miura, A.; Mizuno, K.; Munsat, T.; Nagayama, K.; Nagayama, Y.; Pol, M.J. van de; Wang, J.; Xia, Z.G.; Zhang, W-K.

2002-01-01

Significant advances in microwave and millimeter wave technology over the past decade have enabled the development of a new generation of imaging diagnostics for current and envisioned magnetic fusion devices. Prominent among these are revolutionary microwave electron cyclotron emission imaging (ECEI), microwave phase imaging interferometers, imaging microwave scattering and microwave imaging reflectometer (MIR) systems for imaging electron temperature and electron density fluctuations (both turbulent and coherent) and profiles (including transport barriers) on toroidal devices such as tokamaks, spherical tori, and stellarators. The diagnostic technology is reviewed, and typical diagnostic systems are analyzed. Representative experimental results obtained with these novel diagnostic systems are also presented

Image diagnostic of colonic diseases - controversial questions

International Nuclear Information System (INIS)

Pomakov, P.; Rizov, A.; Stancheva, I.

2013-01-01

In the system of colonic diseases' diagnostic algorithm, fibrocolonoscopy (FCS) is defined as 'Golden Standard'. By this reason some X-ray diagnostic methods - irrigography, etc. are currently not being used in a number of health institutions. The aim of this study is a comparative analysis of FCS and irrigography diagnostic efficacy in various colonic diseases. For 10-years period, in cooperation with a gastroenterologist-gastroscopist, 2151 patients with various colonic diseases were evaluated by FCS and irrigography with pharmaco-diagnostics/when necessary. Advantage of FCS was established in diagnosing diseases with patho-morfologic changes on the inner surface of the colon - benign and malignant neoplastic processes, chronic inflammatory diseases, etc. At the same time functional changes - irritated colon syndrome, changes in defecation act, etc., are not an object of diagnosis through FCS. Correction in colonic diseases diagnostic algorithm is necessary. FCS should be mandatory. If result is negative - irrigography with pharmaco-diagnostics should be done. (authors)

Digital image processing an algorithmic approach with Matlab

CERN Document Server

Qidwai, Uvais

2009-01-01

Introduction to Image Processing and the MATLAB EnvironmentIntroduction Digital Image Definitions: Theoretical Account Image Properties MATLAB Algorithmic Account MATLAB CodeImage Acquisition, Types, and File I/OImage Acquisition Image Types and File I/O Basics of Color Images Other Color Spaces Algorithmic Account MATLAB CodeImage ArithmeticIntroduction Operator Basics Theoretical TreatmentAlgorithmic Treatment Coding ExamplesAffine and Logical Operations, Distortions, and Noise in ImagesIntroduction Affine Operations Logical Operators Noise in Images Distortions in ImagesAlgorithmic Account

Complications in diagnostic imaging. 2. ed.

International Nuclear Information System (INIS)

Ansell, G.; Wilkins, R.A.; Medical Research Council, Harrow

1987-01-01

Thirty-seven chapters review various complications which may arise for patients and staff in medical diagnostic imaging. Five of these chapters are indexed separately covering topics on the complications of using radiopharmaceuticals, safety considerations in magnetic resonance imaging, radiation hazards of diagnostic radiology and medico-legal problems involving diagnostic radiology in both the UK and the USA. (UK)

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

Science.gov (United States)

Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics

Directory of Open Access Journals (Sweden)

Achmad Widodo

2012-01-01

Full Text Available This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM. The aim of this work is to develop intelligent maintenance system for machinery based on an alternative way, namely, thermal images instead of vibration signals. SOM is selected due to its simplicity and is categorized as an unsupervised algorithm. Following the SOM training, machine fault diagnostics is performed by using the pattern recognition technique of machine conditions. The data used in this work are thermal images and vibration signals, which were acquired from machine fault simulator (MFS. It is a reliable tool and is able to simulate several conditions of faulty machine such as unbalance, misalignment, looseness, and rolling element bearing faults (outer race, inner race, ball, and cage defects. Data acquisition were conducted simultaneously by infrared thermography camera and vibration sensors installed in the MFS. The experimental data are presented as thermal image and vibration signal in the time domain. Feature extraction was carried out to obtain salient features sensitive to machine conditions from thermal images and vibration signals. These features are then used to train the SOM for intelligent machine diagnostics process. The results show that SOM can perform intelligent fault diagnostics with plausible accuracies.

Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

Science.gov (United States)

Atkins, M. Stella; Hwang, Robert; Tang, Simon

2001-05-01

We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

Effectiveness of a Staged US and Unenhanced MR Imaging Algorithm in the Diagnosis of Pediatric Appendicitis.

Science.gov (United States)

Dibble, Elizabeth H; Swenson, David W; Cartagena, Claudia; Baird, Grayson L; Herliczek, Thaddeus W

2018-03-01

Purpose To establish, in a large cohort, the diagnostic performance of a staged algorithm involving ultrasonography (US) followed by conditional unenhanced magnetic resonance (MR) imaging for the imaging work-up of pediatric appendicitis. Materials and Methods A staged imaging algorithm in which US and unenhanced MR imaging were performed in pediatric patients suspected of having appendicitis was implemented at the authors' institution on January 1, 2011, with US as the initial modality followed by unenhanced MR imaging when US findings were equivocal. A search of the radiology database revealed 2180 pediatric patients who had undergone imaging for suspected appendicitis from January 1, 2011, through December 31, 2012. Of the 2180 patients, 1982 (90.9%) were evaluated according to the algorithm. The authors reviewed the electronic medical records and imaging reports for all patients. Imaging reports were reviewed and classified as positive, negative, or equivocal for appendicitis and correlated with surgical and pathology reports. Results The frequency of appendicitis was 20.5% (407 of 1982 patients). US alone was performed in 1905 of the 1982 patients (96.1%), yielding a sensitivity of 98.7% (386 of 391 patients) and specificity of 97.1% (1470 of 1514 patients) for appendicitis. Seventy-seven patients underwent unenhanced MR imaging after equivocal US findings, yielding an overall algorithm sensitivity of 98.2% (400 of 407 patients) and specificity of 97.1% (1530 of 1575 patients). Seven of the 1982 patients (0.4%) had false-negative results with the staged algorithm. The negative predictive value of the staged algorithm was 99.5% (1530 of 1537 patients). Conclusion A staged algorithm of US and unenhanced MR imaging for pediatric appendicitis appears to be effective. The results of this study demonstrate that this staged algorithm is 98.2% sensitive and 97.1% specific for the diagnosis of appendicitis in pediatric patients. © RSNA, 2017.

Active imaging for monitoring and technical diagnostics

Directory of Open Access Journals (Sweden)

Marek Piszczek

2014-08-01

Full Text Available The article presents the results of currently running work in the field of active imaging. The term active refers to both the image acquisition methods, so-called methods of the spatio-temporal framing and active visualization method applying augmented reality. Also results of application of the HMD and 6DoF modules as well as the experimental laser photography device are given. The device works by methods of spatio-temporal framing and it has been developed at the IOE WAT. In terms of image acquisition - active imaging involves the use of illumination of the observed scene. In the field of information visualization - active imaging directly concerns the issues of interaction human-machine environment. The results show the possibility of using the described techniques, among others, rescue (fire brigade, security of mass events (police or the protection of critical infrastructure as well as broadly understood diagnostic problems. Examples presented in the article show a wide range of possible uses of the methods both in observational techniques and measurement. They are relatively innovative solutions and require elaboration of series of hardware and algorithmic issues. However, already at this stage it is clear that active acquisition and visualization methods indicate a high potential for this type of information solutions.[b]Keywords[/b]: active imaging, augmented reality, digital image processing

Evaluation of virtual monoenergetic imaging algorithms for dual-energy carotid and intracerebral CT angiography: Effects on image quality, artefacts and diagnostic performance for the detection of stenosis.

Science.gov (United States)

Leithner, Doris; Mahmoudi, Scherwin; Wichmann, Julian L; Martin, Simon S; Lenga, Lukas; Albrecht, Moritz H; Booz, Christian; Arendt, Christophe T; Beeres, Martin; D'Angelo, Tommaso; Bodelle, Boris; Vogl, Thomas J; Scholtz, Jan-Erik

2018-02-01

To investigate the impact of traditional (VMI) and noise-optimized virtual monoenergetic imaging (VMI+) algorithms on quantitative and qualitative image quality, and the assessment of stenosis in carotid and intracranial dual-energy CTA (DE-CTA). DE-CTA studies of 40 patients performed on a third-generation 192-slice dual-source CT scanner were included in this retrospective study. 120-kVp image-equivalent linearly-blended, VMI and VMI+ series were reconstructed. Quantitative analysis included evaluation of contrast-to-noise ratios (CNR) of the aorta, common carotid artery, internal carotid artery, middle cerebral artery, and basilar artery. VMI and VMI+ with highest CNR, and linearly-blended series were rated qualitatively. Three radiologists assessed artefacts and suitability for evaluation at shoulder height, carotid bifurcation, siphon, and intracranial using 5-point Likert scales. Detection and grading of stenosis were performed at carotid bifurcation and siphon. Highest CNR values were observed for 40-keV VMI+ compared to 65-keV VMI and linearly-blended images (P evaluation at shoulder and bifurcation height. Suitability was significantly higher in VMI+ and VMI compared to linearly-blended images for intracranial and ICA assessment (P performance. 40-keV VMI+ showed improved quantitative image quality compared to 65-keV VMI and linearly-blended series in supraaortic DE-CTA. VMI and VMI+ provided increased suitability for carotid and intracranial artery evaluation with excellent assessment of stenosis, but did not translate into increased diagnostic performance. Copyright © 2017 Elsevier B.V. All rights reserved.

The diagnostic efficiency of ultrasound guided imaging algorithm in evaluation of patients with hematuria

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Unsal, Alparslan, E-mail: alparslanunsal@yahoo.com [Adnan Menderes University, Faculty of Medicine, Department of Radiology, 09100 Aydin (Turkey); Caliskan, Eda Kazak [Adnan Menderes University, Faculty of Medicine, Department of Radiology, 09100 Aydin (Turkey); Erol, Haluk [Adnan Menderes University, Faculty of Medicine, Department of Urology, 09100 Aydin (Turkey); Karaman, Can Zafer [Adnan Menderes University, Faculty of Medicine, Department of Radiology, 09100 Aydin (Turkey)

2011-07-15

Purpose: To assess the efficiency of the following imaging algorithm, including intravenous urography (IVU) or computed tomography urography (CTU) based on ultrasonographic (US) selection, in the radiological management of hematuria. Materials and methods: One hundred and forty-one patients with hematuria were prospectively evaluated. Group 1 included 106 cases with normal or nearly normal US result and then they were examined with IVU. Group 2 was composed of the remaining 35 cases which had any urinary tract abnormality, and they were directed to CTU. Radiological results were compared with clinical diagnosis. Results: Ultrasonography and IVU results of 97 cases were congruent in group 1. Eight simple cysts were detected with US and 1 non-obstructing ureter stone was detected with IVU in remaining 9 patients. The only discordant case in clinical comparison was found to have urinary bladder cancer on conventional cystoscopy. Ultrasonography and CTU results were congruent in 30 cases. Additional lesions were detected with CTU (3 ureter stones, 1 ureter TCC, 1 advanced RCC) in remaining 5 patients. Ultrasonography + CTU combination results were all concordant with clinical diagnosis. Except 1 case, radio-clinical agreement was achieved. Conclusion: Cross-sectional imaging modalities are preferred in evaluation of hematuria. CTU is the method of choice; however the limitations preclude using CTU as first line or screening test. Ultrasonography is now being accepted as a first line imaging modality with the increased sensitivity in mass detection compared to IVU. The US guided imaging algorithm can be used effectively in radiological approach to hematuria.

Imaging systems for medical diagnostics

International Nuclear Information System (INIS)

Krestel, E.

1990-01-01

This book provides physicians and clinical physicists with detailed information on today's imaging modalities and assists them in selecting the optimal system for each clinical application. Physicists, engineers and computer specialists engaged in research and development and sales departments will also find this book to be of considerable use. It may also be employed at universities, training centers and in technical seminars. The physiological and physical fundamentals are explained in part 1. The technical solutions contained in part 2 illustrate the numerous possibilities available in X-ray diagnostics, computed tomography, nuclear medical diagnostics, magnetic resonance imaging, sonography and biomagnetic diagnostics. (orig.)

Prosthetic joint infection development of an evidence-based diagnostic algorithm.

Science.gov (United States)

Mühlhofer, Heinrich M L; Pohlig, Florian; Kanz, Karl-Georg; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; Kelch, Sarah; Harrasser, Norbert; von Eisenhart-Rothe, Rüdiger; Schauwecker, Johannes

2017-03-09

Increasing rates of prosthetic joint infection (PJI) have presented challenges for general practitioners, orthopedic surgeons and the health care system in the recent years. The diagnosis of PJI is complex; multiple diagnostic tools are used in the attempt to correctly diagnose PJI. Evidence-based algorithms can help to identify PJI using standardized diagnostic steps. We reviewed relevant publications between 1990 and 2015 using a systematic literature search in MEDLINE and PUBMED. The selected search results were then classified into levels of evidence. The keywords were prosthetic joint infection, biofilm, diagnosis, sonication, antibiotic treatment, implant-associated infection, Staph. aureus, rifampicin, implant retention, pcr, maldi-tof, serology, synovial fluid, c-reactive protein level, total hip arthroplasty (THA), total knee arthroplasty (TKA) and combinations of these terms. From an initial 768 publications, 156 publications were stringently reviewed. Publications with class I-III recommendations (EAST) were considered. We developed an algorithm for the diagnostic approach to display the complex diagnosis of PJI in a clear and logically structured process according to ISO 5807. The evidence-based standardized algorithm combines modern clinical requirements and evidence-based treatment principles. The algorithm provides a detailed transparent standard operating procedure (SOP) for diagnosing PJI. Thus, consistently high, examiner-independent process quality is assured to meet the demands of modern quality management in PJI diagnosis.

Using qualitative research to inform development of a diagnostic algorithm for UTI in children.

Science.gov (United States)

de Salis, Isabel; Whiting, Penny; Sterne, Jonathan A C; Hay, Alastair D

2013-06-01

Diagnostic and prognostic algorithms can help reduce clinical uncertainty. The selection of candidate symptoms and signs to be measured in case report forms (CRFs) for potential inclusion in diagnostic algorithms needs to be comprehensive, clearly formulated and relevant for end users. To investigate whether qualitative methods could assist in designing CRFs in research developing diagnostic algorithms. Specifically, the study sought to establish whether qualitative methods could have assisted in designing the CRF for the Health Technology Association funded Diagnosis of Urinary Tract infection in Young children (DUTY) study, which will develop a diagnostic algorithm to improve recognition of urinary tract infection (UTI) in children aged children in primary care and a Children's Emergency Department. We elicited features that clinicians believed useful in diagnosing UTI and compared these for presence or absence and terminology with the DUTY CRF. Despite much agreement between clinicians' accounts and the DUTY CRFs, we identified a small number of potentially important symptoms and signs not included in the CRF and some included items that could have been reworded to improve understanding and final data analysis. This study uniquely demonstrates the role of qualitative methods in the design and content of CRFs used for developing diagnostic (and prognostic) algorithms. Research groups developing such algorithms should consider using qualitative methods to inform the selection and wording of candidate symptoms and signs.

Predicting diagnostic error in Radiology via eye-tracking and image analytics: Application in mammography

Energy Technology Data Exchange (ETDEWEB)

Voisin, Sophie [ORNL; Pinto, Frank M [ORNL; Morin-Ducote, Garnetta [University of Tennessee, Knoxville (UTK); Hudson, Kathy [University of Tennessee, Knoxville (UTK); Tourassi, Georgia [ORNL

2013-01-01

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels. Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from 4 Radiology residents and 2 breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADs images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated. Results: Diagnostic error can be predicted reliably by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model (AUC=0.79). Personalized user modeling was far more accurate for the more experienced readers (average AUC of 0.837 0.029) than for the less experienced ones (average AUC of 0.667 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features. Conclusions: Diagnostic errors in mammography can be predicted reliably by leveraging the radiologists gaze behavior and image content.

Diagnostic Imaging in Snakes and Lizards

OpenAIRE

Banzato , Tommaso

2013-01-01

The increasing popularity of snakes and lizards as pets has led to an increasing demand of specialised veterinary duties in these animals. Diagnostic imaging is often a fundamental step of the clinical investigation. The interpretation of diagnostic images is complex and requires a broad knowledge of anatomy, physiology and pathology of the species object of the clinical investigation. Moreover, in order to achieve a correct diagnosis, the comparison between normal and abnormal diagnostic im...

Diagnostic imaging of shoulder impingement

International Nuclear Information System (INIS)

Merl, T.; Weinhardt, H.; Oettl, G.; Lenz, M.; Riel, K.A.

1996-01-01

Magnetic resonance imaging is a method that has been advancing in the last few years to the modality of choice for diagnostic evaluation of the bone joints, as the method is capable of imaging not only the ossous but also the soft tissue components of the joint. MRI likewise has become an accepted method for diagnostic evaluation of syndromes of the shoulder, with high diagnostic accuracy in detecting rotator cuff lesions, or as an efficient MRI arthrography for evaluation of the instability or lesions of the labrocapsular complex. In the evaluation of early stages of shoulder impingement, the conventional MRI technique as a static technique yields indirect signs which in many cases do not provide the diagnostic certainty required in order to do justice to the functional nature of the syndrome. In these cases, functional MRI for imaging of the arm in abducted position and in rotational movement may offer a chance to early detect impingement and thus identify patients who will profit from treatment at an early stage [de

Ultrasonic particle image velocimetry for improved flow gradient imaging: algorithms, methodology and validation

International Nuclear Information System (INIS)

Niu Lili; Qian Ming; Yu Wentao; Jin Qiaofeng; Ling Tao; Zheng Hairong; Wan Kun; Gao Shen

2010-01-01

This paper presents a new algorithm for ultrasonic particle image velocimetry (Echo PIV) for improving the flow velocity measurement accuracy and efficiency in regions with high velocity gradients. The conventional Echo PIV algorithm has been modified by incorporating a multiple iterative algorithm, sub-pixel method, filter and interpolation method, and spurious vector elimination algorithm. The new algorithms' performance is assessed by analyzing simulated images with known displacements, and ultrasonic B-mode images of in vitro laminar pipe flow, rotational flow and in vivo rat carotid arterial flow. Results of the simulated images show that the new algorithm produces much smaller bias from the known displacements. For laminar flow, the new algorithm results in 1.1% deviation from the analytically derived value, and 8.8% for the conventional algorithm. The vector quality evaluation for the rotational flow imaging shows that the new algorithm produces better velocity vectors. For in vivo rat carotid arterial flow imaging, the results from the new algorithm deviate 6.6% from the Doppler-measured peak velocities averagely compared to 15% of that from the conventional algorithm. The new Echo PIV algorithm is able to effectively improve the measurement accuracy in imaging flow fields with high velocity gradients.

A new chaotic algorithm for image encryption

International Nuclear Information System (INIS)

Gao Haojiang; Zhang Yisheng; Liang Shuyun; Li Dequn

2006-01-01

Recent researches of image encryption algorithms have been increasingly based on chaotic systems, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper presents a new nonlinear chaotic algorithm (NCA) which uses power function and tangent function instead of linear function. Its structural parameters are obtained by experimental analysis. And an image encryption algorithm in a one-time-one-password system is designed. The experimental results demonstrate that the image encryption algorithm based on NCA shows advantages of large key space and high-level security, while maintaining acceptable efficiency. Compared with some general encryption algorithms such as DES, the encryption algorithm is more secure

Role of teleradiology in modern diagnostic imaging

International Nuclear Information System (INIS)

Chrzan, R.; Urbanik, A.; Wyrobek -Renczynska, M.; Podsiadlo, L.

2004-01-01

Teleradiology is a dynamically expanding technology of electronic transmission of radiologic images. History of teleradiology development, methods of obtaining images in digital form, media used for their transmission, factors affecting time of transmission, methods of visualization of transmitted images, attempts at standardization of new technology and at last typical applications of teleradiology were presented. Teleradiology from the position of technical curiosity advanced to the role of everyday work tool. Possibility of specialist diagnostic imaging assurance in poorly developed regions, not possessing sufficient number of radiologists, turned out particularly important. Cooperation of regional hospitals with specialist centers of diagnostic images reporting and archiving created a chance for making better use of owned equipment and reducing the costs of diagnostics. For the sake of broader and broader access to teleradiology not only over the world but also in Poland it is advisable to familiarize with its possibilities by both radiologists and clinicists using the results of diagnostic imaging. (author)

Behaviors study of image registration algorithms in image guided radiation therapy

International Nuclear Information System (INIS)

Zou Lian; Hou Qing

2008-01-01

Objective: Study the behaviors of image registration algorithms, and analyze the elements which influence the performance of image registrations. Methods: Pre-known corresponding coordinates were appointed for reference image and moving image, and then the influence of region of interest (ROI) selection, transformation function initial parameters and coupled parameter spaces on registration results were studied with a software platform developed in home. Results: Region of interest selection had a manifest influence on registration performance. An improperly chosen ROI resulted in a bad registration. Transformation function initial parameters selection based on pre-known information could improve the accuracy of image registration. Coupled parameter spaces would enhance the dependence of image registration algorithm on ROI selection. Conclusions: It is necessary for clinic IGRT to obtain a ROI selection strategy (depending on specific commercial software) correlated to tumor sites. Three suggestions for image registration technique developers are automatic selection of the initial parameters of transformation function based on pre-known information, developing specific image registration algorithm for specific image feature, and assembling real-time image registration algorithms according to tumor sites selected by software user. (authors)

Algorithms for contrast enhancement of electronic portal images

International Nuclear Information System (INIS)

Díez, S.; Sánchez, S.

2015-01-01

An implementation of two new automatized image processing algorithms for contrast enhancement of portal images is presented as suitable tools which facilitate the setup verification and visualization of patients during radiotherapy treatments. In the first algorithm, called Automatic Segmentation and Histogram Stretching (ASHS), the portal image is automatically segmented in two sub-images delimited by the conformed treatment beam: one image consisting of the imaged patient obtained directly from the radiation treatment field, and the second one is composed of the imaged patient outside it. By segmenting the original image, a histogram stretching can be independently performed and improved in both regions. The second algorithm involves a two-step process. In the first step, a Normalization to Local Mean (NLM), an inverse restoration filter is applied by dividing pixel by pixel a portal image by its blurred version. In the second step, named Lineally Combined Local Histogram Equalization (LCLHE), the contrast of the original image is strongly improved by a Local Contrast Enhancement (LCE) algorithm, revealing the anatomical structures of patients. The output image is lineally combined with a portal image of the patient. Finally the output images of the previous algorithms (NLM and LCLHE) are lineally combined, once again, in order to obtain a contrast enhanced image. These two algorithms have been tested on several portal images with great results. - Highlights: • Two Algorithms are implemented to improve the contrast of Electronic Portal Images. • The multi-leaf and conformed beam are automatically segmented into Portal Images. • Hidden anatomical and bony structures in portal images are revealed. • The task related to the patient setup verification is facilitated by the contrast enhancement then achieved.

Improved Bat Algorithm Applied to Multilevel Image Thresholding

Directory of Open Access Journals (Sweden)

Adis Alihodzic

2014-01-01

Full Text Available Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed.

Quantum Image Steganography and Steganalysis Based On LSQu-Blocks Image Information Concealing Algorithm

Science.gov (United States)

A. AL-Salhi, Yahya E.; Lu, Songfeng

2016-08-01

Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.

Diagnostic tests and algorithms used in the investigation of haematuria: systematic reviews and economic evaluation.

Science.gov (United States)

Rodgers, M; Nixon, J; Hempel, S; Aho, T; Kelly, J; Neal, D; Duffy, S; Ritchie, G; Kleijnen, J; Westwood, M

2006-06-01

of false results, but evidence was lacking regarding the accuracy of routine microscopy and estimates were adopted for the model. The model for imaging the upper urinary tract showed that US detects more tumours than IVU at one-third of the cost, and is also associated with fewer false results. For any cause of haematuria, CT was shown to have a mean incremental cost-effectiveness ratio of pounds sterling 9939 in comparison with the next best option, US. When US is followed up with CT for negative results with persistent haematuria, it dominates the initial use of CT alone, with a saving of pounds sterling 235,000 for the evaluation of 1000 patients. The model for investigation of the lower urinary tract showed that for low-risk patients the use of immediate cystoscopy could be avoided if cystoscopy were used for follow-up patients with a negative initial test using tumour markers and/or cytology, resulting in a saving of pounds sterling 483,000 for the evaluation of 1000 patients. The clinical and economic impact on delayed detection of both upper and lower urinary tract tumours through the use of follow-up testing should be evaluated in future studies. There are insufficient data currently available to derive an evidence-based algorithm of the diagnostic pathway for haematuria. A hypothetical algorithm based on the opinion and practice of clinical experts in the review team, other published algorithms and the results of economic modelling is presented in this report. This algorithm is presented, for comparative purposes, alongside current US and UK guidelines. The ideas contained in these algorithms and the specific questions outlined should form the basis of future research. Quality assessment of the diagnostic accuracy studies included in this review highlighted several areas of deficiency.

Comparison of adaptive statistical iterative reconstruction (ASiRTM) and model-based iterative reconstruction (VeoTM) for paediatric abdominal CT examinations: an observer performance study of diagnostic image quality

International Nuclear Information System (INIS)

Hultenmo, Maria; Caisander, Haakan; Mack, Karsten; Thilander-Klang, Anne

2016-01-01

The diagnostic image quality of 75 paediatric abdominal computed tomography (CT) examinations reconstructed with two different iterative reconstruction (IR) algorithms-adaptive statistical IR (ASiR TM ) and model-based IR (Veo TM )-was compared. Axial and coronal images were reconstructed with 70 % ASiR with the Soft TM convolution kernel and with the Veo algorithm. The thickness of the reconstructed images was 2.5 or 5 mm depending on the scanning protocol used. Four radiologists graded the delineation of six abdominal structures and the diagnostic usefulness of the image quality. The Veo reconstruction significantly improved the visibility of most of the structures compared with ASiR in all subgroups of images. For coronal images, the Veo reconstruction resulted in significantly improved ratings of the diagnostic use of the image quality compared with the ASiR reconstruction. This was not seen for the axial images. The greatest improvement using Veo reconstruction was observed for the 2.5 mm coronal slices. (authors)

Facial biometrics of Yorubas of Nigeria using Akinlolu-Raji image-processing algorithm

Directory of Open Access Journals (Sweden)

Adelaja Abdulazeez Akinlolu

2016-01-01

Full Text Available Background: Forensic anthropology deals with the establishment of human identity using genetics, biometrics, and face recognition technology. This study aims to compute facial biometrics of Yorubas of Osun State of Nigeria using a novel Akinlolu-Raji image-processing algorithm. Materials and Methods: Three hundred Yorubas of Osun State (150 males and 150 females, aged 15–33 years were selected as subjects for the study with informed consents and when established as Yorubas by parents and grandparents. Height, body weight, and facial biometrics (evaluated on three-dimensional [3D] facial photographs were measured on all subjects. The novel Akinlolu-Raji image-processing algorithm for forensic face recognition was developed using the modified row method of computer programming. Facial width, total face height, short forehead height, long forehead height, upper face height, nasal bridge length, nose height, morphological face height, and lower face height computed from readings of the Akinlolu-Raji image-processing algorithm were analyzed using z-test (P ≤ 0.05 of 2010 Microsoft Excel statistical software. Results: Statistical analyzes of facial measurements showed nonsignificant higher mean values (P > 0.05 in Yoruba males compared to females. Yoruba males and females have the leptoprosopic face type based on classifications of face types from facial indices. Conclusions: Akinlolu-Raji image-processing algorithm can be employed for computing anthropometric, forensic, diagnostic, or any other measurements on 2D and 3D images, and data computed from its readings can be converted to actual or life sizes as obtained in 1D measurements. Furthermore, Yoruba males and females have the leptoprosopic face type.

Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study

Energy Technology Data Exchange (ETDEWEB)

Nakamoto, Atsushi; Tanaka, Yoshikazu; Juri, Hiroshi; Nakai, Go; Narumi, Yoshifumi [Osaka Medical College, Department of Radiology, Takatsuki, Osaka (Japan); Yoshikawa, Shushi [Osaka Medical College Hospital, Central Radiology Department, Takatsuki, Osaka (Japan)

2017-07-15

To investigate the diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction (IR) algorithm for the detection of hypervascular liver lesions. Thirty liver phantoms with or without simulated hypervascular lesions were scanned with a 320-slice CT scanner with control-dose (40 mAs) and reduced-dose (30 and 20 mAs) settings. Control-dose images were reconstructed with filtered back projection (FBP), and reduced-dose images were reconstructed with FBP and a hybrid IR algorithm. Objective image noise and the lesion to liver contrast-to-noise ratio (CNR) were evaluated quantitatively. Images were interpreted independently by 2 blinded radiologists, and jackknife alternative free-response receiver-operating characteristic (JAFROC) analysis was performed. Hybrid IR images with reduced-dose settings (both 30 and 20 mAs) yielded significantly lower objective image noise and higher CNR than control-dose FBP images (P <.05). However, hybrid IR images with reduced-dose settings had lower JAFROC1 figure of merit than control-dose FBP images, although only the difference between 20 mAs images and control-dose FBP images was significant for both readers (P <.01). An aggressive reduction of the radiation dose would impair the detectability of hypervascular liver lesions, although objective image noise and CNR would be preserved by a hybrid IR algorithm. (orig.)

The neutron imaging diagnostic at NIF (invited).

Science.gov (United States)

Merrill, F E; Bower, D; Buckles, R; Clark, D D; Danly, C R; Drury, O B; Dzenitis, J M; Fatherley, V E; Fittinghoff, D N; Gallegos, R; Grim, G P; Guler, N; Loomis, E N; Lutz, S; Malone, R M; Martinson, D D; Mares, D; Morley, D J; Morgan, G L; Oertel, J A; Tregillis, I L; Volegov, P L; Weiss, P B; Wilde, C H; Wilson, D C

2012-10-01

A neutron imaging diagnostic has recently been commissioned at the National Ignition Facility (NIF). This new system is an important diagnostic tool for inertial fusion studies at the NIF for measuring the size and shape of the burning DT plasma during the ignition stage of Inertial Confinement Fusion (ICF) implosions. The imaging technique utilizes a pinhole neutron aperture, placed between the neutron source and a neutron detector. The detection system measures the two dimensional distribution of neutrons passing through the pinhole. This diagnostic has been designed to collect two images at two times. The long flight path for this diagnostic, 28 m, results in a chromatic separation of the neutrons, allowing the independently timed images to measure the source distribution for two neutron energies. Typically the first image measures the distribution of the 14 MeV neutrons and the second image of the 6-12 MeV neutrons. The combination of these two images has provided data on the size and shape of the burning plasma within the compressed capsule, as well as a measure of the quantity and spatial distribution of the cold fuel surrounding this core.

The neutron imaging diagnostic at NIF (invited)

Energy Technology Data Exchange (ETDEWEB)

Merrill, F. E.; Clark, D. D.; Danly, C. R.; Drury, O. B.; Fatherley, V. E.; Gallegos, R.; Grim, G. P.; Guler, N.; Loomis, E. N.; Martinson, D. D.; Mares, D.; Morley, D. J.; Morgan, G. L.; Oertel, J. A.; Tregillis, I. L.; Volegov, P. L.; Wilde, C. H.; Wilson, D. C. [Los Alamos National Laboratory, Los Alamos, New Mexico 87544 (United States); Bower, D.; Dzenitis, J. M. [Livermore National Laboratory, Livermore, California 94550 (United States); and others

2012-10-15

A neutron imaging diagnostic has recently been commissioned at the National Ignition Facility (NIF). This new system is an important diagnostic tool for inertial fusion studies at the NIF for measuring the size and shape of the burning DT plasma during the ignition stage of Inertial Confinement Fusion (ICF) implosions. The imaging technique utilizes a pinhole neutron aperture, placed between the neutron source and a neutron detector. The detection system measures the two dimensional distribution of neutrons passing through the pinhole. This diagnostic has been designed to collect two images at two times. The long flight path for this diagnostic, 28 m, results in a chromatic separation of the neutrons, allowing the independently timed images to measure the source distribution for two neutron energies. Typically the first image measures the distribution of the 14 MeV neutrons and the second image of the 6-12 MeV neutrons. The combination of these two images has provided data on the size and shape of the burning plasma within the compressed capsule, as well as a measure of the quantity and spatial distribution of the cold fuel surrounding this core.

Image-based Proof of Work Algorithm for the Incentivization of Blockchain Archival of Interesting Images

OpenAIRE

Billings, Jake

2017-01-01

A new variation of blockchain proof of work algorithm is proposed to incentivize the timely execution of image processing algorithms. A sample image processing algorithm is proposed to determine interesting images using analysis of the entropy of pixel subsets within images. The efficacy of the image processing algorithm is examined using two small sets of training and test data. The interesting image algorithm is then integrated into a simplified blockchain mining proof of work algorithm bas...

Image enhancement of digital periapical radiographs according to diagnostic tasks

International Nuclear Information System (INIS)

Choi, Jin Woo; Han, Won Jeong; Kim, Eun Kyung

2014-01-01

his study was performed to investigate the effect of image enhancement of periapical radiographs according to the diagnostic task. Eighty digital intraoral radiographs were obtained from patients and classified into four groups according to the diagnostic tasks of dental caries, periodontal diseases, periapical lesions, and endodontic files. All images were enhanced differently by using five processing techniques. Three radiologists blindly compared the subjective image quality of the original images and the processed images using a 5-point scale. There were significant differences between the image quality of the processed images and that of the original images (P<0.01) in all the diagnostic task groups. Processing techniques showed significantly different efficacy according to the diagnostic task (P<0.01). Image enhancement affects the image quality differently depending on the diagnostic task. And the use of optimal parameters is important for each diagnostic task.

Image enhancement of digital periapical radiographs according to diagnostic tasks

Energy Technology Data Exchange (ETDEWEB)

Choi, Jin Woo; Han, Won Jeong; Kim, Eun Kyung [Dept. of Oral and Maxillofacial Radiology, Dankook University College of Dentistry, Cheonan (Korea, Republic of)

2014-03-15

his study was performed to investigate the effect of image enhancement of periapical radiographs according to the diagnostic task. Eighty digital intraoral radiographs were obtained from patients and classified into four groups according to the diagnostic tasks of dental caries, periodontal diseases, periapical lesions, and endodontic files. All images were enhanced differently by using five processing techniques. Three radiologists blindly compared the subjective image quality of the original images and the processed images using a 5-point scale. There were significant differences between the image quality of the processed images and that of the original images (P<0.01) in all the diagnostic task groups. Processing techniques showed significantly different efficacy according to the diagnostic task (P<0.01). Image enhancement affects the image quality differently depending on the diagnostic task. And the use of optimal parameters is important for each diagnostic task.

Optimization-Based Image Segmentation by Genetic Algorithms

Directory of Open Access Journals (Sweden)

Rosenberger C

2008-01-01

Full Text Available Abstract Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.

Optimization-Based Image Segmentation by Genetic Algorithms

Directory of Open Access Journals (Sweden)

H. Laurent

2008-05-01

Full Text Available Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.

A diagnostic algorithm for atypical spitzoid tumors: guidelines for immunohistochemical and molecular assessment.

Science.gov (United States)

Cho-Vega, Jeong Hee

2016-07-01

Atypical spitzoid tumors are a morphologically diverse group of rare melanocytic lesions most frequently seen in children and young adults. As atypical spitzoid tumors bear striking resemblance to Spitz nevus and spitzoid melanomas clinically and histopathologically, it is crucial to determine its malignant potential and predict its clinical behavior. To date, many researchers have attempted to differentiate atypical spitzoid tumors from unequivocal melanomas based on morphological, immonohistochemical, and molecular diagnostic differences. A diagnostic algorithm is proposed here to assess the malignant potential of atypical spitzoid tumors by using a combination of immunohistochemical and cytogenetic/molecular tests. Together with classical morphological evaluation, this algorithm includes a set of immunohistochemistry assays (p16(Ink4a), a dual-color Ki67/MART-1, and HMB45), fluorescence in situ hybridization (FISH) with five probes (6p25, 8q24, 11q13, CEN9, and 9p21), and an array-based comparative genomic hybridization. This review discusses details of the algorithm, the rationale of each test used in the algorithm, and utility of this algorithm in routine dermatopathology practice. This algorithmic approach will provide a comprehensive diagnostic tool that complements conventional histological criteria and will significantly contribute to improve the diagnosis and prediction of the clinical behavior of atypical spitzoid tumors.

Structured diagnostic imaging in patients with multiple trauma; Strukturierte radiologische Diagnostik beim Polytrauma

Energy Technology Data Exchange (ETDEWEB)

Linsenmaier, U.; Rieger, J.; Rock, C.; Pfeifer, K.J.; Reiser, M. [Institut fuer Klinische Radiologie, Klinikum der Universitaet Muenchen, Innenstadt (Germany); Kanz, K.G. [Chirurgische Klinik, Klinikum der Universitaet Muenchen, Innenstadt (Germany)

2002-07-01

Purpose. Development of a concept for structured diagnostic imaging in patients with multiple trauma.Material and methods. Evaluation of data from a prospective trial with over 2400 documented patients with multiple trauma. All diagnostic and therapeutic steps, primary and secondary death and the 90 days lethality were documented.Structured diagnostic imaging of multiple injured patients requires the integration of an experienced radiologist in an interdisciplinary trauma team consisting of anesthesia, radiology and trauma surgery. Radiology itself deserves standardized concepts for equipment, personnel and logistics to perform diagnostic imaging for a 24-h-coverage with constant quality.Results. This paper describes criteria for initiation of a shock room or emergency room treatment, strategies for documentation and interdisciplinary algorithms for the early clinical care coordinating diagnostic imaging and therapeutic procedures following standardized guidelines. Diagnostic imaging consists of basic diagnosis, radiological ABC-rule, radiological follow-up and structured organ diagnosis using CT. Radiological trauma scoring allows improved quality control of diagnosis and therapy of multiple injured patients.Conclusion. Structured diagnostic imaging of multiple injured patients leads to a standardization of diagnosis and therapy and ensures constant process quality. (orig.) [German] Fragestellung. Entwicklung eines strukturierten Konzeptes zur radiologischen Diagnostik polytraumatisierter Patienten.Methodik. Die Datenevaluation erfolgte auf Basis einer prospektiven interdisziplinaere Polytraumastudie mit ueber 2400 Patienten. Alle diagnostischen und therapeutischen Schritte werden jeweils unter Angabe von Zeitpunkt und auftretenden Komplikationen erfasst, ein primaeres oder sekundaeres Versterben und die 90-Tage-Letalitaet werden dokumentiert.Die strukturierte radiologische Diagnostik von Mehrfachverletzen verlangt die Integration eines erfahrenen Radiologen in

Algorithmic acquisition of diagnostic patterns in district heating billing system

International Nuclear Information System (INIS)

Kiluk, Sebastian

2012-01-01

An application of algorithmic exploration of billing data is examined for fault detection, diagnosis (FDD) based on evaluation of present state and detection of unexpected changes in energy efficiency of buildings. Large data sets from district heating (DH) billing systems are used for construction of feature space, diagnostic rules and classification of the buildings according to their energy efficiency properties. The algorithmic approach automates discovering knowledge about common, thus accepted changes in buildings’ properties, in equipment and in habitants’ behavior reflecting progress in technology and life style. In this article implementation of Data Mining and Knowledge Discovery (DMKD) method in supervision system with exemplary results based on real data is presented. Crucial steps of data processing influencing diagnostic results are described in details.

Half-unit weighted bilinear algorithm for image contrast enhancement in capsule endoscopy

Science.gov (United States)

Rukundo, Olivier

2018-04-01

This paper proposes a novel enhancement method based exclusively on the bilinear interpolation algorithm for capsule endoscopy images. The proposed method does not convert the original RBG image components to HSV or any other color space or model; instead, it processes directly RGB components. In each component, a group of four adjacent pixels and half-unit weight in the bilinear weighting function are used to calculate the average pixel value, identical for each pixel in that particular group. After calculations, groups of identical pixels are overlapped successively in horizontal and vertical directions to achieve a preliminary-enhanced image. The final-enhanced image is achieved by halving the sum of the original and preliminary-enhanced image pixels. Quantitative and qualitative experiments were conducted focusing on pairwise comparisons between original and enhanced images. Final-enhanced images have generally the best diagnostic quality and gave more details about the visibility of vessels and structures in capsule endoscopy images.

The Downside of Diagnostic Imaging

Science.gov (United States)

An article about radiation exposure during computed tomography and nuclear imaging procedures and the risk of cancer. Several studies released in 2009 have helped to quantify the risk and the growing use of these diagnostic imaging methods.

Preparing diagnostic 3D images for image registration with planning CT images

International Nuclear Information System (INIS)

Tracton, Gregg S.; Miller, Elizabeth P.; Rosenman, Julian; Chang, Sha X.; Sailer, Scott; Boxwala, Azaz; Chaney, Edward L.

1997-01-01

Purpose: Pre-radiotherapy (pre-RT) tomographic images acquired for diagnostic purposes often contain important tumor and/or normal tissue information which is poorly defined or absent in planning CT images. Our two years of clinical experience has shown that computer-assisted 3D registration of pre-RT images with planning CT images often plays an indispensable role in accurate treatment volume definition. Often the only available format of the diagnostic images is film from which the original 3D digital data must be reconstructed. In addition, any digital data, whether reconstructed or not, must be put into a form suitable for incorporation into the treatment planning system. The purpose of this investigation was to identify all problems that must be overcome before this data is suitable for clinical use. Materials and Methods: In the past two years we have 3D-reconstructed 300 diagnostic images from film and digital sources. As a problem was discovered we built a software tool to correct it. In time we collected a large set of such tools and found that they must be applied in a specific order to achieve the correct reconstruction. Finally, a toolkit (ediScan) was built that made all these tools available in the proper manner via a pleasant yet efficient mouse-based user interface. Results: Problems we discovered included different magnifications, shifted display centers, non-parallel image planes, image planes not perpendicular to the long axis of the table-top (shearing), irregularly spaced scans, non contiguous scan volumes, multiple slices per film, different orientations for slice axes (e.g. left-right reversal), slices printed at window settings corresponding to tissues of interest for diagnostic purposes, and printing artifacts. We have learned that the specific steps to correct these problems, in order of application, are: Also, we found that fast feedback and large image capacity (at least 2000 x 2000 12-bit pixels) are essential for practical application

A combinational fast algorithm for image reconstruction

International Nuclear Information System (INIS)

Wu Zhongquan

1987-01-01

A combinational fast algorithm has been developed in order to increase the speed of reconstruction. First, an interpolation method based on B-spline functions is used in image reconstruction. Next, the influence of the boundary conditions assumed here on the interpolation of filtered projections and on the image reconstruction is discussed. It is shown that this boundary condition has almost no influence on the image in the central region of the image space, because the error of interpolation rapidly decreases by a factor of ten in shifting two pixels from the edge toward the center. In addition, a fast algorithm for computing the detecting angle has been used with the mentioned interpolation algorithm, and the cost for detecting angle computaton is reduced by a factor of two. The implementation results show that in the same subjective and objective fidelity, the computational cost for the interpolation using this algorithm is about one-twelfth of the conventional algorithm

Incident Light Frequency-Based Image Defogging Algorithm

Directory of Open Access Journals (Sweden)

Wenbo Zhang

2017-01-01

Full Text Available To solve the color distortion problem produced by the dark channel prior algorithm, an improved method for calculating transmittance of all channels, respectively, was proposed in this paper. Based on the Beer-Lambert Law, the influence between the frequency of the incident light and the transmittance was analyzed, and the ratios between each channel’s transmittance were derived. Then, in order to increase efficiency, the input image was resized to a smaller size before acquiring the refined transmittance which will be resized to the same size of original image. Finally, all the transmittances were obtained with the help of the proportion between each color channel, and then they were used to restore the defogging image. Experiments suggest that the improved algorithm can produce a much more natural result image in comparison with original algorithm, which means the problem of high color saturation was eliminated. What is more, the improved algorithm speeds up by four to nine times compared to the original algorithm.

Investigation into diagnostic agreement using automated computer-assisted histopathology pattern recognition image analysis

Directory of Open Access Journals (Sweden)

Joshua D Webster

2012-01-01

Full Text Available The extent to which histopathology pattern recognition image analysis (PRIA agrees with microscopic assessment has not been established. Thus, a commercial PRIA platform was evaluated in two applications using whole-slide images. Substantial agreement, lacking significant constant or proportional errors, between PRIA and manual morphometric image segmentation was obtained for pulmonary metastatic cancer areas (Passing/Bablok regression. Bland-Altman analysis indicated heteroscedastic measurements and tendency toward increasing variance with increasing tumor burden, but no significant trend in mean bias. The average between-methods percent tumor content difference was -0.64. Analysis of between-methods measurement differences relative to the percent tumor magnitude revealed that method disagreement had an impact primarily in the smallest measurements (tumor burden 0.988, indicating high reproducibility for both methods, yet PRIA reproducibility was superior (C.V.: PRIA = 7.4, manual = 17.1. Evaluation of PRIA on morphologically complex teratomas led to diagnostic agreement with pathologist assessments of pluripotency on subsets of teratomas. Accommodation of the diversity of teratoma histologic features frequently resulted in detrimental trade-offs, increasing PRIA error elsewhere in images. PRIA error was nonrandom and influenced by variations in histomorphology. File-size limitations encountered while training algorithms and consequences of spectral image processing dominance contributed to diagnostic inaccuracies experienced for some teratomas. PRIA appeared better suited for tissues with limited phenotypic diversity. Technical improvements may enhance diagnostic agreement, and consistent pathologist input will benefit further development and application of PRIA.

Investigation into diagnostic agreement using automated computer-assisted histopathology pattern recognition image analysis.

Science.gov (United States)

Webster, Joshua D; Michalowski, Aleksandra M; Dwyer, Jennifer E; Corps, Kara N; Wei, Bih-Rong; Juopperi, Tarja; Hoover, Shelley B; Simpson, R Mark

2012-01-01

The extent to which histopathology pattern recognition image analysis (PRIA) agrees with microscopic assessment has not been established. Thus, a commercial PRIA platform was evaluated in two applications using whole-slide images. Substantial agreement, lacking significant constant or proportional errors, between PRIA and manual morphometric image segmentation was obtained for pulmonary metastatic cancer areas (Passing/Bablok regression). Bland-Altman analysis indicated heteroscedastic measurements and tendency toward increasing variance with increasing tumor burden, but no significant trend in mean bias. The average between-methods percent tumor content difference was -0.64. Analysis of between-methods measurement differences relative to the percent tumor magnitude revealed that method disagreement had an impact primarily in the smallest measurements (tumor burden 0.988, indicating high reproducibility for both methods, yet PRIA reproducibility was superior (C.V.: PRIA = 7.4, manual = 17.1). Evaluation of PRIA on morphologically complex teratomas led to diagnostic agreement with pathologist assessments of pluripotency on subsets of teratomas. Accommodation of the diversity of teratoma histologic features frequently resulted in detrimental trade-offs, increasing PRIA error elsewhere in images. PRIA error was nonrandom and influenced by variations in histomorphology. File-size limitations encountered while training algorithms and consequences of spectral image processing dominance contributed to diagnostic inaccuracies experienced for some teratomas. PRIA appeared better suited for tissues with limited phenotypic diversity. Technical improvements may enhance diagnostic agreement, and consistent pathologist input will benefit further development and application of PRIA.

Overuse of Diagnostic Imaging for Work-Related Injuries.

Science.gov (United States)

Clendenin, Brianna Rebecca; Conlon, Helen Acree; Burns, Candace

2017-02-01

Overuse of health care in the United States is a growing concern. This article addresses the use of diagnostic imaging for work-related injuries. Diagnostic imaging drives substantial cost for increases in workers' compensation. Despite guidelines published by the American College of Radiology and the American College of Occupational Medicine and the Official Disability Guidelines, practitioners are prematurely ordering imaging sooner than recommended. Workers are exposed to unnecessary radiation and are incurring increasing costs without evidence of better outcomes. Practitioners caring for workers and submitting workers' compensation claims should adhere to official guidelines, using their professional judgment to consider financial impact and health outcomes of diagnostic imaging including computed tomography, magnetic resonance imaging, nuclear medicine imaging, radiography, and ultrasound.

Managing digitally formatted diagnostic image data

International Nuclear Information System (INIS)

Templeton, A.W.; Dwyer, S.J.

1985-01-01

Diagnostic radiologists are very comfortable using analog radiographic film and interpreting its recorded images. To improve patient care, the radiologist has sought the finest quality radiographic film for use with the best radiographic imaging systems. The proper choice and use of x-ray tubes, generators, film-screen combinations, and contrast media has occupied the professional attention of the radiologist since the inception of radiology. Image quality can be significantly improved with digitally formatted diagnostic imaging systems by providing dynamic ranges in excess of those possible with analog x-ray films. In a CT scanner, the digital acquisition and reconstruction system can obtain a dynamic range (contrast resolution) of 10,000 to 1. Digital subtraction angiography systems achieve 10-bit dynamic ranges for each of the acquired television frames. Increases in the dynamic ranges of the various imaging modalities have been coupled with improved spatial resolution. A digitally formatted image is a two-dimensional, numerical array of discrete image elements. Each picture element is called a pixel. Each pixel has a discrete size. Figure 15.1 illustrates a digitally formatted image depicting the spatial resolution, array size, and quantization or numerical range of the pixel values. Currently, 512 x 512 image arrays are standard. Development of 1024 x 1024 digital arrays are underway. Significant improvements have also been achieved in the rates at which digital diagnostic imaging data can be acquired, manipulated, and archived

Does MR imaging effectively replace diagnostic arthroscopy

International Nuclear Information System (INIS)

Ruwe, P.; McCarthy, S.; Wright, J.; Randall, L.; Lynch, K.; Jokyl, P.

1990-01-01

This paper determines if MR imaging reduces the number of diagnostic arthroscopic procedures required in patients with knee complaints and if MR imaging is cost-effective compared with diagnostic arthroscopy. The cohort analysis consists of 100 patients seen in a sports medicine clinic by two orthopedic surgeons who agreed on well-defined criteria for performing MR imaging and arthroscopy. Each orthopedic surgeon referring a patient for MR imaging checked a form regarding the plans for arthroscopy. Outcome analysis was conducted at 6 months

Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

International Nuclear Information System (INIS)

Voisin, Sophie; Tourassi, Georgia D.; Pinto, Frank; Morin-Ducote, Garnetta; Hudson, Kathleen B.

2013-01-01

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content

Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

Energy Technology Data Exchange (ETDEWEB)

Voisin, Sophie; Tourassi, Georgia D. [Biomedical Science and Engineering Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Pinto, Frank [School of Engineering, Science, and Technology, Virginia State University, Petersburg, Virginia 23806 (United States); Morin-Ducote, Garnetta; Hudson, Kathleen B. [Department of Radiology, University of Tennessee Medical Center at Knoxville, Knoxville, Tennessee 37920 (United States)

2013-10-15

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content.

Comparison of SeaWinds Backscatter Imaging Algorithms

Science.gov (United States)

Long, David G.

2017-01-01

This paper compares the performance and tradeoffs of various backscatter imaging algorithms for the SeaWinds scatterometer when multiple passes over a target are available. Reconstruction methods are compared with conventional gridding algorithms. In particular, the performance and tradeoffs in conventional ‘drop in the bucket’ (DIB) gridding at the intrinsic sensor resolution are compared to high-spatial-resolution imaging algorithms such as fine-resolution DIB and the scatterometer image reconstruction (SIR) that generate enhanced-resolution backscatter images. Various options for each algorithm are explored, including considering both linear and dB computation. The effects of sampling density and reconstruction quality versus time are explored. Both simulated and actual data results are considered. The results demonstrate the effectiveness of high-resolution reconstruction using SIR as well as its limitations and the limitations of DIB and fDIB. PMID:28828143

Advantages of digital imaging for radiological diagnostic

International Nuclear Information System (INIS)

Trapero, M. A.; Gonzalez, S.; Albillos, J. C.; Martel, J.; Rebollo, M.

2006-01-01

The advantages and limitations of radiological digital images in comparison with analogic ones are analyzed. We discuss three main topics: acquisition, post-procedure manipulation, and visualization, archive and communication. Digital acquisition with computed radiology systems present a global sensitivity very close to conventional film for diagnostic purposes. However, flat panel digital systems seems to achieve some advantages in particular clinical situations. A critical issue is the radiation dose-reduction that can be accomplished without reducing image quality nor diagnostic exactitude. The post-procedure manipulation allows, particularly in multiplanar modalities like CT or MR, to extract all implicit diagnostic information in the images: Main procedures are multiplanar and three-dimensional reformations, dynamic acquisitions, functional studies and image fusion. The use of PACS for visualization, archive and communication of images, improves the effectiveness and the efficiency of the workflow, allows a more comfortable diagnosis for the radiologist and gives way to improvements in the communication of images, allowing tele consulting and the tele radiology. (Author) 6 refs

Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms

International Nuclear Information System (INIS)

Sidky, Emil Y.; Pan Xiaochuan; Reiser, Ingrid S.; Nishikawa, Robert M.; Moore, Richard H.; Kopans, Daniel B.

2009-01-01

Purpose: The authors develop a practical, iterative algorithm for image-reconstruction in undersampled tomographic systems, such as digital breast tomosynthesis (DBT). Methods: The algorithm controls image regularity by minimizing the image total p variation (TpV), a function that reduces to the total variation when p=1.0 or the image roughness when p=2.0. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets. The fact that the tomographic system is undersampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) Reduction in the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in undersampled tomography. Results: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. Conclusions: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.

Approximation algorithms for a genetic diagnostics problem.

Science.gov (United States)

Kosaraju, S R; Schäffer, A A; Biesecker, L G

1998-01-01

We define and study a combinatorial problem called WEIGHTED DIAGNOSTIC COVER (WDC) that models the use of a laboratory technique called genotyping in the diagnosis of an important class of chromosomal aberrations. An optimal solution to WDC would enable us to define a genetic assay that maximizes the diagnostic power for a specified cost of laboratory work. We develop approximation algorithms for WDC by making use of the well-known problem SET COVER for which the greedy heuristic has been extensively studied. We prove worst-case performance bounds on the greedy heuristic for WDC and for another heuristic we call directional greedy. We implemented both heuristics. We also implemented a local search heuristic that takes the solutions obtained by greedy and dir-greedy and applies swaps until they are locally optimal. We report their performance on a real data set that is representative of the options that a clinical geneticist faces for the real diagnostic problem. Many open problems related to WDC remain, both of theoretical interest and practical importance.

A three-dimensional-weighted cone beam filtered backprojection (CB-FBP) algorithm for image reconstruction in volumetric CT-helical scanning

International Nuclear Information System (INIS)

Tang Xiangyang; Hsieh Jiang; Nilsen, Roy A; Dutta, Sandeep; Samsonov, Dmitry; Hagiwara, Akira

2006-01-01

Based on the structure of the original helical FDK algorithm, a three-dimensional (3D)-weighted cone beam filtered backprojection (CB-FBP) algorithm is proposed for image reconstruction in volumetric CT under helical source trajectory. In addition to its dependence on view and fan angles, the 3D weighting utilizes the cone angle dependency of a ray to improve reconstruction accuracy. The 3D weighting is ray-dependent and the underlying mechanism is to give a favourable weight to the ray with the smaller cone angle out of a pair of conjugate rays but an unfavourable weight to the ray with the larger cone angle out of the conjugate ray pair. The proposed 3D-weighted helical CB-FBP reconstruction algorithm is implemented in the cone-parallel geometry that can improve noise uniformity and image generation speed significantly. Under the cone-parallel geometry, the filtering is naturally carried out along the tangential direction of the helical source trajectory. By exploring the 3D weighting's dependence on cone angle, the proposed helical 3D-weighted CB-FBP reconstruction algorithm can provide significantly improved reconstruction accuracy at moderate cone angle and high helical pitches. The 3D-weighted CB-FBP algorithm is experimentally evaluated by computer-simulated phantoms and phantoms scanned by a diagnostic volumetric CT system with a detector dimension of 64 x 0.625 mm over various helical pitches. The computer simulation study shows that the 3D weighting enables the proposed algorithm to reach reconstruction accuracy comparable to that of exact CB reconstruction algorithms, such as the Katsevich algorithm, under a moderate cone angle (4 deg.) and various helical pitches. Meanwhile, the experimental evaluation using the phantoms scanned by a volumetric CT system shows that the spatial resolution along the z-direction and noise characteristics of the proposed 3D-weighted helical CB-FBP reconstruction algorithm are maintained very well in comparison to the FDK

Diagnostic imaging capabilities of the Ocelot -Optical Coherence Tomography System, ex-vivo evaluation and clinical relevance

International Nuclear Information System (INIS)

Dohad, Suhail; Shao, John; Cawich, Ian; Kankaria, Manish; Desai, Arjun

2015-01-01

consistent physician interpretation of images acquired by the Ocelot and the Dragonfly OCT systems in-spite of distinct image processing algorithms and catheter configurations. This represents a dramatic shift away from both fluoroscopic imaging and diagnostic-only OCT imaging during peripheral arterial intervention towards therapeutic devices that incorporate real time diagnostic OCT imaging. In the clinical practice, these diagnostic capabilities have translated to best-in-class safety and efficacy for CTO crossing using the Ocelot catheter

Adaptive Algorithms for Automated Processing of Document Images

Science.gov (United States)

2011-01-01

ABSTRACT Title of dissertation: ADAPTIVE ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES Mudit Agrawal, Doctor of Philosophy, 2011...2011 4. TITLE AND SUBTITLE Adaptive Algorithms for Automated Processing of Document Images 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES by Mudit Agrawal Dissertation submitted to the Faculty of the Graduate School of the University

High speed display algorithm for 3D medical images using Multi Layer Range Image

International Nuclear Information System (INIS)

Ban, Hideyuki; Suzuki, Ryuuichi

1993-01-01

We propose high speed algorithm that display 3D voxel images obtained from medical imaging systems such as MRI. This algorithm convert voxel image data to 6 Multi Layer Range Image (MLRI) data, which is an augmentation of the range image data. To avoid the calculation for invisible voxels, the algorithm selects at most 3 MLRI data from 6 in accordance with the view direction. The proposed algorithm displays 256 x 256 x 256 voxel data within 0.6 seconds using 22 MIPS Workstation without a special hardware such as Graphics Engine. Real-time display will be possible on 100 MIPS class Workstation by our algorithm. (author)

Combining a thermal-imaging diagnostic with an existing imaging VISAR diagnostic at the National Ignition Facility (NIF)

International Nuclear Information System (INIS)

Robert M, Malone; John R, Celesteb; Peter M, Celliers; Brent C, Froggeta; Robert L, Guyton; Morris I, Kaufman; Tony L, Lee; Brian J, MacGowan; Edmund W, Ng; Imants P, Reinbachs; Ronald B, Robinson; Lynn G, Seppala; Tom W, Tunnell; Phillip W, Watts

2005-01-01

Optical diagnostics are currently being designed to analyze high-energy density physics experiments at the National Ignition Facility (NIF). Two independent line-imaging Velocity Interferometer System for Any Reflector (VISAR) interferometers have been fielded to measure shock velocities, breakout times, and emission of targets having sizes of 1-5 mm. An 8-inch-diameter, fused silica triplet lens collects light at f/3 inside the 30-foot-diameter NIF vacuum chamber. VISAR recordings use a 659.5-nm probe laser. By adding a specially coated beam splitter to the interferometer table, light at wavelengths from 540 to 645 nm is spilt into a thermal-imaging diagnostic. Because fused silica lenses are used in the first triplet relay, the intermediate image planes for different wavelengths separate by considerable distances. A corrector lens on the interferometer table reunites these separated wavelength planes to provide a good image. Thermal imaging collects light at f/5 from a 2-mm object placed at Target Chamber Center (TCC). Streak cameras perform VISAR and thermal-imaging recording. All optical lenses are on kinematic mounts so that pointing accuracy of the optical axis may be checked. Counter-propagating laser beams (orange and red) are used to align both diagnostics. The red alignment laser is selected to be at the 50 percent reflection point of the beam splitter. This alignment laser is introduced at the recording streak cameras for both diagnostics and passes through this special beam splitter on its way into the NIF vacuum chamber

Impact of an intra-cycle motion correction algorithm on overall evaluability and diagnostic accuracy of computed tomography coronary angiography

Energy Technology Data Exchange (ETDEWEB)

Pontone, Gianluca; Bertella, Erika; Baggiano, Andrea; Mushtaq, Saima; Loguercio, Monica; Segurini, Chiara; Conte, Edoardo; Beltrama, Virginia; Annoni, Andrea; Formenti, Alberto; Petulla, Maria; Trabattoni, Daniela; Pepi, Mauro [Centro Cardiologico Monzino, IRCCS, Milan (Italy); Andreini, Daniele; Montorsi, Piero; Bartorelli, Antonio L. [Centro Cardiologico Monzino, IRCCS, Milan (Italy); University of Milan, Department of Cardiovascular Sciences and Community Health, Milan (Italy); Guaricci, Andrea I. [University of Foggia, Department of Cardiology, Foggia (Italy)

2016-01-15

The aim of this study was to evaluate the impact of a novel intra-cycle motion correction algorithm (MCA) on overall evaluability and diagnostic accuracy of cardiac computed tomography coronary angiography (CCT). From a cohort of 900 consecutive patients referred for CCT for suspected coronary artery disease (CAD), we enrolled 160 (18 %) patients (mean age 65.3 ± 11.7 years, 101 male) with at least one coronary segment classified as non-evaluable for motion artefacts. The CCT data sets were evaluated using a standard reconstruction algorithm (SRA) and MCA and compared in terms of subjective image quality, evaluability and diagnostic accuracy. The mean heart rate during the examination was 68.3 ± 9.4 bpm. The MCA showed a higher Likert score (3.1 ± 0.9 vs. 2.5 ± 1.1, p < 0.001) and evaluability (94%vs.79 %, p < 0.001) than the SRA. In a 45-patient subgroup studied by clinically indicated invasive coronary angiography, specificity, positive predictive value and accuracy were higher in MCA vs. SRA in segment-based and vessel-based models, respectively (87%vs.73 %, 50%vs.34 %, 85%vs.73 %, p < 0.001 and 62%vs.28 %, 66%vs.51 % and 75%vs.57 %, p < 0.001). In a patient-based model, MCA showed higher accuracy vs. SCA (93%vs.76 %, p < 0.05). MCA can significantly improve subjective image quality, overall evaluability and diagnostic accuracy of CCT. (orig.)

Algorithms for boundary detection in radiographic images

International Nuclear Information System (INIS)

Gonzaga, Adilson; Franca, Celso Aparecido de

1996-01-01

Edge detecting techniques applied to radiographic digital images are discussed. Some algorithms have been implemented and the results are displayed to enhance boundary or hide details. An algorithm applied in a pre processed image with contrast enhanced is proposed and the results are discussed

Digital Image Encryption Algorithm Design Based on Genetic Hyperchaos

Directory of Open Access Journals (Sweden)

Jian Wang

2016-01-01

Full Text Available In view of the present chaotic image encryption algorithm based on scrambling (diffusion is vulnerable to choosing plaintext (ciphertext attack in the process of pixel position scrambling, we put forward a image encryption algorithm based on genetic super chaotic system. The algorithm, by introducing clear feedback to the process of scrambling, makes the scrambling effect related to the initial chaos sequence and the clear text itself; it has realized the image features and the organic fusion of encryption algorithm. By introduction in the process of diffusion to encrypt plaintext feedback mechanism, it improves sensitivity of plaintext, algorithm selection plaintext, and ciphertext attack resistance. At the same time, it also makes full use of the characteristics of image information. Finally, experimental simulation and theoretical analysis show that our proposed algorithm can not only effectively resist plaintext (ciphertext attack, statistical attack, and information entropy attack but also effectively improve the efficiency of image encryption, which is a relatively secure and effective way of image communication.

A Multiresolution Image Completion Algorithm for Compressing Digital Color Images

Directory of Open Access Journals (Sweden)

R. Gomathi

2014-01-01

Full Text Available This paper introduces a new framework for image coding that uses image inpainting method. In the proposed algorithm, the input image is subjected to image analysis to remove some of the portions purposefully. At the same time, edges are extracted from the input image and they are passed to the decoder in the compressed manner. The edges which are transmitted to decoder act as assistant information and they help inpainting process fill the missing regions at the decoder. Textural synthesis and a new shearlet inpainting scheme based on the theory of p-Laplacian operator are proposed for image restoration at the decoder. Shearlets have been mathematically proven to represent distributed discontinuities such as edges better than traditional wavelets and are a suitable tool for edge characterization. This novel shearlet p-Laplacian inpainting model can effectively reduce the staircase effect in Total Variation (TV inpainting model whereas it can still keep edges as well as TV model. In the proposed scheme, neural network is employed to enhance the value of compression ratio for image coding. Test results are compared with JPEG 2000 and H.264 Intracoding algorithms. The results show that the proposed algorithm works well.

Dual-Energy Computed Tomography Angiography of the Lower Extremity Runoff: Impact of Noise-Optimized Virtual Monochromatic Imaging on Image Quality and Diagnostic Accuracy.

Science.gov (United States)

Wichmann, Julian L; Gillott, Matthew R; De Cecco, Carlo N; Mangold, Stefanie; Varga-Szemes, Akos; Yamada, Ricardo; Otani, Katharina; Canstein, Christian; Fuller, Stephen R; Vogl, Thomas J; Todoran, Thomas M; Schoepf, U Joseph

2016-02-01

The aim of this study was to evaluate the impact of a noise-optimized virtual monochromatic imaging algorithm (VMI+) on image quality and diagnostic accuracy at dual-energy computed tomography angiography (CTA) of the lower extremity runoff. This retrospective Health Insurance Portability and Accountability Act-compliant study was approved by the local institutional review board. We evaluated dual-energy CTA studies of the lower extremity runoff in 48 patients (16 women; mean age, 63.3 ± 13.8 years) performed on a third-generation dual-source CT system. Images were reconstructed with standard linear blending (F_0.5), VMI+, and traditional monochromatic (VMI) algorithms at 40 to 120 keV in 10-keV intervals. Vascular attenuation and image noise in 18 artery segments were measured; signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Five-point scales were used to subjectively evaluate vascular attenuation and image noise. In a subgroup of 21 patients who underwent additional invasive catheter angiography, diagnostic accuracy for the detection of significant stenosis (≥50% lumen restriction) of F_0.5, 50-keV VMI+, and 60-keV VMI data sets were assessed. Objective image quality metrics were highest in the 40- and 50-keV VMI+ series (SNR: 20.2 ± 10.7 and 19.0 ± 9.5, respectively; CNR: 18.5 ± 10.3 and 16.8 ± 9.1, respectively) and were significantly (all P traditional VMI technique and standard linear blending for evaluation of the lower extremity runoff using dual-energy CTA.

Radiogenomics: Creating a link between molecular diagnostics and diagnostic imaging

Energy Technology Data Exchange (ETDEWEB)

Rutman, Aaron M. [Department of Radiology, University of California San Diego Medical Center, San Diego, CA 92103 (United States); Kuo, Michael D. [Department of Radiology, University of California San Diego Medical Center, San Diego, CA 92103 (United States); Center for Translational Medical Systems, University of California San Diego Medical Center, San Diego, CA 92103 (United States)], E-mail: mkuo@ucsd.edu

2009-05-15

Studies employing high-throughput biological techniques have recently contributed to an improved characterization of human cancers, allowing for novel sub-classification, better diagnostic accuracy, and more precise prognostication. However, requirement of surgical procurement of tissue among other things limits the clinical application of such methods in everyday patient care. Radiographic imaging is routine in clinical practice but is currently histopathology based. The use of routine radiographic imaging provides a potential platform for linking specific imaging traits with specific gene expression patterns that inform the underlying cellular pathophysiology; imaging features could then serve as molecular surrogates that contribute to the diagnosis, prognosis, and likely gene-expression-associated treatment response of various forms of human cancer. This review focuses on high-throughput methods such as microarray analysis of gene expression, their role in cancer research, and in particular, on novel methods of associating gene expression patterns with radiographic imaging phenotypes, known as 'radiogenomics.' These findings underline a potential future role of both diagnostic and interventional radiologists in genetic assessment of cancer patients with radiographic imaging studies.

Radiogenomics: Creating a link between molecular diagnostics and diagnostic imaging

International Nuclear Information System (INIS)

Rutman, Aaron M.; Kuo, Michael D.

2009-01-01

Studies employing high-throughput biological techniques have recently contributed to an improved characterization of human cancers, allowing for novel sub-classification, better diagnostic accuracy, and more precise prognostication. However, requirement of surgical procurement of tissue among other things limits the clinical application of such methods in everyday patient care. Radiographic imaging is routine in clinical practice but is currently histopathology based. The use of routine radiographic imaging provides a potential platform for linking specific imaging traits with specific gene expression patterns that inform the underlying cellular pathophysiology; imaging features could then serve as molecular surrogates that contribute to the diagnosis, prognosis, and likely gene-expression-associated treatment response of various forms of human cancer. This review focuses on high-throughput methods such as microarray analysis of gene expression, their role in cancer research, and in particular, on novel methods of associating gene expression patterns with radiographic imaging phenotypes, known as 'radiogenomics.' These findings underline a potential future role of both diagnostic and interventional radiologists in genetic assessment of cancer patients with radiographic imaging studies.

Diagnostic imaging procedure volume in the United States

International Nuclear Information System (INIS)

Johnson, J.L.; Abernathy, D.L.

1983-01-01

Comprehensive data on 1979 and 1980 diagnostic imaging procedure volume were collected from a stratified random sample of U.S. short-term general-care hospitals and private practices of radiologists, cardiologists, obstetricians/gynecologists, orthopedic surgeons, and neurologists/neurosurgeons. Approximately 181 million imaging procedures (within the study scope) were performed in 1980. Despite the rapidly increasing use of newer imaging methods, plain film radiography (140.3 million procedures) and contrast studies (22.9 million procedures) continue to comprise the vast majority of diagnostic imaging volume. Ultrasound, computed tomography, nuclear medicine, and special procedures make up less than 10% of total diagnostic imaging procedures. Comparison of the data from this study with data from an earlier study indicates that imaging procedure volume in hospitals expanded at an annual growth rate of almost 8% from 1973 to 1980

Mathematical (diagnostic algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis

Directory of Open Access Journals (Sweden)

Abhishek Banerjee

2015-01-01

Full Text Available The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms include both object based (object features, structures and pixel based (texture measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.

Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

Science.gov (United States)

Hatipoglu, Nuh; Bilgin, Gokhan

2017-10-01

In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.

Encyclopedia of diagnostic imaging

International Nuclear Information System (INIS)

Baert, A.L.

2008-01-01

The simple A to Z format provides easy access to relevant information in the field of imaging. Extensive cross references between keywords and related articles enable efficient searches in a user-friendly manner. Fully searchable and hyperlinked electronic online edition. The aim of this comprehensive encyclopedia is to provide detailed information on diagnostic radiology contributing to the broad field of imaging. The wide range of entries are written by leading experts. They will provide basic and clinical scientists in academia, practice and industry with valuable information about the field of diagnostic imaging. Those in related fields, students, teachers, and interested laypeople will also benefit from the important and relevant information on the most recent developments. Please note that this publication is available as print only or online only or print + online set. Save 75% of the online list price when purchasing the bundle. For more information on the online version please type the publication title into the search box above, then click on the eReference version in the results list. (orig.)

The optimal algorithm for Multi-source RS image fusion.

Science.gov (United States)

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

2016-01-01

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

Diagnostic imaging of hypertrophic pyloric stenosis (HPS)

International Nuclear Information System (INIS)

Frkovic, M.; Seronja Kuhar, M.; Perhoc, Z.; Barbaric-Babic, V.; Molnar, M.; Vukovic, J.

2001-01-01

Background. Imaging of the abdomen in children with suspected hypertrophic pyloric stenosis has been traditionally performed by plain film radiography and upper gastrointestinal contrast studies. In many clinical situations, this approach has been modified or replaced by ultrasound examination. The authors aimed to analyse the value of diagnostic algorithm in children with hypertrophic pyloric stenosis confirmed at surgery in our hospital. Patients and methods. The authors made a five year retrospective review of hospital records of all children operated on for HPS in Clinical Hospital Centre Zagreb - Rebro and found out that 14 boys, between 2 (17 days) and 10 weeks of life (75 days) underwent surgery due to HPS. Results. Specific radiographic signs were: string sign, double track sign, elongation and narrowing of pyloric canal, mushroom sign, gastric distension with fluid and beak sign. Ultrasound was performed in 9 patients, one of them was false negative (sonographer admitted that he had no experience), the rest were positive. Conclusions. If the physical examination is negative or equivocal, sonography by an experienced sonographer must be performed. If the ultrasound finding is negative, than the infant should undergo to barium upper gastrointestinal studies (UGI). If HPS isn't a primary diagnostic question, it's better to perform UGI first in order to make a correct diagnosis. (author)

Is the S.O.S. diagnostic algorithm applicable to creating highly safe protective systems?

International Nuclear Information System (INIS)

Drab, F.

1994-01-01

The S.O.S. diagnostic system is analyzed and compared with KOMPARACE and MIN-MAX type diagnostic systems. Designed for the identification of failed sensors, the S.O.S. dynamic algorithm is based on a digital monitoring of output signals from a pair of sensors measuring the same technological parameter. The last 3 output signal data from the two sensors are stored in the algorithm memory. The analysis indicates that S.O.S. is no major achievement in the field of diagnosis because its properties are nearly identical with those of the conventional MIN-MAX system. Some degradation failures of the sensor are incorrectly interpreted by the new algorithm, some failures are not detected at all. From this point of view the new algorithm is inferior to the KOMPARACE type algorithm. (J.B.). 2 figs., 5 refs

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

The Noise Clinic: a Blind Image Denoising Algorithm

Directory of Open Access Journals (Sweden)

Marc Lebrun

2015-01-01

Full Text Available This paper describes the complete implementation of a blind image algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD noise model. In a second step, the image is denoised by a multiscale adaptation of the Non-local Bayes denoising method. We focus here on a careful analysis of the denoising step and present a detailed discussion of the influence of its parameters. Extensive commented tests of the blind denoising algorithm are presented, on real JPEG images and scans of old photographs.

Application of multislice spiral CT (MSCT) in multiple injured patients and its effect on diagnostic and therapeutic algorithms

International Nuclear Information System (INIS)

Boehm, T.; Alkadhi, H.; Schertler, T.; Baumert, B.; Roos, J.; Marincek, B.; Wildermuth, S.

2004-01-01

The initial diagnostic work-up of trauma victims with multiple injuries is currently a combination of conventional radiography (CR), ultrasound (US), and computed tomography (CT). This article reviews the diagnostic quality of the different imaging modalities regarding detection and classification of injuries. CT performs better than US in detecting traumatic lesions of abdominal parenchymal organs. Furthermore, CT is better than CR in detecting therapeutically relevant chest and bone injuries. MSCT may replace CR and US under the condition that it is faster than or at least as fast as the conventional approach to diagnose lite threatening injuries. This can be achieved only by changing the work-flow for the entire trauma team including radiologist. Furthermore, certain prerequisites must be fulfilled including integration of a MSCT scanner into the emergency room. An optimized whole body CT protocol for the assessment of trauma victims using MSCT as well as a two-step algorithm for reporting the imaging findings depending on their clinical significance is presented. (orig.)

Diagnostic algorithm for relapsing acquired demyelinating syndromes in children.

Science.gov (United States)

Hacohen, Yael; Mankad, Kshitij; Chong, W K; Barkhof, Frederik; Vincent, Angela; Lim, Ming; Wassmer, Evangeline; Ciccarelli, Olga; Hemingway, Cheryl

2017-07-18

To establish whether children with relapsing acquired demyelinating syndromes (RDS) and myelin oligodendrocyte glycoprotein antibodies (MOG-Ab) show distinctive clinical and radiologic features and to generate a diagnostic algorithm for the main RDS for clinical use. A panel reviewed the clinical characteristics, MOG-Ab and aquaporin-4 (AQP4) Ab, intrathecal oligoclonal bands, and Epstein-Barr virus serology results of 110 children with RDS. A neuroradiologist blinded to the diagnosis scored the MRI scans. Clinical, radiologic, and serologic tests results were compared. The findings showed that 56.4% of children were diagnosed with multiple sclerosis (MS), 25.4% with neuromyelitis optica spectrum disorder (NMOSD), 12.7% with multiphasic disseminated encephalomyelitis (MDEM), and 5.5% with relapsing optic neuritis (RON). Blinded analysis defined baseline MRI as typical of MS in 93.5% of children with MS. Acute disseminated encephalomyelitis presentation was seen only in the non-MS group. Of NMOSD cases, 30.7% were AQP4-Ab positive. MOG-Ab were found in 83.3% of AQP4-Ab-negative NMOSD, 100% of MDEM, and 33.3% of RON. Children with MOG-Ab were younger, were less likely to present with area postrema syndrome, and had lower disability, longer time to relapse, and more cerebellar peduncle lesions than children with AQP4-Ab NMOSD. A diagnostic algorithm applicable to any episode of CNS demyelination leads to 4 main phenotypes: MS, AQP4-Ab NMOSD, MOG-Ab-associated disease, and antibody-negative RDS. Children with MS and AQP4-Ab NMOSD showed features typical of adult cases. Because MOG-Ab-positive children showed notable and distinctive clinical and MRI features, they were grouped into a unified phenotype (MOG-Ab-associated disease), included in a new diagnostic algorithm. © 2017 American Academy of Neurology.

A Constrained Algorithm Based NMFα for Image Representation

Directory of Open Access Journals (Sweden)

Chenxue Yang

2014-01-01

Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.

A revolution in diagnostic imaging.

Science.gov (United States)

Mamula, Paul W

2003-03-01

In November 1966, Sandy Koufax, the star left-handed pitcher of the Los Angeles Dodgers, retired after spending his final season coping with traumatic arthritis in his elbow, the compounded effects of a sliding injury to his pitching arm the previous season and 12 years of hard throwing.1 Had his career begun a few years later, he might have been able to benefit from the advances in diagnostic imaging and treatment that were introduced at that time. Modern arthroscopy and computed tomography (CT) did not become available until the mid 1970s,2 and the first elbow reconstruction was done by Frank Jobe, MD, about 10 years after Koufax retired.1 Arthroscopy was first used as a diagnostic tool, but it later became a surgical tool, affecting treatment of knees, then, later, shoulders. Since 1973, when The Physician and Sportsmedicine was launched, we have witnessed a revolution in diagnostic imaging and are continuing to see an evolution of modalities.

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)

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.

Analysis of licensed South African diagnostic imaging equipment ...

African Journals Online (AJOL)

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

Inverse synthetic aperture radar imaging principles, algorithms and applications

CERN Document Server

Chen , Victor C

2014-01-01

Inverse Synthetic Aperture Radar Imaging: Principles, Algorithms and Applications is based on the latest research on ISAR imaging of moving targets and non-cooperative target recognition (NCTR). With a focus on the advances and applications, this book will provide readers with a working knowledge on various algorithms of ISAR imaging of targets and implementation with MATLAB. These MATLAB algorithms will prove useful in order to visualize and manipulate some simulated ISAR images.

Diagnostic imaging in medicine. 2. ed.

International Nuclear Information System (INIS)

Reba, R.C.; Goodenough, D.J.

1984-01-01

This book describes to practitioners the evolutionary progression of new non-invasive diagnostic imaging techniques. The utility of the procedures is also described in a series of state-of-the-art lectures given by outstanding international clinical investigators from NATO countries. Subjects of the papers include the following: advances in source and detector technology, acoustical imaging, NMR and microwave imaging, positron and single photon emission tomography, digital radiography and image processing and display techniques. Fundamental papers describing the theory of non-invasive procedures are included along with papers describing clinical examinations. Examples of utility and studies of diseases of the abdomen and pelvis, heart and lung, and central nervous system are included. Cost-effective and cost-benefit assessment of the new high technology procedures, as well as the use of diagnostic imaging techniques in developing countries are also presented. An index of leading topics completes the volume. (orig.)

An improved ASIFT algorithm for indoor panorama image matching

Science.gov (United States)

Fu, Han; Xie, Donghai; Zhong, Ruofei; Wu, Yu; Wu, Qiong

2017-07-01

The generation of 3D models for indoor objects and scenes is an attractive tool for digital city, virtual reality and SLAM purposes. Panoramic images are becoming increasingly more common in such applications due to their advantages to capture the complete environment in one single image with large field of view. The extraction and matching of image feature points are important and difficult steps in three-dimensional reconstruction, and ASIFT is a state-of-the-art algorithm to implement these functions. Compared with the SIFT algorithm, more feature points can be generated and the matching accuracy of ASIFT algorithm is higher, even for the panoramic images with obvious distortions. However, the algorithm is really time-consuming because of complex operations and performs not very well for some indoor scenes under poor light or without rich textures. To solve this problem, this paper proposes an improved ASIFT algorithm for indoor panoramic images: firstly, the panoramic images are projected into multiple normal perspective images. Secondly, the original ASIFT algorithm is simplified from the affine transformation of tilt and rotation with the images to the only tilt affine transformation. Finally, the results are re-projected to the panoramic image space. Experiments in different environments show that this method can not only ensure the precision of feature points extraction and matching, but also greatly reduce the computing time.

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

Science.gov (United States)

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

2018-01-01

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

Parallel image encryption algorithm based on discretized chaotic map

International Nuclear Information System (INIS)

Zhou Qing; Wong Kwokwo; Liao Xiaofeng; Xiang Tao; Hu Yue

2008-01-01

Recently, a variety of chaos-based algorithms were proposed for image encryption. Nevertheless, none of them works efficiently in parallel computing environment. In this paper, we propose a framework for parallel image encryption. Based on this framework, a new algorithm is designed using the discretized Kolmogorov flow map. It fulfills all the requirements for a parallel image encryption algorithm. Moreover, it is secure and fast. These properties make it a good choice for image encryption on parallel computing platforms

[Diagnostic imaging and acute abdominal pain].

Science.gov (United States)

Liljekvist, Mads Svane; Pommergaard, Hans-Christian; Burcharth, Jakob; Rosenberg, Jacob

2015-01-19

Acute abdominal pain is a common clinical condition. Clinical signs and symptoms can be difficult to interpret, and diagnostic imaging may help to identify intra-abdominal disease. Conventional X-ray, ultrasound (US) and computed tomography (CT) of the abdomen vary in usability between common surgical causes of acute abdominal pain. Overall, conventional X-ray cannot confidently diagnose or rule out disease. US and CT are equally trustworthy for most diseases. US with subsequent CT may enhance diagnostic precision. Magnetic resonance seems promising for future use in acute abdominal imaging.

Fast image matching algorithm based on projection characteristics

Science.gov (United States)

Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

2011-06-01

Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

Image segmentation algorithm based on T-junctions cues

Science.gov (United States)

Qian, Yanyu; Cao, Fengyun; Wang, Lu; Yang, Xuejie

2016-03-01

To improve the over-segmentation and over-merge phenomenon of single image segmentation algorithm,a novel approach of combing Graph-Based algorithm and T-junctions cues is proposed in this paper. First, a method by L0 gradient minimization is applied to the smoothing of the target image eliminate artifacts caused by noise and texture detail; Then, the initial over-segmentation result of the smoothing image using the graph-based algorithm; Finally, the final results via a region fusion strategy by t-junction cues. Experimental results on a variety of images verify the new approach's efficiency in eliminating artifacts caused by noise,segmentation accuracy and time complexity has been significantly improved.

A study of diagnostic imaging in pancreatic trauma

International Nuclear Information System (INIS)

Hirota, Masashi; Kanazumi, Naohito; Kato, Koichi; Eguchi, Takehiko; Kobayashi, Hironobu; Suzuki, Yuichi; Kimura, Jiro; Ishii, Masataka

2002-01-01

Pancreatic trauma treatment depends on pancreatic ductal injury. We examined the usefulness and problems of diagnostic imaging, such as enhanced CT, ERP, and CT after ERP, in pancreatic trauma. Subjects were 12 patients with pancreatic trauma treated in our hospital between April 1993 and March 2000. Enhanced CT was performed in 6 patients undergoing diagnostic imagings and ERP in 4 of the 6. Overall diagnostic accuracy of pancreatic ductal injury in enhanced CT was 16.7% and accuracy in ERP with CT after ERP was 100%. Intraoperative diagnosis of main pancreatic ductal injury was difficult in 1 of 2 patients in whom ERP failed. The importance of preoperative diagnostic imaging is thus clear. We expect that MRCP, recently evaluated in pancreatic disease diagnosis, will become a new pancreatic trauma modality. (author)

New hallmark of hepatocellular carcinoma, early hepatocellular carcinoma and high-grade dysplastic nodules on Gd-EOB-DTPA MRI in patients with cirrhosis: a new diagnostic algorithm.

Science.gov (United States)

Renzulli, Matteo; Biselli, Maurizio; Brocchi, Stefano; Granito, Alessandro; Vasuri, Francesco; Tovoli, Francesco; Sessagesimi, Elisa; Piscaglia, Fabio; D'Errico, Antonietta; Bolondi, Luigi; Golfieri, Rita

2018-02-03

Many improvements have been made in diagnosing hepatocellular carcinoma (HCC), but the radiological hallmarks of HCC have remained the same for many years. We prospectively evaluated the imaging criteria of HCC, early HCC and high-grade dysplastic nodules (HGDNs) in patients under surveillance for chronic liver disease, using gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) MRI and diffusion-weighted imaging. Our study population included 420 nodules >1 cm in 228 patients. The MRI findings of each nodule were collected in all sequences/phases. The diagnosis of HCC was made according to the American Association for the Study of Liver Diseases (AASLD) criteria; all atypical nodules were diagnosed using histology. A classification and regression tree was developed using three MRI findings which were independently significant correlated variables for early HCC/HCC, and the best sequence of their application in a new diagnostic algorithm (hepatobiliary hypointensity, arterial hyperintensity and diffusion restriction) was suggested. This algorithm demonstrated, both in the entire study population and for nodules ≤2 cm, higher sensitivity (96% [95% CI 93.5% to 97.6%] and 96.6% [95% CI 93.9% to 98.5%], P<0.001, respectively) and slightly lower specificity (91.8% [95% CI 88.6% to 94.1%], P=0.063, and 92.7% [95% CI 88.9% to 95.4%], P=0.125, respectively) than those of the AASLD criteria. Our new diagnostic algorithm also showed a very high sensitivity (94.7%; 95% CI 92% to 96.6%) and specificity (99.3%; 95% CI 97.7% to 99.8%) in classifying HGDN. Our new diagnostic algorithm demonstrated significantly higher sensitivity and comparable specificity than those of the AASLD imaging criteria for HCC in patients with cirrhosis evaluated using Gd-EOB-DTPA MRI, even for lesions ≤2 cm. Moreover, this diagnostic algorithm allowed evaluating other lesions which could arise in a cirrhotic liver, such as early HCC and HGDN. © Article author

Diagnostic reference levels in medical imaging

International Nuclear Information System (INIS)

Rosenstein, M.

2001-01-01

The paper proposes additional advice to national or local authorities and the clinical community on the application of diagnostic reference levels as a practical tool to manage radiation doses to patients in diagnostic radiology and nuclear medicine. A survey was made of the various approaches that have been taken by authoritative bodies to establish diagnostic reference levels for medical imaging tasks. There are a variety of ways to implement the idea of diagnostic reference levels, depending on the medical imaging task of interest, the national or local state of practice and the national or local preferences for technical implementation. The existing International Commission on Radiological Protection (ICRP) guidance is reviewed, the survey information is summarized, a set of unifying principles is espoused and a statement of additional advice that has been proposed to ICRP Committee 3 is presented. The proposed advice would meet a need for a unifying set of principles to provide a framework for diagnostic reference levels but would allow flexibility in their selection and use. While some illustrative examples are given, the proposed advice does not specify the specific quantities to be used, the numerical values to be set for the quantities or the technical details of how national or local authorities should implement diagnostic reference levels. (author)

Vertigo in childhood: proposal for a diagnostic algorithm based upon clinical experience.

Science.gov (United States)

Casani, A P; Dallan, I; Navari, E; Sellari Franceschini, S; Cerchiai, N

2015-06-01

The aim of this paper is to analyse, after clinical experience with a series of patients with established diagnoses and review of the literature, all relevant anamnestic features in order to build a simple diagnostic algorithm for vertigo in childhood. This study is a retrospective chart review. A series of 37 children underwent complete clinical and instrumental vestibular examination. Only neurological disorders or genetic diseases represented exclusion criteria. All diagnoses were reviewed after applying the most recent diagnostic guidelines. In our experience, the most common aetiology for dizziness is vestibular migraine (38%), followed by acute labyrinthitis/neuritis (16%) and somatoform vertigo (16%). Benign paroxysmal vertigo was diagnosed in 4 patients (11%) and paroxysmal torticollis was diagnosed in a 1-year-old child. In 8% (3 patients) of cases, the dizziness had a post-traumatic origin: 1 canalolithiasis of the posterior semicircular canal and 2 labyrinthine concussions, respectively. Menière's disease was diagnosed in 2 cases. A bilateral vestibular failure of unknown origin caused chronic dizziness in 1 patient. In conclusion, this algorithm could represent a good tool for guiding clinical suspicion to correct diagnostic assessment in dizzy children where no neurological findings are detectable. The algorithm has just a few simple steps, based mainly on two aspects to be investigated early: temporal features of vertigo and presence of hearing impairment. A different algorithm has been proposed for cases in which a traumatic origin is suspected.

Whole-body MR imaging versus sequential multimodal diagnostic algorithm for staging patients with rectal cancer. Cost analysis

International Nuclear Information System (INIS)

Huppertz, A.; Charite Universitaetsklinikum Berlin; Schmidt, M.; Schoeffski, O.; Wagner, M.; Asbach, P.; Maurer, M.H.; Puettcher, O.; Strassburg, J.; Stoeckmann, F.

2010-01-01

Purpose: To compare the direct costs of two diagnostic algorithms for pretherapeutic TNM staging of rectal cancer. Materials and Methods: In a study including 33 patients (mean age: 62.5 years), the direct fixed and variable costs of a sequential multimodal algorithm (rectoscopy, endoscopic and abdominal ultrasound, chest X-ray, thoracic/abdominal CT in the case of positive findings in abdominal ultrasound or chest X-ray) were compared to those of a novel algorithm of rectoscopy followed by MRI using a whole-body scanner. MRI included T 2w sequences of the rectum, 3D T 1w sequences of the liver and chest after bolus injection of gadoxetic acid, and delayed phases of the liver. The personnel work times, material items, and work processes were tracked to the nearest minute by interviewing those responsible for the process (surgeon, gastroenterologist, two radiologists). The costs of labor and materials were determined from personnel reimbursement data and hospital accounting records. Fixed costs were determined from vendor pricing. Results: The mean MRI time was 55 min. CT was performed in 19 / 33 patients (57 %) causing an additional day of hospitalization (costs 374 Euro). The costs for equipment and material were higher for MRI compared to sequential algorithm (equipment 116 vs. 30 Euro; material 159 vs. 60 Euro per patient). The personnel costs were markedly lower for MRI (436 vs. 732 Euro per patient). Altogether, the absolute cost advantage of MRI was 31.3 % (711 vs. 1035 Euro for sequential algorithm). Conclusion: Substantial savings are achievable with the use of whole-body MRI for the preoperative TNM staging of patients with rectal cancer. (orig.)

RANZAR Body Systems Framework of diagnostic imaging examination descriptors

International Nuclear Information System (INIS)

Pitman, Alexander D.; Penlington, Lisa; Doromal, Darren; Vukolova, Natalia; Slater, Gregory

2014-01-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were ‘greyed out’. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities.

RANZCR Body Systems Framework of diagnostic imaging examination descriptors.

Science.gov (United States)

Pitman, Alexander G; Penlington, Lisa; Doromal, Darren; Slater, Gregory; Vukolova, Natalia

2014-08-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were 'greyed out'. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities. © 2014 The Royal Australian and New Zealand College of Radiologists.

Hybrid wavefront sensing and image correction algorithm for imaging through turbulent media

Science.gov (United States)

Wu, Chensheng; Robertson Rzasa, John; Ko, Jonathan; Davis, Christopher C.

2017-09-01

It is well known that passive image correction of turbulence distortions often involves using geometry-dependent deconvolution algorithms. On the other hand, active imaging techniques using adaptive optic correction should use the distorted wavefront information for guidance. Our work shows that a hybrid hardware-software approach is possible to obtain accurate and highly detailed images through turbulent media. The processing algorithm also takes much fewer iteration steps in comparison with conventional image processing algorithms. In our proposed approach, a plenoptic sensor is used as a wavefront sensor to guide post-stage image correction on a high-definition zoomable camera. Conversely, we show that given the ground truth of the highly detailed image and the plenoptic imaging result, we can generate an accurate prediction of the blurred image on a traditional zoomable camera. Similarly, the ground truth combined with the blurred image from the zoomable camera would provide the wavefront conditions. In application, our hybrid approach can be used as an effective way to conduct object recognition in a turbulent environment where the target has been significantly distorted or is even unrecognizable.

Parallel asynchronous systems and image processing algorithms

Science.gov (United States)

Coon, D. D.; Perera, A. G. U.

1989-01-01

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

Algorithms for image processing and computer vision

CERN Document Server

Parker, J R

2010-01-01

A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It's an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists wh

Dose and diagnostic image quality in digital tomosynthesis imaging of facial bones in pediatrics

Science.gov (United States)

King, J. M.; Hickling, S.; Elbakri, I. A.; Reed, M.; Wrogemann, J.

2011-03-01

The purpose of this study was to evaluate the use of digital tomosynthesis (DT) for pediatric facial bone imaging. We compared the eye lens dose and diagnostic image quality of DT facial bone exams relative to digital radiography (DR) and computed tomography (CT), and investigated whether we could modify our current DT imaging protocol to reduce patient dose while maintaining sufficient diagnostic image quality. We measured the dose to the eye lens for all three modalities using high-sensitivity thermoluminescent dosimeters (TLDs) and an anthropomorphic skull phantom. To assess the diagnostic image quality of DT compared to the corresponding DR and CT images, we performed an observer study where the visibility of anatomical structures in the DT phantom images were rated on a four-point scale. We then acquired DT images at lower doses and had radiologists indicate whether the visibility of each structure was adequate for diagnostic purposes. For typical facial bone exams, we measured eye lens doses of 0.1-0.4 mGy for DR, 0.3-3.7 mGy for DT, and 26 mGy for CT. In general, facial bone structures were visualized better with DT then DR, and the majority of structures were visualized well enough to avoid the need for CT. DT imaging provides high quality diagnostic images of the facial bones while delivering significantly lower doses to the lens of the eye compared to CT. In addition, we found that by adjusting the imaging parameters, the DT effective dose can be reduced by up to 50% while maintaining sufficient image quality.

Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

Science.gov (United States)

Jiexian, Zeng; Xiupeng, Liu

2014-01-01

Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

Directory of Open Access Journals (Sweden)

V.G. Biju

2015-11-01

Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

Application of the EM algorithm to radiographic images.

Science.gov (United States)

Brailean, J C; Little, D; Giger, M L; Chen, C T; Sullivan, B J

1992-01-01

The expectation maximization (EM) algorithm has received considerable attention in the area of positron emitted tomography (PET) as a restoration and reconstruction technique. In this paper, the restoration capabilities of the EM algorithm when applied to radiographic images is investigated. This application does not involve reconstruction. The performance of the EM algorithm is quantitatively evaluated using a "perceived" signal-to-noise ratio (SNR) as the image quality metric. This perceived SNR is based on statistical decision theory and includes both the observer's visual response function and a noise component internal to the eye-brain system. For a variety of processing parameters, the relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to compare quantitatively the effects of the EM algorithm with two other image enhancement techniques: global contrast enhancement (windowing) and unsharp mask filtering. The results suggest that the EM algorithm's performance is superior when compared to unsharp mask filtering and global contrast enhancement for radiographic images which contain objects smaller than 4 mm.

High performance deformable image registration algorithms for manycore processors

CERN Document Server

Shackleford, James; Sharp, Gregory

2013-01-01

High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. E

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

Science.gov (United States)

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

2018-01-01

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

Digital imaging in diagnostic radiology. Image quality - radiation exposure

International Nuclear Information System (INIS)

Schmidt, T.; Stieve, F.E.

1996-01-01

The publication contains the 37 lectures of the symposium on digital imaging in diagnostic radiology, held in November 1995 at Kloster Seeon, as well as contributions enhancing the information presented in the lectures. The publication reflects the state of the art in this subject field, discusses future trends and gives recommendations and information relating to current practice in radiology. In-depth information is given about R and D activities for the digitalisation of X-ray pictures and the image quality required to meet the purposes of modern diagnostics. Further aspects encompass radiological protection and dose optimization as well as optimization of examination methods. (vhe) [de

Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software.

Science.gov (United States)

Moon, Andres; Smith, Geoffrey H; Kong, Jun; Rogers, Thomas E; Ellis, Carla L; Farris, Alton B Brad

2018-02-01

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm 2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling "maxima" criteria for CD3 expression (custom CD3+ cells/mm 2 ). Based on visual inspections of "markup" images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide "flow cytometry" that can facilitate additional diagnostic accuracy in tissue-based assessments.

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

Science.gov (United States)

Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad

2016-05-17

that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Diagnostic imaging of the hand

Energy Technology Data Exchange (ETDEWEB)

Schmitt, Rainer [Hospital for Cardiovascular Diseases, Bad Neustadt an der Saale (Germany). Dept. of Radiology; Lanz, Ulrich [Perlach Hospital, Munich (Germany). Dept. of Hand Surgery

2008-07-01

With its complex anatomy and specialized biomechanics, the human hand has always presented physicians with a unique challenge when it comes to diagnosing and treating the diseases that afflict it. And while recent decades have seen a rapid increase in the number of therapeutic options, many diseases and injuries of the hand are still commonly misinterpreted. In diagnostic imaging of the hand, an interdisciplinary team, comprisingspecialists in radiology, surgery, and rheumatology, presents a comprehensive,reliable guide to this topographically intricate area. Highlights include: - More than 1000 high-quality illustrations - All state-of-the-art imaging modalities-including multidetector CT, with 2D displays and 3D reconstructions, and contrast-enhanced MRI with multi-channel, phased-array coils - An overview of all currently used methods of examination - A detailed presentation of the anatomic and functional foundations necessary for diagnosis - Full coverage of all disorders of the hand - Systematic treatment of each disease's definition, pathogenesis, and clinical symptoms, according to a graduated diagnostic plan - Easy-to-use format, featuring crisp images and line drawings seamlessly integrated with concise text, summary tables, and handy checklists - A heavily cross-referenced appendix of differential diagnosis tables - Emphasis on interdisciplinary consultation throughout designed to help both radiologists and clinicians develop the most efficient and effective strategies for evaluating and treating patients, Diagnostic imaging of the hand will leave specialists of all levels with a fresh appreciation for - and a richer understanding of - the expanding array of cutting-edge alternatives for diagnosing and treating disorders of the hand. (orig.)

Diagnostic imaging of the hand

International Nuclear Information System (INIS)

Schmitt, Rainer; Lanz, Ulrich

2008-01-01

With its complex anatomy and specialized biomechanics, the human hand has always presented physicians with a unique challenge when it comes to diagnosing and treating the diseases that afflict it. And while recent decades have seen a rapid increase in the number of therapeutic options, many diseases and injuries of the hand are still commonly misinterpreted. In diagnostic imaging of the hand, an interdisciplinary team, comprisingspecialists in radiology, surgery, and rheumatology, presents a comprehensive,reliable guide to this topographically intricate area. Highlights include: - More than 1000 high-quality illustrations - All state-of-the-art imaging modalities-including multidetector CT, with 2D displays and 3D reconstructions, and contrast-enhanced MRI with multi-channel, phased-array coils - An overview of all currently used methods of examination - A detailed presentation of the anatomic and functional foundations necessary for diagnosis - Full coverage of all disorders of the hand - Systematic treatment of each disease's definition, pathogenesis, and clinical symptoms, according to a graduated diagnostic plan - Easy-to-use format, featuring crisp images and line drawings seamlessly integrated with concise text, summary tables, and handy checklists - A heavily cross-referenced appendix of differential diagnosis tables - Emphasis on interdisciplinary consultation throughout designed to help both radiologists and clinicians develop the most efficient and effective strategies for evaluating and treating patients, Diagnostic imaging of the hand will leave specialists of all levels with a fresh appreciation for - and a richer understanding of - the expanding array of cutting-edge alternatives for diagnosing and treating disorders of the hand. (orig.)

Meniscal tear. Diagnostic errors in MR imaging

International Nuclear Information System (INIS)

Barrera, M. C.; Recondo, J. A.; Gervas, C.; Fernandez, E.; Villanua, J. A.M.; Salvador, E.

2003-01-01

To analyze diagnostic discrepancies found between magnetic resonance (MR) and arthroscopy, and the determine the reasons that they occur. Two-hundred and forty-eight MR knee explorations were retrospectively checked. Forty of these showed diagnostic discrepancies between MR and arthroscopy. Two radiologists independently re-analyzed the images from 29 of the 40 studies without knowing which diagnosis had resulted from which of the two techniques. Their interpretations were correlated with the initial MR diagnosis, MR images and arthroscopic results. Initial errors in MR imaging were classified as either unavoidable, interpretive, or secondary to equivocal findings. Eleven MR examinations could not be checked since their corresponding imaging results could not be located. Of 34 errors found in the original diagnoses, 12 (35.5%)were classified as unavoidable, 14 (41.2%) as interpretative and 8 (23.5%) as secondary to equivocal findings. 41.2% of the errors were avoided in the retrospective study probably due to our department having greater experience in interpreting MR images, 25.5% were unavailable even in the retrospective study. A small percentage of diagnostic errors were due to the presence of subtle equivocal findings. (Author) 15 refs

An enhanced fractal image denoising algorithm

International Nuclear Information System (INIS)

Lu Jian; Ye Zhongxing; Zou Yuru; Ye Ruisong

2008-01-01

In recent years, there has been a significant development in image denoising using fractal-based method. This paper presents an enhanced fractal predictive denoising algorithm for denoising the images corrupted by an additive white Gaussian noise (AWGN) by using quadratic gray-level function. Meanwhile, a quantization method for the fractal gray-level coefficients of the quadratic function is proposed to strictly guarantee the contractivity requirement of the enhanced fractal coding, and in terms of the quality of the fractal representation measured by PSNR, the enhanced fractal image coding using quadratic gray-level function generally performs better than the standard fractal coding using linear gray-level function. Based on this enhanced fractal coding, the enhanced fractal image denoising is implemented by estimating the fractal gray-level coefficients of the quadratic function of the noiseless image from its noisy observation. Experimental results show that, compared with other standard fractal-based image denoising schemes using linear gray-level function, the enhanced fractal denoising algorithm can improve the quality of the restored image efficiently

The Role of Diagnostic Algorithms in the Management of Blunt Splenic Injury

Directory of Open Access Journals (Sweden)

Liang-Yu Chen

2005-08-01

Conclusion: Diagnostic algorithms using sonograms for screening provide an initial means of selecting patients for NOM. Patients with higher grades of splenic injury can then be managed non-operatively.

Target recognition of ladar range images using slice image: comparison of four improved algorithms

Science.gov (United States)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

[Diagnostic imaging of breast cancer : An update].

Science.gov (United States)

Funke, M

2016-10-01

Advances in imaging of the female breast have substantially influenced the diagnosis and probably also the therapy and prognosis of breast cancer in the past few years. This article gives an overview of the most important imaging modalities in the diagnosis of breast cancer. Digital mammography is considered to be the gold standard for the early detection of breast cancer. Digital breast tomosynthesis can increase the diagnostic accuracy of mammography and is used for the assessment of equivocal or suspicious mammography findings. Other modalities, such as ultrasound and contrast-enhanced magnetic resonance imaging (MRI) play an important role in the diagnostics, staging and follow-up of breast cancer. Percutaneous needle biopsy is a rapid and minimally invasive method for the histological verification of breast cancer. New breast imaging modalities, such as contrast-enhanced spectral mammography, diffusion-weighted MRI and MR spectroscopy can possibly further improve breast cancer diagnostics; however, further studies are necessary to prove the advantages of these methods so that they cannot yet be recommended for routine clinical use.

Diagnostic information management system for the evaluation of medical images

Energy Technology Data Exchange (ETDEWEB)

Higa, Toshiaki; Torizuka, Kanji; Minato, Kotaro; Komori, Masaru; Hirakawa, Akina

1985-04-01

A practical, small and low-cost diagnostic information management system has been developed for a comparative study of various medical imaging procedures, including ordinary radiography, X-ray computed tomography, emission computed tomography, and so forth. The purpose of the system is to effectively manage the original image data files and diagnostic descriptions during the various imaging procedures. A diagnostic description of each imaging procedure for each patient is made on a hand-sort punched-card with line-drawings and ordinary medical terminology and then coded and computerized using Index for Roentgen Diagnoses (American College of Radiology). A database management software (DB Master) on a personal computer (Apple II) is used for searching for patients' records on hand-sort punched-cards and finally original medical images. Discussed are realistic use of medical images and an effective form of diagnostic descriptions.

Diagnostic information management system for the evaluation of medical images

International Nuclear Information System (INIS)

Higa, Toshiaki; Torizuka, Kanji; Minato, Kotaro; Komori, Masaru; Hirakawa, Akina.

1985-01-01

A practical, small and low-cost diagnostic information management system has been developed for a comparative study of various medical imaging procedures, including ordinary radiography, X-ray computed tomography, emission computed tomography, and so forth. The purpose of the system is to effectively manage the original image data files and diagnostic descriptions during the various imaging procedures. A diagnostic description of each imaging procedure for each patient is made on a hand-sort punched-card with line-drawings and ordinary medical terminology and then coded and computerized using Index for Roentgen Diagnoses (American College of Radiology). A database management software (DB Master) on a personal computer (Apple II) is used for searching for patients' records on hand-sort punched-cards and finally original medical images. Discussed are realistic use of medical images and an effective form of diagnostic descriptions. (author)

WE-AB-206-01: Diagnostic Ultrasound Imaging Quality Assurance

Energy Technology Data Exchange (ETDEWEB)

Zagzebski, J. [University of Wisconsin (United States)

2016-06-15

The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. The goal of this ultrasound hands-on workshop is to demonstrate quality control (QC) testing in diagnostic ultrasound and to provide updates in ACR ultrasound accreditation requirements. The first half of this workshop will include two presentations reviewing diagnostic ultrasound QA/QC and ACR ultrasound accreditation requirements. The second half of the workshop will include live demonstrations of basic QC tests. An array of ultrasound testing phantoms and ultrasound scanners will be available for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations and on-site instructors. The targeted attendees are medical physicists in diagnostic imaging. Learning Objectives: Gain familiarity with common elements of a QA/QC program for diagnostic ultrasound imaging dentify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools Learn ACR ultrasound accreditation requirements Jennifer Walter is an employee of American College of Radiology on Ultrasound Accreditation.

WE-AB-206-01: Diagnostic Ultrasound Imaging Quality Assurance

International Nuclear Information System (INIS)

Zagzebski, J.

2016-01-01

The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. The goal of this ultrasound hands-on workshop is to demonstrate quality control (QC) testing in diagnostic ultrasound and to provide updates in ACR ultrasound accreditation requirements. The first half of this workshop will include two presentations reviewing diagnostic ultrasound QA/QC and ACR ultrasound accreditation requirements. The second half of the workshop will include live demonstrations of basic QC tests. An array of ultrasound testing phantoms and ultrasound scanners will be available for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations and on-site instructors. The targeted attendees are medical physicists in diagnostic imaging. Learning Objectives: Gain familiarity with common elements of a QA/QC program for diagnostic ultrasound imaging dentify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools Learn ACR ultrasound accreditation requirements Jennifer Walter is an employee of American College of Radiology on Ultrasound Accreditation.

Regularization iteration imaging algorithm for electrical capacitance tomography

Science.gov (United States)

Tong, Guowei; Liu, Shi; Chen, Hongyan; Wang, Xueyao

2018-03-01

The image reconstruction method plays a crucial role in real-world applications of the electrical capacitance tomography technique. In this study, a new cost function that simultaneously considers the sparsity and low-rank properties of the imaging targets is proposed to improve the quality of the reconstruction images, in which the image reconstruction task is converted into an optimization problem. Within the framework of the split Bregman algorithm, an iterative scheme that splits a complicated optimization problem into several simpler sub-tasks is developed to solve the proposed cost function efficiently, in which the fast-iterative shrinkage thresholding algorithm is introduced to accelerate the convergence. Numerical experiment results verify the effectiveness of the proposed algorithm in improving the reconstruction precision and robustness.

An efficient fractal image coding algorithm using unified feature and DCT

International Nuclear Information System (INIS)

Zhou Yiming; Zhang Chao; Zhang Zengke

2009-01-01

Fractal image compression is a promising technique to improve the efficiency of image storage and image transmission with high compression ratio, however, the huge time consumption for the fractal image coding is a great obstacle to the practical applications. In order to improve the fractal image coding, efficient fractal image coding algorithms using a special unified feature and a DCT coder are proposed in this paper. Firstly, based on a necessary condition to the best matching search rule during fractal image coding, the fast algorithm using a special unified feature (UFC) is addressed, and it can reduce the search space obviously and exclude most inappropriate matching subblocks before the best matching search. Secondly, on the basis of UFC algorithm, in order to improve the quality of the reconstructed image, a DCT coder is combined to construct a hybrid fractal image algorithm (DUFC). Experimental results show that the proposed algorithms can obtain good quality of the reconstructed images and need much less time than the baseline fractal coding algorithm.

HIV misdiagnosis in sub-Saharan Africa: performance of diagnostic algorithms at six testing sites

Science.gov (United States)

Kosack, Cara S.; Shanks, Leslie; Beelaert, Greet; Benson, Tumwesigye; Savane, Aboubacar; Ng’ang’a, Anne; Andre, Bita; Zahinda, Jean-Paul BN; Fransen, Katrien; Page, Anne-Laure

2017-01-01

Abstract Introduction: We evaluated the diagnostic accuracy of HIV testing algorithms at six programmes in five sub-Saharan African countries. Methods: In this prospective multisite diagnostic evaluation study (Conakry, Guinea; Kitgum, Uganda; Arua, Uganda; Homa Bay, Kenya; Doula, Cameroun and Baraka, Democratic Republic of Congo), samples from clients (greater than equal to five years of age) testing for HIV were collected and compared to a state-of-the-art algorithm from the AIDS reference laboratory at the Institute of Tropical Medicine, Belgium. The reference algorithm consisted of an enzyme-linked immuno-sorbent assay, a line-immunoassay, a single antigen-enzyme immunoassay and a DNA polymerase chain reaction test. Results: Between August 2011 and January 2015, over 14,000 clients were tested for HIV at 6 HIV counselling and testing sites. Of those, 2786 (median age: 30; 38.1% males) were included in the study. Sensitivity of the testing algorithms ranged from 89.5% in Arua to 100% in Douala and Conakry, while specificity ranged from 98.3% in Doula to 100% in Conakry. Overall, 24 (0.9%) clients, and as many as 8 per site (1.7%), were misdiagnosed, with 16 false-positive and 8 false-negative results. Six false-negative specimens were retested with the on-site algorithm on the same sample and were found to be positive. Conversely, 13 false-positive specimens were retested: 8 remained false-positive with the on-site algorithm. Conclusions: The performance of algorithms at several sites failed to meet expectations and thresholds set by the World Health Organization, with unacceptably high rates of false results. Alongside the careful selection of rapid diagnostic tests and the validation of algorithms, strictly observing correct procedures can reduce the risk of false results. In the meantime, to identify false-positive diagnoses at initial testing, patients should be retested upon initiating antiretroviral therapy. PMID:28691437

Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

Science.gov (United States)

Elahi, Sana; kaleem, Muhammad; Omer, Hammad

2018-01-01

Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

Trends in utilization: has extremity MR imaging replaced diagnostic arthroscopy?

International Nuclear Information System (INIS)

Glynn, Nicole; Morrison, William B.; Parker, Laurence; Schweitzer, Mark E.; Carrino, John A.

2004-01-01

To examine the relative change in utilization of magnetic resonance (MR) imaging of the extremities versus diagnostic and therapeutic arthroscopy. Using the 1993, 1996, and 1999 nationwide Medicare Part B databases, utilization rates (per 100,000) were determined for upper and lower extremity MR imaging, diagnostic arthroscopy and therapeutic arthroscopy using CPT-4 codes. Utilization of extremity MR imaging was compared with that of diagnostic and therapeutic arthroscopy in 10 geographic regions of the United States and tracked over time. Combined lower and upper extremity MR imaging utilization per 100,000 increased from 393 to 1,056 in 1999 (+168.7%). Utilization of diagnostic arthroscopy of the extremities decreased from 18 in 1993 to 8 in 1999 (-55.6%); therapeutic arthroscopy rates increased from 461 in 1993 to 636 in 1999 (+40.0%). Specifically, from 1993 to 1999, utilization of lower extremity MR imaging increased from 270 to 661 (+144.8%). Utilization of diagnostic arthroscopy of the knee over the same time period decreased from 11 to 5 (-54.5%); therapeutic arthroscopy increased from 394 to 501 (+27.2%). Similarly, utilization rates for upper extremity MR imaging increased from 123 to 395 (+221.1%). Utilization of diagnostic arthroscopy of the shoulder over the same time period decreased from 7 to 2 (-71.4%); therapeutic arthroscopy increased from 44 to 104 (+136.4%). No specific geographic trends were ascertained. The utilization of MR imaging of the extremities has markedly increased from 1993 to 1999. During the same time period the utilization of diagnostic arthroscopy has decreased and that of therapeutic arthroscopy has increased. These findings support the hypothesis that there is increased reliance of clinical practitioners on the diagnostic information provided by MR imaging in preoperative clinical decision-making. (orig.)

Autonomous algorithms for image restoration

OpenAIRE

Griniasty , Meir

1994-01-01

We describe a general theoretical framework for algorithms that adaptively tune all their parameters during the restoration of a noisy image. The adaptation procedure is based on a mean field approach which is known as ``Deterministic Annealing'', and is reminiscent of the ``Deterministic Bolzmann Machiné'. The algorithm is less time consuming in comparison with its simulated annealing alternative. We apply the theory to several architectures and compare their performances.

Comparison of analyzer-based imaging computed tomography extraction algorithms and application to bone-cartilage imaging

International Nuclear Information System (INIS)

Diemoz, Paul C; Bravin, Alberto; Coan, Paola; Glaser, Christian

2010-01-01

In x-ray phase-contrast analyzer-based imaging, the contrast is provided by a combination of absorption, refraction and scattering effects. Several extraction algorithms, which attempt to separate and quantify these different physical contributions, have been proposed and applied. In a previous work, we presented a quantitative comparison of five among the most well-known extraction algorithms based on the geometrical optics approximation applied to planar images: diffraction-enhanced imaging (DEI), extended diffraction-enhanced imaging (E-DEI), generalized diffraction-enhanced imaging (G-DEI), multiple-image radiography (MIR) and Gaussian curve fitting (GCF). In this paper, we compare these algorithms in the case of the computed tomography (CT) modality. The extraction algorithms are applied to analyzer-based CT images of both plastic phantoms and biological samples (cartilage-on-bone cylinders). Absorption, refraction and scattering signals are derived. Results obtained with the different algorithms may vary greatly, especially in the case of large refraction angles. We show that ABI-CT extraction algorithms can provide an excellent tool to enhance the visualization of cartilage internal structures, which may find applications in a clinical context. Besides, by using the refraction images, the refractive index decrements for both the cartilage matrix and the cartilage cells have been estimated.

Low-Complexity Regularization Algorithms for Image Deblurring

KAUST Repository

Alanazi, Abdulrahman

2016-11-01

Image restoration problems deal with images in which information has been degraded by blur or noise. In practice, the blur is usually caused by atmospheric turbulence, motion, camera shake, and several other mechanical or physical processes. In this study, we present two regularization algorithms for the image deblurring problem. We first present a new method based on solving a regularized least-squares (RLS) problem. This method is proposed to find a near-optimal value of the regularization parameter in the RLS problems. Experimental results on the non-blind image deblurring problem are presented. In all experiments, comparisons are made with three benchmark methods. The results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and structural similarity, as well as the visual quality of the deblurred images. To reduce the complexity of the proposed algorithm, we propose a technique based on the bootstrap method to estimate the regularization parameter in low and high-resolution images. Numerical results show that the proposed technique can effectively reduce the computational complexity of the proposed algorithms. In addition, for some cases where the point spread function (PSF) is separable, we propose using a Kronecker product so as to reduce the computations. Furthermore, in the case where the image is smooth, it is always desirable to replace the regularization term in the RLS problems by a total variation term. Therefore, we propose a novel method for adaptively selecting the regularization parameter in a so-called square root regularized total variation (SRTV). Experimental results demonstrate that our proposed method outperforms the other benchmark methods when applied to smooth images in terms of PSNR, SSIM and the restored image quality. In this thesis, we focus on the non-blind image deblurring problem, where the blur kernel is assumed to be known. However, we developed algorithms that also work

A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.

Science.gov (United States)

Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng

2017-09-08

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.

Child abuse. Diagnostic imaging of skeletal injuries

International Nuclear Information System (INIS)

Stenzel, Martin; Mentzel, Hans-Joachim

2012-01-01

Diagnostic imaging, besides medical history and clinical examination, is a major component in assessment of cases of suspected physical child abuse. Performance of proper imaging technique, and knowledge of specific injury patterns is required for accurate image interpretation by the radiologist, and serves protection of the child in case of proven abuse. On the other side, it is essential to protect the family in unjustified accusations. The reader will be familiarised with essentials of the topic 'Physical child abuse', in order to be able to correctly assess quality, completeness, and results of X-ray films. Moreover, opportunities and limitations of alternative diagnostic modalities will be discussed. (orig.)

LSB Based Quantum Image Steganography Algorithm

Science.gov (United States)

Jiang, Nan; Zhao, Na; Wang, Luo

2016-01-01

Quantum steganography is the technique which hides a secret message into quantum covers such as quantum images. In this paper, two blind LSB steganography algorithms in the form of quantum circuits are proposed based on the novel enhanced quantum representation (NEQR) for quantum images. One algorithm is plain LSB which uses the message bits to substitute for the pixels' LSB directly. The other is block LSB which embeds a message bit into a number of pixels that belong to one image block. The extracting circuits can regain the secret message only according to the stego cover. Analysis and simulation-based experimental results demonstrate that the invisibility is good, and the balance between the capacity and the robustness can be adjusted according to the needs of applications.

Thinning an object boundary on digital image using pipelined algorithm

International Nuclear Information System (INIS)

Dewanto, S.; Aliyanta, B.

1997-01-01

In digital image processing, the thinning process to an object boundary is required to analyze the image structure with a measurement of parameter such as area, circumference of the image object. The process needs a sufficient large memory and time consuming if all the image pixels stored in the memory and the following process is done after all the pixels has ben transformed. pipelined algorithm can reduce the time used in the process. This algorithm uses buffer memory where its size can be adjusted. the next thinning process doesn't need to wait all the transformation of pixels. This paper described pipelined algorithm with some result on the use of the algorithm to digital image

Evaluation of Underwater Image Enhancement Algorithms under Different Environmental Conditions

Directory of Open Access Journals (Sweden)

Marino Mangeruga

2018-01-01

Full Text Available Underwater images usually suffer from poor visibility, lack of contrast and colour casting, mainly due to light absorption and scattering. In literature, there are many algorithms aimed to enhance the quality of underwater images through different approaches. Our purpose was to identify an algorithm that performs well in different environmental conditions. We have selected some algorithms from the state of the art and we have employed them to enhance a dataset of images produced in various underwater sites, representing different environmental and illumination conditions. These enhanced images have been evaluated through some quantitative metrics. By analysing the results of these metrics, we tried to understand which of the selected algorithms performed better than the others. Another purpose of our research was to establish if a quantitative metric was enough to judge the behaviour of an underwater image enhancement algorithm. We aim to demonstrate that, even if the metrics can provide an indicative estimation of image quality, they could lead to inconsistent or erroneous evaluations.

Companion diagnostics and molecular imaging-enhanced approaches for oncology clinical trials.

Science.gov (United States)

Van Heertum, Ronald L; Scarimbolo, Robert; Ford, Robert; Berdougo, Eli; O'Neal, Michael

2015-01-01

In the era of personalized medicine, diagnostic approaches are helping pharmaceutical and biotechnology sponsors streamline the clinical trial process. Molecular assays and diagnostic imaging are routinely being used to stratify patients for treatment, monitor disease, and provide reliable early clinical phase assessments. The importance of diagnostic approaches in drug development is highlighted by the rapidly expanding global cancer diagnostics market and the emergent attention of regulatory agencies worldwide, who are beginning to offer more structured platforms and guidance for this area. In this paper, we highlight the key benefits of using companion diagnostics and diagnostic imaging with a focus on oncology clinical trials. Nuclear imaging using widely available radiopharmaceuticals in conjunction with molecular imaging of oncology targets has opened the door to more accurate disease assessment and the modernization of standard criteria for the evaluation, staging, and treatment responses of cancer patients. Furthermore, the introduction and validation of quantitative molecular imaging continues to drive and optimize the field of oncology diagnostics. Given their pivotal role in disease assessment and treatment, the validation and commercialization of diagnostic tools will continue to advance oncology clinical trials, support new oncology drugs, and promote better patient outcomes.

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

Science.gov (United States)

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

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.

Optimization of image processing algorithms on mobile platforms

Science.gov (United States)

Poudel, Pramod; Shirvaikar, Mukul

2011-03-01

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

Diagnostic imaging in medicine. 2nd ed

Energy Technology Data Exchange (ETDEWEB)

Reba, R C; Goodenough, D J; Davidson, H F

1984-01-01

This book describes to practitioners the evolutionary progression of new non-invasive diagnostic imaging techniques. The utility of the procedures is also described in a series of state-of-the-art lectures given by outstanding international clinical investigators from NATO countries. Subjects of the papers include the following: advances in source and detector technology, acoustical imaging, NMR and microwave imaging, positron and single photon emission tomography, digital radiography and image processing and display techniques. Fundamental papers describing the theory of non-invasive procedures are included along with papers describing clinical examinations. Examples of utility and studies of diseases of the abdomen and pelvis, heart and lung, and central nervous system are included. Cost-effective and cost-benefit assessment of the new high technology procedures, as well as the use of diagnostic imaging techniques in developing countries are also presented. An index of leading topics completes the volume.

Diagnostic imaging in internal medicine

International Nuclear Information System (INIS)

Eisenberg, R.L.

1985-01-01

This book examines medical diagnostic techniques. Topics considered include biological considerations in the approach to clinical medicines; infectious diseases; disorders of the heart; disorders of the vascular system; disorders of the respiratory system; diseases of the kidneys and urinary tract; disorders of the alimentary tract; disorders of the hepatobiliary system and pancreas; disorders of the hematopoietic system; disorders of bone and bone mineralization; disorders of the joints, connective tissues, and striated muscles; disorders of the nervous system; miscellaneous disorders; and procedures in diagnostic imaging

Diagnostic image quality of video-digitized chest images

International Nuclear Information System (INIS)

Winter, L.H.; Butler, R.B.; Becking, W.B.; Warnars, G.A.O.; Haar Romeny, B. ter; Ottes, F.P.; Valk, J.-P.J. de

1989-01-01

The diagnostic accuracy obtained with the Philips picture archiving and communications subsystem was investigated by means of an observer performance study using receiver operating characteristic (ROC) analysis. The image qualities of conventional films and video digitized images were compared. The scanner had a 1024 x 1024 x 8 bit memory. The digitized images were displayed on a 60 Hz interlaced display monitor 1024 lines. Posteroanterior (AP) roetgenograms of a chest phantom with superimposed simulated interstitial pattern disease (IPD) were produced; there were 28 normal and 40 abnormal films. Normal films were produced by the chest phantom alone. Abnormal films were taken of the chest phantom with varying degrees of superimposed simulated intersitial disease (PND) for an observer performance study, because the results of a simulated interstitial pattern disease study are less likely to be influenced by perceptual capabilities. The conventional films and the video digitized images were viewed by five experienced observers during four separate sessions. Conventional films were presented on a viewing box, the digital images were displayed on the monitor described above. The presence of simulated intersitial disease was indicated on a 5-point ROC certainty scale by each observer. We analyzed the differences between ROC curves derived from correlated data statistically. The mean time required to evaluate 68 digitized images is approximately four times the mean time needed to read the convential films. The diagnostic quality of the video digitized images was significantly lower (at the 5% level) than that of the conventional films (median area under the curve (AUC) of 0.71 and 0.94, respectively). (author). 25 refs.; 2 figs.; 4 tabs

Algorithms for diagnostics of the measuring channels and technological equipment at NPP with WWER-1000

International Nuclear Information System (INIS)

Vysotskij, V.G.

1997-01-01

An algorithm for diagnostics of the state of measuring channels of an information computer system with usage of analysis of statistical channel characteristics is presented. An algorithm for testing the generalized state of the NPP technological equipment is proposed

Analysis and improvement of a chaos-based image encryption algorithm

International Nuclear Information System (INIS)

Xiao Di; Liao Xiaofeng; Wei Pengcheng

2009-01-01

The security of digital image attracts much attention recently. In Guan et al. [Guan Z, Huang F, Guan W. Chaos-based image encryption algorithm. Phys Lett A 2005; 346: 153-7.], a chaos-based image encryption algorithm has been proposed. In this paper, the cause of potential flaws in the original algorithm is analyzed in detail, and then the corresponding enhancement measures are proposed. Both theoretical analysis and computer simulation indicate that the improved algorithm can overcome these flaws and maintain all the merits of the original one.

Multilevel Image Segmentation Based on an Improved Firefly Algorithm

Directory of Open Access Journals (Sweden)

Kai Chen

2016-01-01

Full Text Available Multilevel image segmentation is time-consuming and involves large computation. The firefly algorithm has been applied to enhancing the efficiency of multilevel image segmentation. However, in some cases, firefly algorithm is easily trapped into local optima. In this paper, an improved firefly algorithm (IFA is proposed to search multilevel thresholds. In IFA, in order to help fireflies escape from local optima and accelerate the convergence, two strategies (i.e., diversity enhancing strategy with Cauchy mutation and neighborhood strategy are proposed and adaptively chosen according to different stagnation stations. The proposed IFA is compared with three benchmark optimal algorithms, that is, Darwinian particle swarm optimization, hybrid differential evolution optimization, and firefly algorithm. The experimental results show that the proposed method can efficiently segment multilevel images and obtain better performance than the other three methods.

Secure image encryption algorithm design using a novel chaos based S-Box

International Nuclear Information System (INIS)

Çavuşoğlu, Ünal; Kaçar, Sezgin; Pehlivan, Ihsan; Zengin, Ahmet

2017-01-01

Highlights: • A new chaotic system is developed for creating S-Box and image encryption algorithm. • Chaos based random number generator is designed with the help of the new chaotic system. NIST tests are run on generated random numbers to verify randomness. • A new S-Box design algorithm is developed to create the chaos based S-Box to be utilized in encryption algorithm and performance tests are made. • The new developed S-Box based image encryption algorithm is introduced and image encryption application is carried out. • To show the quality and strong of the encryption process, security analysis are performed and compared with the AES and chaos algorithms. - Abstract: In this study, an encryption algorithm that uses chaos based S-BOX is developed for secure and speed image encryption. First of all, a new chaotic system is developed for creating S-Box and image encryption algorithm. Chaos based random number generator is designed with the help of the new chaotic system. Then, NIST tests are run on generated random numbers to verify randomness. A new S-Box design algorithm is developed to create the chaos based S-Box to be utilized in encryption algorithm and performance tests are made. As the next step, the new developed S-Box based image encryption algorithm is introduced in detail. Finally, image encryption application is carried out. To show the quality and strong of the encryption process, security analysis are performed. Proposed algorithm is compared with the AES and chaos algorithms. According to tests results, the proposed image encryption algorithm is secure and speed for image encryption application.

Brain-inspired algorithms for retinal image analysis

NARCIS (Netherlands)

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

2016-01-01

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

Development of real time diagnostics and feedback algorithms for JET in view of the next step

Energy Technology Data Exchange (ETDEWEB)

Murari, A.; Barana, O. [Consorzio RFX Associazione EURATOM ENEA per la Fusione, Corso Stati Uniti 4, Padua (Italy); Felton, R.; Zabeo, L.; Piccolo, F.; Sartori, F. [Euratom/UKAEA Fusion Assoc., Culham Science Centre, Abingdon, Oxon (United Kingdom); Joffrin, E.; Mazon, D.; Laborde, L.; Moreau, D. [Association EURATOM-CEA, CEA Cadarache, 13 - Saint-Paul-lez-Durance (France); Albanese, R. [Assoc. Euratom-ENEA-CREATE, Univ. Mediterranea RC (Italy); Arena, P.; Bruno, M. [Assoc. Euratom-ENEA-CREATE, Univ.di Catania (Italy); Ambrosino, G.; Ariola, M. [Assoc. Euratom-ENEA-CREATE, Univ. Napoli Federico Napoli (Italy); Crisanti, F. [Associazone EURATOM ENEA sulla Fusione, C.R. Frascati (Italy); Luna, E. de la; Sanchez, J. [Associacion EURATOM CIEMAT para Fusion, Madrid (Spain)

2004-07-01

Real time control of many plasma parameters will be an essential aspect in the development of reliable high performance operation of Next Step Tokamaks. The main prerequisites for any feedback scheme are the precise real-time determination of the quantities to be controlled, requiring top quality and highly reliable diagnostics, and the availability of robust control algorithms. A new set of real time diagnostics was recently implemented on JET to prove the feasibility of determining, with high accuracy and time resolution, the most important plasma quantities. With regard to feedback algorithms, new model-based controllers were developed to allow a more robust control of several plasma parameters. Both diagnostics and algorithms were successfully used in several experiments, ranging from H-mode plasmas to configuration with ITBs (internal thermal barriers). Since elaboration of computationally heavy measurements is often required, significant attention was devoted to non-algorithmic methods like Digital or Cellular Neural/Nonlinear Networks. The real time hardware and software adopted architectures are also described with particular attention to their relevance to ITER. (authors)

Development of real time diagnostics and feedback algorithms for JET in view of the next step

International Nuclear Information System (INIS)

Murari, A.; Felton, R.; Zabeo, L.; Piccolo, F.; Sartori, F.; Murari, A.; Barana, O.; Albanese, R.; Joffrin, E.; Mazon, D.; Laborde, L.; Moreau, D.; Arena, P.; Bruno, M.; Ambrosino, G.; Ariola, M.; Crisanti, F.; Luna, E. de la; Sanchez, J.

2004-01-01

Real time control of many plasma parameters will be an essential aspect in the development of reliable high performance operation of Next Step Tokamaks. The main prerequisites for any feedback scheme are the precise real-time determination of the quantities to be controlled, requiring top quality and highly reliable diagnostics, and the availability of robust control algorithms. A new set of real time diagnostics was recently implemented on JET to prove the feasibility of determining, with high accuracy and time resolution, the most important plasma quantities. With regard to feedback algorithms, new model-based controllers were developed to allow a more robust control of several plasma parameters. Both diagnostics and algorithms were successfully used in several experiments, ranging from H-mode plasmas to configuration with internal transport barriers. Since elaboration of computationally heavy measurements is often required, significant attention was devoted to non-algorithmic methods like Digital or Cellular Neural/Nonlinear Networks. The real time hardware and software adopted architectures are also described with particular attention to their relevance to ITER. (authors)

Development of real time diagnostics and feedback algorithms for JET in view of the next step

International Nuclear Information System (INIS)

Murari, A.; Barana, O.; Murari, A.; Felton, R.; Zabeo, L.; Piccolo, F.; Sartori, F.; Joffrin, E.; Mazon, D.; Laborde, L.; Moreau, D.; Albanese, R.; Arena, P.; Bruno, M.; Ambrosino, G.; Ariola, M.; Crisanti, F.; Luna, E. de la; Sanchez, J.

2004-01-01

Real time control of many plasma parameters will be an essential aspect in the development of reliable high performance operation of Next Step Tokamaks. The main prerequisites for any feedback scheme are the precise real-time determination of the quantities to be controlled, requiring top quality and highly reliable diagnostics, and the availability of robust control algorithms. A new set of real time diagnostics was recently implemented on JET to prove the feasibility of determining, with high accuracy and time resolution, the most important plasma quantities. With regard to feedback algorithms, new model-based controllers were developed to allow a more robust control of several plasma parameters. Both diagnostics and algorithms were successfully used in several experiments, ranging from H-mode plasmas to configuration with ITBs (internal thermal barriers). Since elaboration of computationally heavy measurements is often required, significant attention was devoted to non-algorithmic methods like Digital or Cellular Neural/Nonlinear Networks. The real time hardware and software adopted architectures are also described with particular attention to their relevance to ITER. (authors)

A Superresolution Image Reconstruction Algorithm Based on Landweber in Electrical Capacitance Tomography

Directory of Open Access Journals (Sweden)

Chen Deyun

2013-01-01

Full Text Available According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm.

A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation.

Science.gov (United States)

Pelet, S; Previte, M J R; Laiho, L H; So, P T C

2004-10-01

Global fitting algorithms have been shown to improve effectively the accuracy and precision of the analysis of fluorescence lifetime imaging microscopy data. Global analysis performs better than unconstrained data fitting when prior information exists, such as the spatial invariance of the lifetimes of individual fluorescent species. The highly coupled nature of global analysis often results in a significantly slower convergence of the data fitting algorithm as compared with unconstrained analysis. Convergence speed can be greatly accelerated by providing appropriate initial guesses. Realizing that the image morphology often correlates with fluorophore distribution, a global fitting algorithm has been developed to assign initial guesses throughout an image based on a segmentation analysis. This algorithm was tested on both simulated data sets and time-domain lifetime measurements. We have successfully measured fluorophore distribution in fibroblasts stained with Hoechst and calcein. This method further allows second harmonic generation from collagen and elastin autofluorescence to be differentiated in fluorescence lifetime imaging microscopy images of ex vivo human skin. On our experimental measurement, this algorithm increased convergence speed by over two orders of magnitude and achieved significantly better fits. Copyright 2004 Biophysical Society

A chaos-based image encryption algorithm with variable control parameters

International Nuclear Information System (INIS)

Wang Yong; Wong, K.-W.; Liao Xiaofeng; Xiang Tao; Chen Guanrong

2009-01-01

In recent years, a number of image encryption algorithms based on the permutation-diffusion structure have been proposed. However, the control parameters used in the permutation stage are usually fixed in the whole encryption process, which favors attacks. In this paper, a chaos-based image encryption algorithm with variable control parameters is proposed. The control parameters used in the permutation stage and the keystream employed in the diffusion stage are generated from two chaotic maps related to the plain-image. As a result, the algorithm can effectively resist all known attacks against permutation-diffusion architectures. Theoretical analyses and computer simulations both confirm that the new algorithm possesses high security and fast encryption speed for practical image encryption.

A hash-based image encryption algorithm

Science.gov (United States)

Cheddad, Abbas; Condell, Joan; Curran, Kevin; McKevitt, Paul

2010-03-01

There exist several algorithms that deal with text encryption. However, there has been little research carried out to date on encrypting digital images or video files. This paper describes a novel way of encrypting digital images with password protection using 1D SHA-2 algorithm coupled with a compound forward transform. A spatial mask is generated from the frequency domain by taking advantage of the conjugate symmetry of the complex imagery part of the Fourier Transform. This mask is then XORed with the bit stream of the original image. Exclusive OR (XOR), a logical symmetric operation, that yields 0 if both binary pixels are zeros or if both are ones and 1 otherwise. This can be verified simply by modulus (pixel1, pixel2, 2). Finally, confusion is applied based on the displacement of the cipher's pixels in accordance with a reference mask. Both security and performance aspects of the proposed method are analyzed, which prove that the method is efficient and secure from a cryptographic point of view. One of the merits of such an algorithm is to force a continuous tone payload, a steganographic term, to map onto a balanced bits distribution sequence. This bit balance is needed in certain applications, such as steganography and watermarking, since it is likely to have a balanced perceptibility effect on the cover image when embedding.

An Example-Based Super-Resolution Algorithm for Selfie Images

Directory of Open Access Journals (Sweden)

Jino Hans William

2016-01-01

Full Text Available A selfie is typically a self-portrait captured using the front camera of a smartphone. Most state-of-the-art smartphones are equipped with a high-resolution (HR rear camera and a low-resolution (LR front camera. As selfies are captured by front camera with limited pixel resolution, the fine details in it are explicitly missed. This paper aims to improve the resolution of selfies by exploiting the fine details in HR images captured by rear camera using an example-based super-resolution (SR algorithm. HR images captured by rear camera carry significant fine details and are used as an exemplar to train an optimal matrix-value regression (MVR operator. The MVR operator serves as an image-pair priori which learns the correspondence between the LR-HR patch-pairs and is effectively used to super-resolve LR selfie images. The proposed MVR algorithm avoids vectorization of image patch-pairs and preserves image-level information during both learning and recovering process. The proposed algorithm is evaluated for its efficiency and effectiveness both qualitatively and quantitatively with other state-of-the-art SR algorithms. The results validate that the proposed algorithm is efficient as it requires less than 3 seconds to super-resolve LR selfie and is effective as it preserves sharp details without introducing any counterfeit fine details.

Diagnostic imaging of craniopharyngioma

International Nuclear Information System (INIS)

Gradzki, J.; Nowak, S.; Paprzycki, W.

1993-01-01

40 patients have been examined with operational and histological confirmation of craniopharyngioma. CT image and X-ray plane of skull were performed in case all of these patients. TMR was conformed to examine 4 patients. X-ray planes was compared to CT. CT permits tumor cyst detection. The efficacy of mentioned above diagnostic techniques was compared with surgical findings. (author)

Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

Science.gov (United States)

McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

2006-03-01

spatial resolution bar patterns demonstrated that the BONE (GE) and B46f (Siemens) showed higher spatial resolution compared to the STANDARD (GE) or B30f (Siemens) reconstruction algorithms typically used for routine body CT imaging. Only the sharper images were deemed clinically acceptable for the evaluation of diffuse lung disease (e.g. emphysema). Quantitative analyses of the extent of emphysema in patient data showed the percent volumes above the -950 HU threshold as 9.4% for the BONE reconstruction, 5.9% for the STANDARD reconstruction, and 4.7% for the BONE filtered images. Contrary to the practice of using standard resolution CT images for the quantitation of diffuse lung disease, these data demonstrate that a single sharp reconstruction (BONE/B46f) should be used for both the qualitative and quantitative evaluation of diffuse lung disease. The sharper reconstruction images, which are required for diagnostic interpretation, provide accurate CT numbers over the range of -1000 to +900 HU and preserve the fidelity of small structures in the reconstructed images. A filtered version of the sharper images can be accurately substituted for images reconstructed with smoother kernels for comparison to previously published results.

Sensitivity study of voxel-based PET image comparison to image registration algorithms

Energy Technology Data Exchange (ETDEWEB)

Yip, Stephen, E-mail: syip@lroc.harvard.edu; Chen, Aileen B.; Berbeco, Ross [Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Aerts, Hugo J. W. L. [Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 and Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115 (United States)

2014-11-01

Purpose: Accurate deformable registration is essential for voxel-based comparison of sequential positron emission tomography (PET) images for proper adaptation of treatment plan and treatment response assessment. The comparison may be sensitive to the method of deformable registration as the optimal algorithm is unknown. This study investigated the impact of registration algorithm choice on therapy response evaluation. Methods: Sixteen patients with 20 lung tumors underwent a pre- and post-treatment computed tomography (CT) and 4D FDG-PET scans before and after chemoradiotherapy. All CT images were coregistered using a rigid and ten deformable registration algorithms. The resulting transformations were then applied to the respective PET images. Moreover, the tumor region defined by a physician on the registered PET images was classified into progressor, stable-disease, and responder subvolumes. Particularly, voxels with standardized uptake value (SUV) decreases >30% were classified as responder, while voxels with SUV increases >30% were progressor. All other voxels were considered stable-disease. The agreement of the subvolumes resulting from difference registration algorithms was assessed by Dice similarity index (DSI). Coefficient of variation (CV) was computed to assess variability of DSI between individual tumors. Root mean square difference (RMS{sub rigid}) of the rigidly registered CT images was used to measure the degree of tumor deformation. RMS{sub rigid} and DSI were correlated by Spearman correlation coefficient (R) to investigate the effect of tumor deformation on DSI. Results: Median DSI{sub rigid} was found to be 72%, 66%, and 80%, for progressor, stable-disease, and responder, respectively. Median DSI{sub deformable} was 63%–84%, 65%–81%, and 82%–89%. Variability of DSI was substantial and similar for both rigid and deformable algorithms with CV > 10% for all subvolumes. Tumor deformation had moderate to significant impact on DSI for progressor

Enhanced ultrasound for advanced diagnostics, ultrasound tomography for volume limb imaging and prosthetic fitting

Science.gov (United States)

Anthony, Brian W.

2016-04-01

Ultrasound imaging methods hold the potential to deliver low-cost, high-resolution, operator-independent and nonionizing imaging systems - such systems couple appropriate algorithms with imaging devices and techniques. The increasing demands on general practitioners motivate us to develop more usable and productive diagnostic imaging equipment. Ultrasound, specifically freehand ultrasound, is a low cost and safe medical imaging technique. It doesn't expose a patient to ionizing radiation. Its safety and versatility make it very well suited for the increasing demands on general practitioners, or for providing improved medical care in rural regions or the developing world. However it typically suffers from sonographer variability; we will discuss techniques to address user variability. We also discuss our work to combine cylindrical scanning systems with state of the art inversion algorithms to deliver ultrasound systems for imaging and quantifying limbs in 3-D in vivo. Such systems have the potential to track the progression of limb health at a low cost and without radiation exposure, as well as, improve prosthetic socket fitting. Current methods of prosthetic socket fabrication remain subjective and ineffective at creating an interface to the human body that is both comfortable and functional. Though there has been recent success using methods like magnetic resonance imaging and biomechanical modeling, a low-cost, streamlined, and quantitative process for prosthetic cup design and fabrication has not been fully demonstrated. Medical ultrasonography may inform the design process of prosthetic sockets in a more objective manner. This keynote talk presents the results of progress in this area.

Optimum image compression rate maintaining diagnostic image quality of digital intraoral radiographs

International Nuclear Information System (INIS)

Song, Ju Seop; Koh, Kwang Joon

2000-01-01

The aims of the present study are to determine the optimum compression rate in terms of file size reduction and diagnostic quality of the images after compression and evaluate the transmission speed of original or each compressed images. The material consisted of 24 extracted human premolars and molars. The occlusal surfaces and proximal surfaces of the teeth had a clinical disease spectrum that ranged from sound to varying degrees of fissure discoloration and cavitation. The images from Digora system were exported in TIFF and the images from conventional intraoral film were scanned and digitalized in TIFF by Nikon SF-200 scanner(Nikon, Japan). And six compression factors were chosen and applied on the basis of the results from a pilot study. The total number of images to be assessed were 336. Three radiologists assessed the occlusal and proximal surfaces of the teeth with 5-rank scale. Finally diagnosed as either sound or carious lesion by one expert oral pathologist. And sensitivity and specificity and kappa value for diagnostic agreement was calculated. Also the area (Az) values under the ROC curve were calculated and paired t-test and oneway ANOVA test was performed. Thereafter, transmission time of the image files of the each compression level were compared with that of the original image files. No significant difference was found between original and the corresponding images up to 7% (1:14) compression ratio for both the occlusal and proximal caries (p<0.05). JPEG3 (1:14) image files are transmitted fast more than 10 times, maintained diagnostic information in image, compared with original image files. 1:14 compressed image file may be used instead of the original image and reduce storage needs and transmission time.

Imaging diagnostics of the foot; Bildgebende Diagnostik des Fusses

Energy Technology Data Exchange (ETDEWEB)

Szeimies, Ulrike; Staebler, Axel [Radiologie in Muenchen-Harlaching, Muenchen (Germany); Walther, Markus (eds.) [Schoen-Klinik Muenchen-Harlaching, Muenchen (Germany). Zentrum fuer Fuss- und Sprunggelenkchirurgie

2012-11-01

The book on imaging diagnostics of the foot contains the following chapters: (1) Imaging techniques. (2) Clinical diagnostics. (3) Ankle joint and hind foot. (4) Metatarsus. (5) Forefoot. (6) Pathology of plantar soft tissue. (7) Nervous system diseases. (8) Diseases without specific anatomic localization. (9) System diseases including the foot. (10) Tumor like lesions. (11) Normative variants.

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Ali, I; Ahmad, S [University of Oklahoma Health Sciences, Oklahoma City, OK (United States); Alsbou, N [Department of Electrical and Computer Engineering, Ada, OH (United States)

2014-06-01

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embedded into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract

Image quality evaluation of full reference algorithm

Science.gov (United States)

He, Nannan; Xie, Kai; Li, Tong; Ye, Yushan

2018-03-01

Image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity Image Metric(SSIM) and feature similarity(FSIM) of objective evaluation methods. The different evaluation methods are tested by Matlab, and the advantages and disadvantages of these methods are obtained by analyzing and comparing them.MSE and PSNR are simple, but they are not considered to introduce HVS characteristics into image quality evaluation. The evaluation result is not ideal. SSIM has a good correlation and simple calculation ,because it is considered to the human visual effect into image quality evaluation,However the SSIM method is based on a hypothesis,The evaluation result is limited. The FSIM method can be used for test of gray image and color image test, and the result is better. Experimental results show that the new image quality evaluation algorithm based on FSIM is more accurate.

Evaluation of compression ratio using JPEG 2000 on diagnostic images in dentistry

International Nuclear Information System (INIS)

Jung, Gi Hun; Han, Won Jeong; Yoo, Dong Soo; Kim, Eun Kyung; Choi, Soon Chul

2005-01-01

To find out the proper compression ratios without degrading image quality and affecting lesion detectability on diagnostic images used in dentistry compressed with JPEG 2000 algorithm. Sixty Digora peri apical images, sixty panoramic computed radiographic (CR) images, sixty computed tomography (CT) images, and sixty magnetic resonance (MR) images were compressed into JPEG 2000 with ratios of 10 levels from 5:1 to 50:1. To evaluate the lesion detectability, the images were graded with 5 levels (1 : definitely absent ; 2 : probably absent ; 3 : equivocal ; 4 : probably present ; 5 : definitely present), and then receiver operating characteristic analysis was performed using the original image as a gold standard. Also to evaluate subjectively the image quality, the images were graded with 5 levels (1 : definitely unacceptable ; 2 : probably unacceptable ; 3 : equivocal ; 4 : probably acceptable ; 5 : definitely acceptable), and then paired t-test was performed. In Digora, CR panoramic and CT images, compressed images up to ratios of 15:1 showed nearly the same lesion detectability as original images, and in MR images, compressed images did up to ratios of 25:1. In Digora and CR panoramic images, compressed images up to ratios of 5:1 showed little difference between the original and reconstructed images in subjective assessment of image quality. In CT images, compressed images did up to ratios of 10:1 and in MR images up to ratios of 15:1. We considered compression ratios up to 5:1 in Digora and CR panoramic images, up to 10:1 in CT images, up to 15:1 in MR images as clinically applicable compression ratios.

Diagnostic Accuracy Comparison of Artificial Immune Algorithms for Primary Headaches

Directory of Open Access Journals (Sweden)

Ufuk Çelik

2015-01-01

Full Text Available The present study evaluated the diagnostic accuracy of immune system algorithms with the aim of classifying the primary types of headache that are not related to any organic etiology. They are divided into four types: migraine, tension, cluster, and other primary headaches. After we took this main objective into consideration, three different neurologists were required to fill in the medical records of 850 patients into our web-based expert system hosted on our project web site. In the evaluation process, Artificial Immune Systems (AIS were used as the classification algorithms. The AIS are classification algorithms that are inspired by the biological immune system mechanism that involves significant and distinct capabilities. These algorithms simulate the specialties of the immune system such as discrimination, learning, and the memorizing process in order to be used for classification, optimization, or pattern recognition. According to the results, the accuracy level of the classifier used in this study reached a success continuum ranging from 95% to 99%, except for the inconvenient one that yielded 71% accuracy.

Application aspects of advanced antenna diagnostics with the 3D reconstruction algorithm

DEFF Research Database (Denmark)

Cappellin, Cecilia; Pivnenko, Sergey

2015-01-01

This paper focuses on two important applications of the 3D reconstruction algorithm of the commercial software DIATOOL for antenna diagnostics. The first one is the accurate and detailed identification of array malfunctioning, thanks to the available enhanced spatial resolution of the reconstruct...... fields and currents. The second one is the filtering of the scattering from support structures and feed network leakage. Representative experimental results are presented and guidelines on the recommended measurement parameters for obtaining the best diagnostics results are provided....

Imaging for dismantlement verification: Information management and analysis algorithms

International Nuclear Information System (INIS)

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

2012-01-01

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

Novel prediction- and subblock-based algorithm for fractal image compression

International Nuclear Information System (INIS)

Chung, K.-L.; Hsu, C.-H.

2006-01-01

Fractal encoding is the most consuming part in fractal image compression. In this paper, a novel two-phase prediction- and subblock-based fractal encoding algorithm is presented. Initially the original gray image is partitioned into a set of variable-size blocks according to the S-tree- and interpolation-based decomposition principle. In the first phase, each current block of variable-size range block tries to find the best matched domain block based on the proposed prediction-based search strategy which utilizes the relevant neighboring variable-size domain blocks. The first phase leads to a significant computation-saving effect. If the domain block found within the predicted search space is unacceptable, in the second phase, a subblock strategy is employed to partition the current variable-size range block into smaller blocks to improve the image quality. Experimental results show that our proposed prediction- and subblock-based fractal encoding algorithm outperforms the conventional full search algorithm and the recently published spatial-correlation-based algorithm by Truong et al. in terms of encoding time and image quality. In addition, the performance comparison among our proposed algorithm and the other two algorithms, the no search-based algorithm and the quadtree-based algorithm, are also investigated

A segmentation algorithm based on image projection for complex text layout

Science.gov (United States)

Zhu, Wangsheng; Chen, Qin; Wei, Chuanyi; Li, Ziyang

2017-10-01

Segmentation algorithm is an important part of layout analysis, considering the efficiency advantage of the top-down approach and the particularity of the object, a breakdown of projection layout segmentation algorithm. Firstly, the algorithm will algorithm first partitions the text image, and divided into several columns, then for each column scanning projection, the text image is divided into several sub regions through multiple projection. The experimental results show that, this method inherits the projection itself and rapid calculation speed, but also can avoid the effect of arc image information page segmentation, and also can accurate segmentation of the text image layout is complex.

Validation of Diagnostic Imaging Based on Repeat Examinations. An Image Interpretation Model

International Nuclear Information System (INIS)

Isberg, B.; Jorulf, H.; Thorstensen, Oe.

2004-01-01

Purpose: To develop an interpretation model, based on repeatedly acquired images, aimed at improving assessments of technical efficacy and diagnostic accuracy in the detection of small lesions. Material and Methods: A theoretical model is proposed. The studied population consists of subjects that develop focal lesions which increase in size in organs of interest during the study period. The imaging modality produces images that can be re-interpreted with high precision, e.g. conventional radiography, computed tomography, and magnetic resonance imaging. At least four repeat examinations are carried out. Results: The interpretation is performed in four or five steps: 1. Independent readers interpret the examinations chronologically without access to previous or subsequent films. 2. Lesions found on images at the last examination are included in the analysis, with interpretation in consensus. 3. By concurrent back-reading in consensus, the lesions are identified on previous images until they are so small that even in retrospect they are undetectable. The earliest examination at which included lesions appear is recorded, and the lesions are verified by their growth (imaging reference standard). Lesion size and other characteristics may be recorded. 4. Records made at step 1 are corrected to those of steps 2 and 3. False positives are recorded. 5. (Optional) Lesion type is confirmed by another diagnostic test. Conclusion: Applied on subjects with progressive disease, the proposed image interpretation model may improve assessments of technical efficacy and diagnostic accuracy in the detection of small focal lesions. The model may provide an accurate imaging reference standard as well as repeated detection rates and false-positive rates for tested imaging modalities. However, potential review bias necessitates a strict protocol

FACT. New image parameters based on the watershed-algorithm

Energy Technology Data Exchange (ETDEWEB)

Linhoff, Lena; Bruegge, Kai Arno; Buss, Jens [TU Dortmund (Germany). Experimentelle Physik 5b; Collaboration: FACT-Collaboration

2016-07-01

FACT, the First G-APD Cherenkov Telescope, is the first imaging atmospheric Cherenkov telescope that is using Geiger-mode avalanche photodiodes (G-APDs) as photo sensors. The raw data produced by this telescope are processed in an analysis chain, which leads to a classification of the primary particle that induce a shower and to an estimation of its energy. One important step in this analysis chain is the parameter extraction from shower images. By the application of a watershed algorithm to the camera image, new parameters are computed. Perceiving the brightness of a pixel as height, a set of pixels can be seen as 'landscape' with hills and valleys. A watershed algorithm groups all pixels to a cluster that belongs to the same hill. From the emerging segmented image, one can find new parameters for later analysis steps, e.g. number of clusters, their shape and containing photon charge. For FACT data, the FellWalker algorithm was chosen from the class of watershed algorithms, because it was designed to work on discrete distributions, in this case the pixels of a camera image. The FellWalker algorithm is implemented in FACT-tools, which provides the low level analysis framework for FACT. This talk will focus on the computation of new, FellWalker based, image parameters, which can be used for the gamma-hadron separation. Additionally, their distributions concerning real and Monte Carlo Data are compared.

Multi-viewpoint Image Array Virtual Viewpoint Rapid Generation Algorithm Based on Image Layering

Science.gov (United States)

Jiang, Lu; Piao, Yan

2018-04-01

The use of multi-view image array combined with virtual viewpoint generation technology to record 3D scene information in large scenes has become one of the key technologies for the development of integrated imaging. This paper presents a virtual viewpoint rendering method based on image layering algorithm. Firstly, the depth information of reference viewpoint image is quickly obtained. During this process, SAD is chosen as the similarity measure function. Then layer the reference image and calculate the parallax based on the depth information. Through the relative distance between the virtual viewpoint and the reference viewpoint, the image layers are weighted and panned. Finally the virtual viewpoint image is rendered layer by layer according to the distance between the image layers and the viewer. This method avoids the disadvantages of the algorithm DIBR, such as high-precision requirements of depth map and complex mapping operations. Experiments show that, this algorithm can achieve the synthesis of virtual viewpoints in any position within 2×2 viewpoints range, and the rendering speed is also very impressive. The average result proved that this method can get satisfactory image quality. The average SSIM value of the results relative to real viewpoint images can reaches 0.9525, the PSNR value can reaches 38.353 and the image histogram similarity can reaches 93.77%.

Improving performance of wavelet-based image denoising algorithm using complex diffusion process

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Sharifzadeh, Sara; Korhonen, Jari

2012-01-01

using a variety of standard images and its performance has been compared against several de-noising algorithms known from the prior art. Experimental results show that the proposed algorithm preserves the edges better and in most cases, improves the measured visual quality of the denoised images......Image enhancement and de-noising is an essential pre-processing step in many image processing algorithms. In any image de-noising algorithm, the main concern is to keep the interesting structures of the image. Such interesting structures often correspond to the discontinuities (edges...... in comparison to the existing methods known from the literature. The improvement is obtained without excessive computational cost, and the algorithm works well on a wide range of different types of noise....

A high-performance spatial database based approach for pathology imaging algorithm evaluation.

Science.gov (United States)

Wang, Fusheng; Kong, Jun; Gao, Jingjing; Cooper, Lee A D; Kurc, Tahsin; Zhou, Zhengwen; Adler, David; Vergara-Niedermayr, Cristobal; Katigbak, Bryan; Brat, Daniel J; Saltz, Joel H

2013-01-01

Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. WE HAVE CONSIDERED TWO SCENARIOS FOR ALGORITHM EVALUATION: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data were formatted based on the PAIS data model and

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

Science.gov (United States)

Overmeyer, Austin D.

2015-01-01

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

A locally adaptive algorithm for shadow correction in color images

Science.gov (United States)

Karnaukhov, Victor; Kober, Vitaly

2017-09-01

The paper deals with correction of color images distorted by spatially nonuniform illumination. A serious distortion occurs in real conditions when a part of the scene containing 3D objects close to a directed light source is illuminated much brighter than the rest of the scene. A locally-adaptive algorithm for correction of shadow regions in color images is proposed. The algorithm consists of segmentation of shadow areas with rank-order statistics followed by correction of nonuniform illumination with human visual perception approach. The performance of the proposed algorithm is compared to that of common algorithms for correction of color images containing shadow regions.

Optimisation of centroiding algorithms for photon event counting imaging

International Nuclear Information System (INIS)

Suhling, K.; Airey, R.W.; Morgan, B.L.

1999-01-01

Approaches to photon event counting imaging in which the output events of an image intensifier are located using a centroiding technique have long been plagued by fixed pattern noise in which a grid of dimensions similar to those of the CCD pixels is superimposed on the image. This is caused by a mismatch between the photon event shape and the centroiding algorithm. We have used hyperbolic cosine, Gaussian, Lorentzian, parabolic as well as 3-, 5-, and 7-point centre of gravity algorithms, and hybrids thereof, to assess means of minimising this fixed pattern noise. We show that fixed pattern noise generated by the widely used centre of gravity centroiding is due to intrinsic features of the algorithm. Our results confirm that the recently proposed use of Gaussian centroiding does indeed show a significant reduction of fixed pattern noise compared to centre of gravity centroiding (Michel et al., Mon. Not. R. Astron. Soc. 292 (1997) 611-620). However, the disadvantage of a Gaussian algorithm is a centroiding failure for small pulses, caused by a division by zero, which leads to a loss of detective quantum efficiency (DQE) and to small amounts of residual fixed pattern noise. Using both real data from an image intensifier system employing a progressive scan camera, framegrabber and PC, and also synthetic data from Monte-Carlo simulations, we find that hybrid centroiding algorithms can reduce the fixed pattern noise without loss of resolution or loss of DQE. Imaging a test pattern to assess the features of the different algorithms shows that a hybrid of Gaussian and 3-point centre of gravity centroiding algorithms results in an optimum combination of low fixed pattern noise (lower than a simple Gaussian), high DQE, and high resolution. The Lorentzian algorithm gives the worst results in terms of high fixed pattern noise and low resolution, and the Gaussian and hyperbolic cosine algorithms have the lowest DQEs

Design of an Image Motion Compenstaion (IMC Algorithm for Image Registration of the Communication, Ocean, Meteorolotical Satellite (COMS-1

Directory of Open Access Journals (Sweden)

Taek Seo Jung

2006-03-01

Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.

Optimizing diagnostic workup in the DRG environment: Dynamic algorithms and minimizing radiologic costs may cost your hospital money

International Nuclear Information System (INIS)

Saint-Louis, L.A.; Henschke, C.I.; Balter, S.; Whalen, J.P.; Balter, P.

1987-01-01

In certain diagnosis-related group (DRG) categories, the availability of sufficient CT scanners or of new equipment, such as MR equipment, can expedite the definitive workup. This will reduce the average length of stay and hospital cost. We analyzed the total hospital and radiologic charges by DRG category for all patients admitted to our hospital in 1985 and 1986. Although the cost per procedure is relatively high, the radiologic component is a small percentage of total hospital costs (median, 3%; maximum, <10%). The authors developed alternative diagnostic algorithms for radiologic-intensive DRG categories. Different diagnostic algorithms proposed for the same clinical problems were compared analytically in terms of impact on the hospital (cost, equipment availability, and length of stay). An example is the workup for FUO. Traditional approach uses plain x-rays and gallium scans and only uses CT when localizing symptoms are present. An alternative approach is to perform CT only. Although more CT examinations would be required, there is considerable reduction in the length of hospital stay and in overall charges. Neurologic and thoracic workups will be given as examples of classes or problems that can be addressed analytically: sequencing of the workup; prevalence; patient population; resource of allocation; and introduction of new imaging modality

Image-Data Compression Using Edge-Optimizing Algorithm for WFA Inference.

Science.gov (United States)

Culik, Karel II; Kari, Jarkko

1994-01-01

Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

Molecular cardiovascular imaging

International Nuclear Information System (INIS)

Schaefers, M.

2007-01-01

Although huge and long-lasting research efforts have been spent on the development of new diagnostic techniques investigating cardiovascular diseases, still fundamental challenges exist; the main challenge being the diagnosis of a suspected or known coronary artery disease or its consequences (myocardial infarction, heart failure etc.). Beside morphological techniques, functional imaging modalities are available in clinical diagnostic algorithms, whereas molecular cardiovascular imaging techniques are still under development. This review summarizes clinical-diagnostical challenges of modern cardiovascular medicine as well as the potential of new molecular imaging techniques to face these. (orig.)

A Novel Plant Root Foraging Algorithm for Image Segmentation Problems

Directory of Open Access Journals (Sweden)

Lianbo Ma

2014-01-01

Full Text Available This paper presents a new type of biologically-inspired global optimization methodology for image segmentation based on plant root foraging behavior, namely, artificial root foraging algorithm (ARFO. The essential motive of ARFO is to imitate the significant characteristics of plant root foraging behavior including branching, regrowing, and tropisms for constructing a heuristic algorithm for multidimensional and multimodal problems. A mathematical model is firstly designed to abstract various plant root foraging patterns. Then, the basic process of ARFO algorithm derived in the model is described in details. When tested against ten benchmark functions, ARFO shows the superiority to other state-of-the-art algorithms on several benchmark functions. Further, we employed the ARFO algorithm to deal with multilevel threshold image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the suitability of the proposed method for solving such problem.

Diagnostic imaging in undergraduate medical education: an expanding role

International Nuclear Information System (INIS)

Miles, K.A.

2005-01-01

Radiologists have been involved in anatomy instruction for medical students for decades. However, recent technical advances in radiology, such as multiplanar imaging, 'virtual endoscopy', functional and molecular imaging, and spectroscopy, offer new ways in which to use imaging for teaching basic sciences to medical students. The broad dissemination of picture archiving and communications systems is making such images readily available to medical schools, providing new opportunities for the incorporation of diagnostic imaging into the undergraduate medical curriculum. Current reforms in the medical curriculum and the establishment of new medical schools in the UK further underline the prospects for an expanding role for imaging in medical education. This article reviews the methods by which diagnostic imaging can be used to support the learning of anatomy and other basic sciences

Decoding using back-project algorithm from coded image in ICF

International Nuclear Information System (INIS)

Jiang shaoen; Liu Zhongli; Zheng Zhijian; Tang Daoyuan

1999-01-01

The principle of the coded imaging and its decoding in inertial confinement fusion is described simply. The authors take ring aperture microscope for example and use back-project (BP) algorithm to decode the coded image. The decoding program has been performed for numerical simulation. Simulations of two models are made, and the results show that the accuracy of BP algorithm is high and effect of reconstruction is good. Thus, it indicates that BP algorithm is applicable to decoding for coded image in ICF experiments

Present practice of diagnostic imaging in the newborn infants

International Nuclear Information System (INIS)

Akamatsu, Hiroshi

1994-01-01

The present practice of diagnostic imaging in our NICU (which includes premature unit) was studied, surveying the total 637 admitted newborn infants during the year of 1992. The total number of diagnostic imaging performed other than scout radiography was 939. The number of ultrasonography of the heart and the brain, and brain CT was 752 or 80.0% of the total. These were done more frequently in the cases of very low birth weight infants. In our NICU, ultrasonography including pulse-doppler method, is performed for diagnosis of structural and functional abnormality of the cardiopulmonary systems and also for finding intracranial lesion, on the basis of finding in plain chest films. In spite of various limitation, we are performing, as the necessity commands, fluoroscopic contrast study, angiography, scintigraphy and MRI for the low birth weight (≥1,500g) and mature infants. Some of the actual cases in which diagnostic imaging was helpful were presented. Recently, upon admittance to the NICU for the specific abnormality of the newborn and premature infants, orginally, asymptomatic diseases are often found and diagnosed. This should be the results of progress in diagnostic imaging in recent years. (author)

Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

DEFF Research Database (Denmark)

Karagiannis, Georgios; Antón Castro, Francesc/François; Mioc, Darka

2016-01-01

An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detec...... of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches....

Diagnostic Medical Imaging in Pediatric Patients and Subsequent Cancer Risk.

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Mulvihill, David J; Jhawar, Sachin; Kostis, John B; Goyal, Sharad

2017-11-01

The use of diagnostic medical imaging is becoming increasingly more commonplace in the pediatric setting. However, many medical imaging modalities expose pediatric patients to ionizing radiation, which has been shown to increase the risk of cancer development in later life. This review article provides a comprehensive overview of the available data regarding the risk of cancer development following exposure to ionizing radiation from diagnostic medical imaging. Attention is paid to modalities such as computed tomography scans and fluoroscopic procedures that can expose children to radiation doses orders of magnitude higher than standard diagnostic x-rays. Ongoing studies that seek to more precisely determine the relationship of diagnostic medical radiation in children and subsequent cancer development are discussed, as well as modern strategies to better quantify this risk. Finally, as cardiovascular imaging and intervention contribute substantially to medical radiation exposure, we discuss strategies to enhance radiation safety in these areas. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

An accelerated threshold-based back-projection algorithm for Compton camera image reconstruction

International Nuclear Information System (INIS)

Mundy, Daniel W.; Herman, Michael G.

2011-01-01

Purpose: Compton camera imaging (CCI) systems are currently under investigation for radiotherapy dose reconstruction and verification. The ability of such a system to provide real-time images during dose delivery will be limited by the computational speed of the image reconstruction algorithm. In this work, the authors present a fast and simple method by which to generate an initial back-projected image from acquired CCI data, suitable for use in a filtered back-projection algorithm or as a starting point for iterative reconstruction algorithms, and compare its performance to the current state of the art. Methods: Each detector event in a CCI system describes a conical surface that includes the true point of origin of the detected photon. Numerical image reconstruction algorithms require, as a first step, the back-projection of each of these conical surfaces into an image space. The algorithm presented here first generates a solution matrix for each slice of the image space by solving the intersection of the conical surface with the image plane. Each element of the solution matrix is proportional to the distance of the corresponding voxel from the true intersection curve. A threshold function was developed to extract those pixels sufficiently close to the true intersection to generate a binary intersection curve. This process is repeated for each image plane for each CCI detector event, resulting in a three-dimensional back-projection image. The performance of this algorithm was tested against a marching algorithm known for speed and accuracy. Results: The threshold-based algorithm was found to be approximately four times faster than the current state of the art with minimal deficit to image quality, arising from the fact that a generically applicable threshold function cannot provide perfect results in all situations. The algorithm fails to extract a complete intersection curve in image slices near the detector surface for detector event cones having axes nearly

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

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Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

An AK-LDMeans algorithm based on image clustering

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Chen, Huimin; Li, Xingwei; Zhang, Yongbin; Chen, Nan

2018-03-01

Clustering is an effective analytical technique for handling unmarked data for value mining. Its ultimate goal is to mark unclassified data quickly and correctly. We use the roadmap for the current image processing as the experimental background. In this paper, we propose an AK-LDMeans algorithm to automatically lock the K value by designing the Kcost fold line, and then use the long-distance high-density method to select the clustering centers to further replace the traditional initial clustering center selection method, which further improves the efficiency and accuracy of the traditional K-Means Algorithm. And the experimental results are compared with the current clustering algorithm and the results are obtained. The algorithm can provide effective reference value in the fields of image processing, machine vision and data mining.

Performance evaluation of the EM algorithm applied to radiographic images

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Brailean, J.C.; Giger, M.L.; Chen, C.T.; Sullivan, B.J.

1990-01-01

In this paper the authors evaluate the expectation maximization (EM) algorithm, both qualitatively and quantitatively, as a technique for enhancing radiographic images. Previous studies have qualitatively shown the usefulness of the EM algorithm but have failed to quantify and compare its performance with those of other image processing techniques. Recent studies by Loo et al, Ishida et al, and Giger et al, have explained improvements in image quality quantitatively in terms of a signal-to-noise ratio (SNR) derived from signal detection theory. In this study, we take a similar approach in quantifying the effect of the EM algorithm on detection of simulated low-contrast square objects superimposed on radiographic mottle. The SNRs of the original and processed images are calculated taking into account both the human visual system response and the screen-film transfer function as well as a noise component internal to the eye-brain system. The EM algorithm was also implemented on digital screen-film images of test patterns and clinical mammograms

Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

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Schüpbach Jörg

2012-04-01

Full Text Available Abstract Background Serologic testing algorithms for recent HIV seroconversion (STARHS provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident ( Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and

Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method

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Lijuan Zhang

2014-01-01

Full Text Available To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constraint. Secondly, the EM algorithm is improved by combining the AO imaging system parameters and regularization technique. A cost function for the joint-deconvolution multiframe AO images is given, and the optimization model for their parameter estimations is built. Lastly, the image-restoration experiments on both analog images and the real AO are performed to verify the recovery effect of our algorithm. The experimental results show that comparing with the Wiener-IBD or RL-IBD algorithm, our iterations decrease 14.3% and well improve the estimation accuracy. The model distinguishes the PSF of the AO images and recovers the observed target images clearly.

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

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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.

Neural Network Blind Equalization Algorithm Applied in Medical CT Image Restoration

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Yunshan Sun

2013-01-01

Full Text Available A new algorithm for iterative blind image restoration is presented in this paper. The method extends blind equalization found in the signal case to the image. A neural network blind equalization algorithm is derived and used in conjunction with Zigzag coding to restore the original image. As a result, the effect of PSF can be removed by using the proposed algorithm, which contributes to eliminate intersymbol interference (ISI. In order to obtain the estimation of the original image, what is proposed in this method is to optimize constant modulus blind equalization cost function applied to grayscale CT image by using conjugate gradient method. Analysis of convergence performance of the algorithm verifies the feasibility of this method theoretically; meanwhile, simulation results and performance evaluations of recent image quality metrics are provided to assess the effectiveness of the proposed method.

A high-performance spatial database based approach for pathology imaging algorithm evaluation

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Fusheng Wang

2013-01-01

Full Text Available Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS data model. Aims: (1 Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2 Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3 Develop a set of queries to support data sampling and result comparisons; (4 Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1 algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2 algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The

Fast Superpixel Segmentation Algorithm for PolSAR Images

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Zhang Yue

2017-10-01

Full Text Available As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

Implementation of digital image encryption algorithm using logistic function and DNA encoding

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Suryadi, MT; Satria, Yudi; Fauzi, Muhammad

2018-03-01

Cryptography is a method to secure information that might be in form of digital image. Based on past research, in order to increase security level of chaos based encryption algorithm and DNA based encryption algorithm, encryption algorithm using logistic function and DNA encoding was proposed. Digital image encryption algorithm using logistic function and DNA encoding use DNA encoding to scramble the pixel values into DNA base and scramble it in DNA addition, DNA complement, and XOR operation. The logistic function in this algorithm used as random number generator needed in DNA complement and XOR operation. The result of the test show that the PSNR values of cipher images are 7.98-7.99 bits, the entropy values are close to 8, the histogram of cipher images are uniformly distributed and the correlation coefficient of cipher images are near 0. Thus, the cipher image can be decrypted perfectly and the encryption algorithm has good resistance to entropy attack and statistical attack.

Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology

International Nuclear Information System (INIS)

Doi, Kunio

2006-01-01

Over the last 50 years, diagnostic imaging has grown from a state of infancy to a high level of maturity. Many new imaging modalities have been developed. However, modern medical imaging includes not only image production but also image processing, computer-aided diagnosis (CAD), image recording and storage, and image transmission, most of which are included in a picture archiving and communication system (PACS). The content of this paper includes a short review of research and development in medical imaging science and technology, which covers (a) diagnostic imaging in the 1950s, (b) the importance of image quality and diagnostic performance, (c) MTF, Wiener spectrum, NEQ and DQE, (d) ROC analysis, (e) analogue imaging systems, (f) digital imaging systems, (g) image processing, (h) computer-aided diagnosis, (i) PACS, (j) 3D imaging and (k) future directions. Although some of the modalities are already very sophisticated, further improvements will be made in image quality for MRI, ultrasound and molecular imaging. The infrastructure of PACS is likely to be improved further in terms of its reliability, speed and capacity. However, CAD is currently still in its infancy, and is likely to be a subject of research for a long time. (review)

Retinex enhancement of infrared images.

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Li, Ying; He, Renjie; Xu, Guizhi; Hou, Changzhi; Sun, Yunyan; Guo, Lei; Rao, Liyun; Yan, Weili

2008-01-01

With the ability of imaging the temperature distribution of body, infrared imaging is promising in diagnostication and prognostication of diseases. However the poor quality of the raw original infrared images prevented applications and one of the essential problems is the low contrast appearance of the imagined object. In this paper, the image enhancement technique based on the Retinex theory is studied, which is a process that automatically retrieve the visual realism to images. The algorithms, including Frackle-McCann algorithm, McCann99 algorithm, single-scale Retinex algorithm, multi-scale Retinex algorithm and multi-scale Retinex algorithm with color restoration, are experienced to the enhancement of infrared images. The entropy measurements along with the visual inspection were compared and results shown the algorithms based on Retinex theory have the ability in enhancing the infrared image. Out of the algorithms compared, MSRCR demonstrated the best performance.

MR imaging diagnostic protocol for unilocular lesions of the jaw

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Hironobu Konouchi

2012-08-01

Using our MR imaging diagnostic protocol to diagnose 31 cases, we obtained a positivity rate of 71.0%. The use of our MR imaging diagnostic protocol for unilocular lesions, which are especially difficult to differentiate by radiography, would improve the morphological and qualitative diagnosis of soft tissue lesions.

Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction.

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Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide

2018-06-01

Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.

Image Reconstruction Algorithm For Electrical Capacitance Tomography (ECT)

International Nuclear Information System (INIS)

Arko

2001-01-01

). Most image reconstruction algorithms for electrical capacitance tomography (ECT) use sensitivity maps as weighting factors. The computation is fast, involving a simple multiply-and- accumulate (MAC) operation, but the resulting image suffers from blurring due to the soft-field effect of the sensor. This paper presents a low cost iterative method employing proportional thresholding, which improves image quality dramatically. The strategy for implementation, computational cost, and achievable speed is examined when using a personal computer (PC) and Digital Signal Processor (DSP). For PC implementation, Watcom C++ 10.6 and Visual C++ 5.0 compilers were used. The experimental results are compared to the images reconstructed by commercially available software. The new algorithm improves the image quality significantly at a cost of a few iterations. This technique can be readily exploited for online applications

3-D Image Encryption Based on Rubik's Cube and RC6 Algorithm

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Helmy, Mai; El-Rabaie, El-Sayed M.; Eldokany, Ibrahim M.; El-Samie, Fathi E. Abd

2017-12-01

A novel encryption algorithm based on the 3-D Rubik's cube is proposed in this paper to achieve 3D encryption of a group of images. This proposed encryption algorithm begins with RC6 as a first step for encrypting multiple images, separately. After that, the obtained encrypted images are further encrypted with the 3-D Rubik's cube. The RC6 encrypted images are used as the faces of the Rubik's cube. From the concepts of image encryption, the RC6 algorithm adds a degree of diffusion, while the Rubik's cube algorithm adds a degree of permutation. The simulation results demonstrate that the proposed encryption algorithm is efficient, and it exhibits strong robustness and security. The encrypted images are further transmitted over wireless Orthogonal Frequency Division Multiplexing (OFDM) system and decrypted at the receiver side. Evaluation of the quality of the decrypted images at the receiver side reveals good results.

Plenoptic Imaging for Three-Dimensional Particle Field Diagnostics.

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Guildenbecher, Daniel Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hall, Elise Munz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-06-01

Plenoptic imaging is a promising emerging technology for single-camera, 3D diagnostics of particle fields. In this work, recent developments towards quantitative measurements of particle size, positions, and velocities are discussed. First, the technique is proven viable with measurements of the particle field generated by the impact of a water drop on a thin film of water. Next, well cont rolled experiments are used to verify diagnostic uncertainty. Finally, an example is presented of 3D plenoptic imaging of a laboratory scale, explosively generated fragment field.

An Improved FCM Medical Image Segmentation Algorithm Based on MMTD

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Ningning Zhou

2014-01-01

Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.

A Versatile Image Processor For Digital Diagnostic Imaging And Its Application In Computed Radiography

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Blume, H.; Alexandru, R.; Applegate, R.; Giordano, T.; Kamiya, K.; Kresina, R.

1986-06-01

In a digital diagnostic imaging department, the majority of operations for handling and processing of images can be grouped into a small set of basic operations, such as image data buffering and storage, image processing and analysis, image display, image data transmission and image data compression. These operations occur in almost all nodes of the diagnostic imaging communications network of the department. An image processor architecture was developed in which each of these functions has been mapped into hardware and software modules. The modular approach has advantages in terms of economics, service, expandability and upgradeability. The architectural design is based on the principles of hierarchical functionality, distributed and parallel processing and aims at real time response. Parallel processing and real time response is facilitated in part by a dual bus system: a VME control bus and a high speed image data bus, consisting of 8 independent parallel 16-bit busses, capable of handling combined up to 144 MBytes/sec. The presented image processor is versatile enough to meet the video rate processing needs of digital subtraction angiography, the large pixel matrix processing requirements of static projection radiography, or the broad range of manipulation and display needs of a multi-modality diagnostic work station. Several hardware modules are described in detail. For illustrating the capabilities of the image processor, processed 2000 x 2000 pixel computed radiographs are shown and estimated computation times for executing the processing opera-tions are presented.

A Novel Perceptual Hash Algorithm for Multispectral Image Authentication

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Kaimeng Ding

2018-01-01

Full Text Available The perceptual hash algorithm is a technique to authenticate the integrity of images. While a few scholars have worked on mono-spectral image perceptual hashing, there is limited research on multispectral image perceptual hashing. In this paper, we propose a perceptual hash algorithm for the content authentication of a multispectral remote sensing image based on the synthetic characteristics of each band: firstly, the multispectral remote sensing image is preprocessed with band clustering and grid partition; secondly, the edge feature of the band subsets is extracted by band fusion-based edge feature extraction; thirdly, the perceptual feature of the same region of the band subsets is compressed and normalized to generate the perceptual hash value. The authentication procedure is achieved via the normalized Hamming distance between the perceptual hash value of the recomputed perceptual hash value and the original hash value. The experiments indicated that our proposed algorithm is robust compared to content-preserved operations and it efficiently authenticates the integrity of multispectral remote sensing images.

A Degree Distribution Optimization Algorithm for Image Transmission

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Jiang, Wei; Yang, Junjie

2016-09-01

Luby Transform (LT) code is the first practical implementation of digital fountain code. The coding behavior of LT code is mainly decided by the degree distribution which determines the relationship between source data and codewords. Two degree distributions are suggested by Luby. They work well in typical situations but not optimally in case of finite encoding symbols. In this work, the degree distribution optimization algorithm is proposed to explore the potential of LT code. Firstly selection scheme of sparse degrees for LT codes is introduced. Then probability distribution is optimized according to the selected degrees. In image transmission, bit stream is sensitive to the channel noise and even a single bit error may cause the loss of synchronization between the encoder and the decoder. Therefore the proposed algorithm is designed for image transmission situation. Moreover, optimal class partition is studied for image transmission with unequal error protection. The experimental results are quite promising. Compared with LT code with robust soliton distribution, the proposed algorithm improves the final quality of recovered images obviously with the same overhead.

Research on Image Reconstruction Algorithms for Tuber Electrical Resistance Tomography System

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Jiang Zili

2016-01-01

Full Text Available The application of electrical resistance tomography (ERT technology has been expanded to the field of agriculture, and the concept of TERT (Tuber Electrical Resistance Tomography is proposed. On the basis of the research on the forward and the inverse problems of the TERT system, a hybrid algorithm based on genetic algorithm is proposed, which can be used in TERT system to monitor the growth status of the plant tubers. The image reconstruction of TERT system is different from the conventional ERT system for two phase-flow measurement. Imaging of TERT needs more precision measurement and the conventional ERT cares more about the image reconstruction speed. A variety of algorithms are analyzed and optimized for the purpose of making them suitable for TERT system. For example: linear back projection, modified Newton-Raphson and genetic algorithm. Experimental results showed that the novel hybrid algorithm is superior to other algorithm and it can effectively improve the image reconstruction quality.

Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

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R. V. V. Krishna

2016-10-01

Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

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W. Lu

2017-09-01

Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

Diagnostic imaging in focal epilepsy

International Nuclear Information System (INIS)

Zlatareva, D.

2013-01-01

Focal epilepsies account for 60% of all seizure disorders worldwide. In this review the classic and new classification system of epileptic seizures and syndromes as well as genetic forms are discussed. Magnetic resonance (MR) is the technique of choice for diagnostic imaging in focal epilepsy because of its sensitivity and high tissue contrast. The review is focused on the lack of consensus of imaging protocols and reported findings in refractory epilepsy. The most frequently encountered MRI findings in epilepsy are reported and their imaging characteristics are depicted. Diagnosis of hippocampal sclerosis and malformations of cortical development as two major causes of refractory focal epilepsy is described in details. Some promising new techniques as positron emission tomography computed tomography (PET/CT) and MR and PET/CT fusion are briefly discussed. Also the relevance of adequate imaging in focal epilepsy, some practical points in imaging interpretation and differential diagnosis are highlighted. (author)

Improved SURF Algorithm and Its Application in Seabed Relief Image Matching

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Zhang Hong-Mei

2017-01-01

Full Text Available The matching based on seabed relief image is widely used in underwater relief matching navigation and target recognition, etc. However, being influenced by various factors, some conventional matching algorithms are difficult to obtain an ideal result in the matching of seabed relief image. SURF(Speeded Up Robust Features algorithm is based on feature points pair to achieve matching, and can get good results in the seabed relief image matching. However, in practical applications, the traditional SURF algorithm is easy to get false matching, especially when the area’s features are similar or not obvious, the problem is more seriously. In order to improve the robustness of the algorithm, this paper proposes an improved matching algorithm, which combines the SURF, and RANSAC (Random Sample Consensus algorithms. The new algorithm integrates the two algorithms advantages, firstly, the SURF algorithm is applied to detect and extract the feature points then to pre-match. Secondly, RANSAC algorithm is utilized to eliminate mismatching points, and then the accurate matching is accomplished with the correct matching points. The experimental results show that the improved algorithm overcomes the mismatching problem effectively and have better precision and faster speed than the traditional SURF algorithm.

From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image

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Mengmeng Zhang

2014-01-01

Full Text Available Image saliency detection has become increasingly important with the development of intelligent identification and machine vision technology. This process is essential for many image processing algorithms such as image retrieval, image segmentation, image recognition, and adaptive image compression. We propose a salient region detection algorithm for full-resolution images. This algorithm analyzes the randomness and correlation of image pixels and pixel-to-region saliency computation mechanism. The algorithm first obtains points with more saliency probability by using the improved smallest univalue segment assimilating nucleus operator. It then reconstructs the entire saliency region detection by taking these points as reference and combining them with image spatial color distribution, as well as regional and global contrasts. The results for subjective and objective image saliency detection show that the proposed algorithm exhibits outstanding performance in terms of technology indices such as precision and recall rates.

A recommender system for medical imaging diagnostic.

Science.gov (United States)

Monteiro, Eriksson; Valente, Frederico; Costa, Carlos; Oliveira, José Luís

2015-01-01

The large volume of data captured daily in healthcare institutions is opening new and great perspectives about the best ways to use it towards improving clinical practice. In this paper we present a context-based recommender system to support medical imaging diagnostic. The system relies on data mining and context-based retrieval techniques to automatically lookup for relevant information that may help physicians in the diagnostic decision.

Diagnostic imaging in fertility disorders

International Nuclear Information System (INIS)

Winfield, A.C.; Fleischer, A.C.

1987-01-01

Some 10%-15% of married couples are affected by a fertility disorder. The number of infertile couples seeking medical assistance has increased dramatically in the past decade. The roles of diagnostic imaging with radiography and US (conventional and transvaginal) is emphasized in the assessment of couples with fertility disorders and an unexpectedly higher incidence of fetal wastage secondary to unsuspected uterine anomalies. The most frequently utilized radiographic examination in infertile patients is hysterosalpingography (HSG). Techniques and complications of HSG are illustrated. The normal anatomy, variants, and congenital anomalies of the uterus and fallopian tubes are demonstrated, as are the numerous abnormalities such as filling defects of the uterine cavity, synechiae, effects of maternal diethylstilbestrol exposure, inflammatory tubal disease, and the more common HSG findings following uterine and tubal surgery. The role of diagnostic imaging in male infertility, including vasography and varicocele detection, are addressed. Conventional and transvaginal US in the management of gynecologic fertility disorders are examined, with an emphasis on follicular monitoring, guided follicular aspirations, endometrial evaluations, and evaluation of other disorders (such as endometriosis) associated with infertility

Fast, fat-suppressed diagnostic imaging of the breast

International Nuclear Information System (INIS)

Metzger, G.J.; Weatherall, P.

1999-01-01

Maximum sensitivity and diagnostic precision of MR imaging of the breast can be achieved only with fat-suppressed diagnostic scans with high resolution. Optimal results were obtained with a 3D-FFE sequence and excitation by a binomial pulse and an amplitude-modulated binomial pulse. (orig./CB) [de

Image Encryption Using a Lightweight Stream Encryption Algorithm

Directory of Open Access Journals (Sweden)

Saeed Bahrami

2012-01-01

Full Text Available Security of the multimedia data including image and video is one of the basic requirements for the telecommunications and computer networks. In this paper, we consider a simple and lightweight stream encryption algorithm for image encryption, and a series of tests are performed to confirm suitability of the described encryption algorithm. These tests include visual test, histogram analysis, information entropy, encryption quality, correlation analysis, differential analysis, and performance analysis. Based on this analysis, it can be concluded that the present algorithm in comparison to A5/1 and W7 stream ciphers has the same security level, is better in terms of the speed of performance, and is used for real-time applications.

Algorithms for reconstructing images for industrial applications

International Nuclear Information System (INIS)

Lopes, R.T.; Crispim, V.R.

1986-01-01

Several algorithms for reconstructing objects from their projections are being studied in our Laboratory, for industrial applications. Such algorithms are useful locating the position and shape of different composition of materials in the object. A Comparative study of two algorithms is made. The two investigated algorithsm are: The MART (Multiplicative - Algebraic Reconstruction Technique) and the Convolution Method. The comparison are carried out from the point view of the quality of the image reconstructed, number of views and cost. (Author) [pt

Magnetic resonance imaging of the wrist: Diagnostic performance statistics

International Nuclear Information System (INIS)

Hobby, Jonathan L.; Tom, Brian D.M.; Bearcroft, Philip W.P.; Dixon, Adrian K.

2001-01-01

AIM: To review the published diagnostic performance statistics for magnetic resonance imaging (MRI) of the wrist for tears of the triangular fibrocartilage complex, the intrinsic carpal ligaments, and for osteonecrosis of the carpal bones. MATERIALS AND METHODS: We used Medline and Embase to search the English language literature. Studies evaluating the diagnostic performance of MRI of the wrist in living patients with surgical confirmation of MR findings were identified. RESULTS: We identified 11 studies reporting the diagnostic performance of MRI for tears of the triangular fibrocartilage complex for a total of 410 patients, six studies for the scapho-lunate ligament (159 patients), six studies for the luno-triquetral ligament (142 patients) and four studies (56 patients) for osteonecrosis of the carpal bones. CONCLUSIONS: Magnetic resonance imaging is an accurate means of diagnosing tears of the triangular fibrocartilage and carpal osteonecrosis. Although MRI is highly specific for tears of the intrinsic carpal ligaments, its sensitivity is low. The diagnostic performance of MRI in the wrist is improved by using high-resolution T2* weighted 3D gradient echo sequences. Using current imaging techniques without intra-articular contrast medium, magnetic resonance imaging cannot reliably exclude tears of the intrinsic carpal ligaments. Hobby, J.L. (2001)

A Spherical Model Based Keypoint Descriptor and Matching Algorithm for Omnidirectional Images

Directory of Open Access Journals (Sweden)

Guofeng Tong

2014-04-01

Full Text Available Omnidirectional images generally have nonlinear distortion in radial direction. Unfortunately, traditional algorithms such as scale-invariant feature transform (SIFT and Descriptor-Nets (D-Nets do not work well in matching omnidirectional images just because they are incapable of dealing with the distortion. In order to solve this problem, a new voting algorithm is proposed based on the spherical model and the D-Nets algorithm. Because the spherical-based keypoint descriptor contains the distortion information of omnidirectional images, the proposed matching algorithm is invariant to distortion. Keypoint matching experiments are performed on three pairs of omnidirectional images, and comparison is made among the proposed algorithm, the SIFT and the D-Nets. The result shows that the proposed algorithm is more robust and more precise than the SIFT, and the D-Nets in matching omnidirectional images. Comparing with the SIFT and the D-Nets, the proposed algorithm has two main advantages: (a there are more real matching keypoints; (b the coverage range of the matching keypoints is wider, including the seriously distorted areas.

Efficient Active Contour and K-Means Algorithms in Image Segmentation

Directory of Open Access Journals (Sweden)

J.R. Rommelse

2004-01-01

Full Text Available In this paper we discuss a classic clustering algorithm that can be used to segment images and a recently developed active contour image segmentation model. We propose integrating aspects of the classic algorithm to improve the active contour model. For the resulting CVK and B-means segmentation algorithms we examine methods to decrease the size of the image domain. The CVK method has been implemented to run on parallel and distributed computers. By changing the order of updating the pixels, it was possible to replace synchronous communication with asynchronous communication and subsequently the parallel efficiency is improved.

Diagnostic imaging of exotic pets

International Nuclear Information System (INIS)

Silverman, S.

1993-01-01

Radiographic, ultrasonographic, and computed tomographic (CT) imaging are important diagnostic modalities in exotic pets. The use of appropriate radiographic equipment, film-screen combinations, and radiographic projections enhances the information obtained from radiographs. Both normal findings and common radiographic abnormalities are discussed. The use of ultrasonography and CT scanning for exotic small mammals and reptiles is described

A MAP blind image deconvolution algorithm with bandwidth over-constrained

Science.gov (United States)

Ren, Zhilei; Liu, Jin; Liang, Yonghui; He, Yulong

2018-03-01

We demonstrate a maximum a posteriori (MAP) blind image deconvolution algorithm with bandwidth over-constrained and total variation (TV) regularization to recover a clear image from the AO corrected images. The point spread functions (PSFs) are estimated by bandwidth limited less than the cutoff frequency of the optical system. Our algorithm performs well in avoiding noise magnification. The performance is demonstrated on simulated data.

Iris recognition using image moments and k-means algorithm.

Science.gov (United States)

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%.

Diagnostic imaging in pregraduate integrated curricula

International Nuclear Information System (INIS)

Kainberger, F.; Kletter, K.

2007-01-01

Pregraduate medical curricula are currently undergoing a reform process that is moving away from a traditional discipline-related structure and towards problem-based integrated forms of teaching. Imaging sciences, with their inherently technical advances, are specifically influenced by the effects of paradigm shifts in medical education. The teaching of diagnostic radiology should be based on the definition of three core competencies: in vivo visualization of normal and abnormal morphology and function, diagnostic reasoning, and interventional treatment. On the basis of these goals, adequate teaching methods and e-learning tools should be implemented by focusing on case-based teaching. Teaching materials used in the fields of normal anatomy, pathology, and clinical diagnosis may help diagnostic radiology to play a central role in modern pregraduate curricula. (orig.)

[Diagnostic imaging in pregraduate integrated curricula].

Science.gov (United States)

Kainberger, F; Kletter, K

2007-11-01

Pregraduate medical curricula are currently undergoing a reform process that is moving away from a traditional discipline-related structure and towards problem-based integrated forms of teaching. Imaging sciences, with their inherently technical advances, are specifically influenced by the effects of paradigm shifts in medical education. The teaching of diagnostic radiology should be based on the definition of three core competencies: in vivo visualization of normal and abnormal morphology and function, diagnostic reasoning, and interventional treatment. On the basis of these goals, adequate teaching methods and e-learning tools should be implemented by focusing on case-based teaching. Teaching materials used in the fields of normal anatomy, pathology, and clinical diagnosis may help diagnostic radiology to play a central role in modern pregraduate curricula.

New Autism Diagnostic Interview-Revised Algorithms for Toddlers and Young Preschoolers from 12 to 47 Months of Age

Science.gov (United States)

Kim, So Hyun; Lord, Catherine

2012-01-01

Autism Diagnostic Interview-Revised (Rutter et al. in "Autism diagnostic interview-revised." Western Psychological Services, Los Angeles, 2003) diagnostic algorithms specific to toddlers and young preschoolers were created using 829 assessments of children aged from 12 to 47 months with ASD, nonspectrum disorders, and typical development. The…

A Class of Manifold Regularized Multiplicative Update Algorithms for Image Clustering.

Science.gov (United States)

Yang, Shangming; Yi, Zhang; He, Xiaofei; Li, Xuelong

2015-12-01

Multiplicative update algorithms are important tools for information retrieval, image processing, and pattern recognition. However, when the graph regularization is added to the cost function, different classes of sample data may be mapped to the same subspace, which leads to the increase of data clustering error rate. In this paper, an improved nonnegative matrix factorization (NMF) cost function is introduced. Based on the cost function, a class of novel graph regularized NMF algorithms is developed, which results in a class of extended multiplicative update algorithms with manifold structure regularization. Analysis shows that in the learning, the proposed algorithms can efficiently minimize the rank of the data representation matrix. Theoretical results presented in this paper are confirmed by simulations. For different initializations and data sets, variation curves of cost functions and decomposition data are presented to show the convergence features of the proposed update rules. Basis images, reconstructed images, and clustering results are utilized to present the efficiency of the new algorithms. Last, the clustering accuracies of different algorithms are also investigated, which shows that the proposed algorithms can achieve state-of-the-art performance in applications of image clustering.

An adaptive clustering algorithm for image matching based on corner feature

Science.gov (United States)

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

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

A comparative study of image low level feature extraction algorithms

Directory of Open Access Journals (Sweden)

M.M. El-gayar

2013-07-01

Full Text Available Feature extraction and matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods for assessing the performance of popular image matching algorithms are presented and rely on costly descriptors for detection and matching. Specifically, the method assesses the type of images under which each of the algorithms reviewed herein perform to its maximum or highest efficiency. The efficiency is measured in terms of the number of matches founds by the algorithm and the number of type I and type II errors encountered when the algorithm is tested against a specific pair of images. Current comparative studies asses the performance of the algorithms based on the results obtained in different criteria such as speed, sensitivity, occlusion, and others. This study addresses the limitations of the existing comparative tools and delivers a generalized criterion to determine beforehand the level of efficiency expected from a matching algorithm given the type of images evaluated. The algorithms and the respective images used within this work are divided into two groups: feature-based and texture-based. And from this broad classification only three of the most widely used algorithms are assessed: color histogram, FAST (Features from Accelerated Segment Test, SIFT (Scale Invariant Feature Transform, PCA-SIFT (Principal Component Analysis-SIFT, F-SIFT (fast-SIFT and SURF (speeded up robust features. The performance of the Fast-SIFT (F-SIFT feature detection methods are compared for scale changes, rotation, blur, illumination changes and affine transformations. All the experiments use repeatability measurement and the number of correct matches for the evaluation measurements. SIFT presents its stability in most situations although its slow. F-SIFT is the fastest one with good performance as the same as SURF, SIFT, PCA-SIFT show its advantages in rotation and illumination changes.

Development of information preserving data compression algorithm for CT images

International Nuclear Information System (INIS)

Kobayashi, Yoshio

1989-01-01

Although digital imaging techniques in radiology develop rapidly, problems arise in archival storage and communication of image data. This paper reports on a new information preserving data compression algorithm for computed tomographic (CT) images. This algorithm consists of the following five processes: 1. Pixels surrounding the human body showing CT values smaller than -900 H.U. are eliminated. 2. Each pixel is encoded by its numerical difference from its neighboring pixel along a matrix line. 3. Difference values are encoded by a newly designed code rather than the natural binary code. 4. Image data, obtained with the above process, are decomposed into bit planes. 5. The bit state transitions in each bit plane are encoded by run length coding. Using this new algorithm, the compression ratios of brain, chest, and abdomen CT images are 4.49, 4.34. and 4.40 respectively. (author)

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

NARCIS (Netherlands)

Bejnordi, Babak Ehteshami; Veta, Mitko; van Diest, Paul Johannes; Van Ginneken, Bram; Karssemeijer, Nico; Litjens, Geert; van der Laak, Jeroen A.W.M.; Hermsen, Meyke; Manson, Quirine F.; Balkenhol, Maschenka; Geessink, Oscar; Stathonikos, Nikolaos; Van Dijk, Marcory C.R.F.; Bult, Peter; Beca, Francisco; Beck, Andrew H.; Wang, Dayong; Khosla, Aditya; Gargeya, Rishab; Irshad, Humayun; Zhong, Aoxiao; Dou, Qi; Li, Quanzheng; Chen, Hao; Lin, Huang Jing; Heng, Pheng Ann; Haß, Christian; Bruni, Elia; Wong, Quincy; Halici, Ugur; Öner, Mustafa Ümit; Cetin-Atalay, Rengul; Berseth, Matt; Khvatkov, Vitali; Vylegzhanin, Alexei; Kraus, Oren; Shaban, Muhammad; Rajpoot, Nasir; Awan, Ruqayya; Sirinukunwattana, Korsuk; Qaiser, Talha; Tsang, Yee Wah; Tellez, David; Annuscheit, Jonas; Hufnagl, Peter; Valkonen, Mira; Kartasalo, Kimmo; Latonen, Leena; Ruusuvuori, Pekka; Liimatainen, Kaisa

2017-01-01

IMPORTANCE: Application of deep learning algorithms to whole-slide pathology imagescan potentially improve diagnostic accuracy and efficiency. OBJECTIVE: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph

Post-graduate training in imaging diagnostics, nuclear medicine and radiotherapy for radiographers

International Nuclear Information System (INIS)

Petkova, E.; Velkova, K.; Shangova, M.; Karidova, S.

2006-01-01

Full text: The application of new technologies in imaging diagnostics, as well as the use of digital processing and storing of information, has increased the quality and scope of imaging diagnostics. The potentials of therapeutic methods connected with imaging diagnostics and nuclear medicine, interventional therapeutic procedures (dilatation, embolism, stent, etc.), basins with radio-pharmaceuticals, etc., are constantly increasing. The constant training of radiographers in working with the new, advanced image-diagnostic equipment has become an established international practice in the process of training the human resources of the imaging-diagnostic departments and centers. Objectives: 1. Investigating the potentials of post-graduate training for monitoring the dynamics in the development of the principles, methods and techniques in imaging diagnostics; 2. The attitude of radiographers towards post-graduate training. Systematic approach and critical analysis of published data and mathematical-statistical methods with regard to the need of post-graduate training. The processed data of the survey on the necessity for post-graduate training conducted among 3rd year students in the last 3 years - 75 % consider post-graduate training mandatory, 11% deem it necessary, and 14% have no opinion on the issue; and among the working radiographers in the last 3 years the results are as follows: mandatory - 91%, necessary - 7%, no opinion - 2%. The improvement and advances in imaging diagnostic equipment and apparatuses have considerably outstripped the professional training of radiographers. The key word in the race for knowledge is constant learning and training, which can successfully be achieved within the framework of post-graduate training

The ANACONDA algorithm for deformable image registration in radiotherapy

International Nuclear Information System (INIS)

Weistrand, Ola; Svensson, Stina

2015-01-01

Purpose: The purpose of this work was to describe a versatile algorithm for deformable image registration with applications in radiotherapy and to validate it on thoracic 4DCT data as well as CT/cone beam CT (CBCT) data. Methods: ANAtomically CONstrained Deformation Algorithm (ANACONDA) combines image information (i.e., intensities) with anatomical information as provided by contoured image sets. The registration problem is formulated as a nonlinear optimization problem and solved with an in-house developed solver, tailored to this problem. The objective function, which is minimized during optimization, is a linear combination of four nonlinear terms: 1. image similarity term; 2. grid regularization term, which aims at keeping the deformed image grid smooth and invertible; 3. a shape based regularization term which works to keep the deformation anatomically reasonable when regions of interest are present in the reference image; and 4. a penalty term which is added to the optimization problem when controlling structures are used, aimed at deforming the selected structure in the reference image to the corresponding structure in the target image. Results: To validate ANACONDA, the authors have used 16 publically available thoracic 4DCT data sets for which target registration errors from several algorithms have been reported in the literature. On average for the 16 data sets, the target registration error is 1.17 ± 0.87 mm, Dice similarity coefficient is 0.98 for the two lungs, and image similarity, measured by the correlation coefficient, is 0.95. The authors have also validated ANACONDA using two pelvic cases and one head and neck case with planning CT and daily acquired CBCT. Each image has been contoured by a physician (radiation oncologist) or experienced radiation therapist. The results are an improvement with respect to rigid registration. However, for the head and neck case, the sample set is too small to show statistical significance. Conclusions: ANACONDA

Algorithm-Architecture Matching for Signal and Image Processing

CERN Document Server

Gogniat, Guy; Morawiec, Adam; Erdogan, Ahmet

2011-01-01

Advances in signal and image processing together with increasing computing power are bringing mobile technology closer to applications in a variety of domains like automotive, health, telecommunication, multimedia, entertainment and many others. The development of these leading applications, involving a large diversity of algorithms (e.g. signal, image, video, 3D, communication, cryptography) is classically divided into three consecutive steps: a theoretical study of the algorithms, a study of the target architecture, and finally the implementation. Such a linear design flow is reaching its li

Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI)

International Nuclear Information System (INIS)

Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

2007-01-01

Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting

Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress

International Nuclear Information System (INIS)

Liu, Patrick T.; Pavlicek, William P.; Peter, Mary B.; Roberts, Catherine C.; Paden, Robert G.; Spangehl, Mark J.

2009-01-01

Despite recent advances in CT technology, metal orthopedic implants continue to cause significant artifacts on many CT exams, often obscuring diagnostic information. We performed this prospective study to evaluate the effectiveness of an experimental metal artifact reduction (MAR) image reconstruction program for CT. We examined image quality on CT exams performed in patients with hip arthroplasties as well as other types of implanted metal orthopedic devices. The exam raw data were reconstructed using two different methods, the standard filtered backprojection (FBP) program and the MAR program. Images were evaluated for quality of the metal-cement-bone interfaces, trabeculae ≤1 cm from the metal, trabeculae 5 cm apart from the metal, streak artifact, and overall soft tissue detail. The Wilcoxon Rank Sum test was used to compare the image scores from the large and small prostheses. Interobserver agreement was calculated. When all patients were grouped together, the MAR images showed mild to moderate improvement over the FBP images. However, when the cases were divided by implant size, the MAR images consistently received higher image quality scores than the FBP images for large metal implants (total hip prostheses). For small metal implants (screws, plates, staples), conversely, the MAR images received lower image quality scores than the FBP images due to blurring artifact. The difference of image scores for the large and small implants was significant (p=0.002). Interobserver agreement was found to be high for all measures of image quality (k>0.9). The experimental MAR reconstruction algorithm significantly improved CT image quality for patients with large metal implants. However, the MAR algorithm introduced blurring artifact that reduced image quality with small metal implants. (orig.)

Pediatric chest HRCT using the iDose4 Hybrid Iterative Reconstruction Algorithm: Which iDose level to choose?

International Nuclear Information System (INIS)

Smarda, M; Alexopoulou, E; Mazioti, A; Kordolaimi, S; Ploussi, A; Efstathopoulos, E; Priftis, K

2015-01-01

Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our department's 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions. (paper)

An Image Encryption Algorithm Based on Balanced Pixel and Chaotic Map

Directory of Open Access Journals (Sweden)

Jian Zhang

2014-01-01

Full Text Available Image encryption technology has been applied in many fields and is becoming the main way of protecting the image information security. There are also many ways of image encryption. However, the existing encryption algorithms, in order to obtain a better effect of encryption, always need encrypting several times. There is not an effective method to decide the number of encryption times, generally determined by the human eyes. The paper proposes an image encryption algorithm based on chaos and simultaneously proposes a balanced pixel algorithm to determine the times of image encryption. Many simulation experiments have been done including encryption effect and security analysis. Experimental results show that the proposed method is feasible and effective.

Diagnostic accuracy of imaging modalities for internal derangements of temporomandibular joint

International Nuclear Information System (INIS)

Kobayashi, Kaoru; Igarashi, Chinami; Yuasa, Masao; Imanaka, Masahiro; Kondoh, Toshirou

1998-01-01

The purpose of this study was to evaluate and review the diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of imaging diagnosis for temporomandibular disorders. The role of diagnostic imaging is to detect and document specific anatomic abnormalities associated with the signs and symptoms in the temporomandibular joint. Magnetic resonance imaging (MR imaging) can accurately depict disc displacement and disc deformity. MR imaging is our first choice among the various imaging modalities for the patients with clinical signs and symptoms. However, it has been shown that intra-capsular adhesions and perforations of the disc and retrodiscal tissue are sometimes not detected by MR imaging. To improve the diagnostic technique for adhesions and perforations, double-contrast arthrotomography with fluoroscopy should be employed. The irregular surface of the eminences and the glenoid fossae shown by MR imaging and tomography are correlated with subchondral bone exposure by arthroscopy. Erosion of the condyles detected by MR imaging, tomography and rotational panoramic radiography is correlated with subchondral bone exposure detected by arthroscopy. (author). 69 refs

New segmentation-based tone mapping algorithm for high dynamic range image

Science.gov (United States)

Duan, Weiwei; Guo, Huinan; Zhou, Zuofeng; Huang, Huimin; Cao, Jianzhong

2017-07-01

The traditional tone mapping algorithm for the display of high dynamic range (HDR) image has the drawback of losing the impression of brightness, contrast and color information. To overcome this phenomenon, we propose a new tone mapping algorithm based on dividing the image into different exposure regions in this paper. Firstly, the over-exposure region is determined using the Local Binary Pattern information of HDR image. Then, based on the peak and average gray of the histogram, the under-exposure and normal-exposure region of HDR image are selected separately. Finally, the different exposure regions are mapped by differentiated tone mapping methods to get the final result. The experiment results show that the proposed algorithm achieve the better performance both in visual quality and objective contrast criterion than other algorithms.

The clinician's guide to diagnostic imaging: Cost-effective pathways. Second edition

International Nuclear Information System (INIS)

Grossman, Z.D.; Chew, F.S.; Ellis, D.A.; Brigham, S.C.

1987-01-01

The authors developed a cost-effective approach to imaging studies, based on initial selection of an exam that best addresses the specific clinical problem and obviates the need for additional diagnostic tests. Tightly reasoned arguments compare available imaging options with respect to diagnostic yield, feasibility, risk, and cost. To aid the clinician in making cost comparisons, each paper of the Second Edition lists the dollar cost of relevant imaging studies. The Second Edition has been thoroughly revised to reflect the important advances in diagnostic imaging of the past three years, highlighting CT's expanding role in thoracic and abdominal problems, magnetic resonance imaging as a spectacular diagnostic tool for the central nervous system, and the clinical application of many newly-developed radiopharmaceuticals. New chapters cover breast cancer screening, acute spinal trauma, search for primary cancer of unknown origin, acute anuria, blunt chest trauma, new onset seizures, and spinal cord compression from metastases. Other papers have been rewritten for greater clarity and to incorporate new techniques, like dipyridamole stress testing. A glossary and an introduction define and explain the capabilities and limitations of current techniques

First results of genetic algorithm application in ML image reconstruction in emission tomography

International Nuclear Information System (INIS)

Smolik, W.

1999-01-01

This paper concerns application of genetic algorithm in maximum likelihood image reconstruction in emission tomography. The example of genetic algorithm for image reconstruction is presented. The genetic algorithm was based on the typical genetic scheme modified due to the nature of solved problem. The convergence of algorithm was examined. The different adaption functions, selection and crossover methods were verified. The algorithm was tested on simulated SPECT data. The obtained results of image reconstruction are discussed. (author)

Diagnostic imaging of lymphomas in pediatric patients

International Nuclear Information System (INIS)

Petrova, A.

2010-01-01

Lymphoma is the third most common malignancy in children, after leukemias and brain tumors, most commonly during early childhood before 14 years. In definite stages cancer can engage all organs and systems. These conditions associate with immunodeficiency, increased susceptibility to infections and second neoplasms. The social importance of the problem requires early diagnosis, accurate staging, and assessment of the treatment and determination of the risk for relapse of the disease. The aim of the present review is to represent the role of the modern methods of diagnostic imaging - ultrasonography (US), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Positron Emisson Tomography (PET) scan in the process of diagnostics, in the decision of therapeutic strategy and the follow-up of children with lymphomas

Time Reversal Reconstruction Algorithm Based on PSO Optimized SVM Interpolation for Photoacoustic Imaging

Directory of Open Access Journals (Sweden)

Mingjian Sun

2015-01-01

Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.

Basic artefacts of diagnostic imaging by the magnetic resonance method

International Nuclear Information System (INIS)

Vitak, T.; Seidl, Z.; Obenberger, J.; Vaneckova, M.; Danes, J.; Krasensky, J.; Peterkova, V

2000-01-01

Artefacts in diagnostic imaging are defined as a geometric or anatomic misrepresentation of the reality by the image formed. The article deals with artefacts due to field and frequency shifts, in particular due to the water-fat chemical shift and due to magnetic susceptibility. The physical nature of the artefacts is explained and their diagnostic significance is discussed. (P.A.)

A novel image encryption algorithm based on a 3D chaotic map

Science.gov (United States)

Kanso, A.; Ghebleh, M.

2012-07-01

Recently [Solak E, Çokal C, Yildiz OT Biyikoǧlu T. Cryptanalysis of Fridrich's chaotic image encryption. Int J Bifur Chaos 2010;20:1405-1413] cryptanalyzed the chaotic image encryption algorithm of [Fridrich J. Symmetric ciphers based on two-dimensional chaotic maps. Int J Bifur Chaos 1998;8(6):1259-1284], which was considered a benchmark for measuring security of many image encryption algorithms. This attack can also be applied to other encryption algorithms that have a structure similar to Fridrich's algorithm, such as that of [Chen G, Mao Y, Chui, C. A symmetric image encryption scheme based on 3D chaotic cat maps. Chaos Soliton Fract 2004;21:749-761]. In this paper, we suggest a novel image encryption algorithm based on a three dimensional (3D) chaotic map that can defeat the aforementioned attack among other existing attacks. The design of the proposed algorithm is simple and efficient, and based on three phases which provide the necessary properties for a secure image encryption algorithm including the confusion and diffusion properties. In phase I, the image pixels are shuffled according to a search rule based on the 3D chaotic map. In phases II and III, 3D chaotic maps are used to scramble shuffled pixels through mixing and masking rules, respectively. Simulation results show that the suggested algorithm satisfies the required performance tests such as high level security, large key space and acceptable encryption speed. These characteristics make it a suitable candidate for use in cryptographic applications.

A novel algorithm for thermal image encryption.

Science.gov (United States)

Hussain, Iqtadar; Anees, Amir; Algarni, Abdulmohsen

2018-04-16

Thermal images play a vital character at nuclear plants, Power stations, Forensic labs biological research, and petroleum products extraction. Safety of thermal images is very important. Image data has some unique features such as intensity, contrast, homogeneity, entropy and correlation among pixels that is why somehow image encryption is trickier as compare to other encryptions. With conventional image encryption schemes it is normally hard to handle these features. Therefore, cryptographers have paid attention to some attractive properties of the chaotic maps such as randomness and sensitivity to build up novel cryptosystems. That is why, recently proposed image encryption techniques progressively more depends on the application of chaotic maps. This paper proposed an image encryption algorithm based on Chebyshev chaotic map and S8 Symmetric group of permutation based substitution boxes. Primarily, parameters of chaotic Chebyshev map are chosen as a secret key to mystify the primary image. Then, the plaintext image is encrypted by the method generated from the substitution boxes and Chebyshev map. By this process, we can get a cipher text image that is perfectly twisted and dispersed. The outcomes of renowned experiments, key sensitivity tests and statistical analysis confirm that the proposed algorithm offers a safe and efficient approach for real-time image encryption.

A new modified fast fractal image compression algorithm

DEFF Research Database (Denmark)

Salarian, Mehdi; Nadernejad, Ehsan; MiarNaimi, Hossein

2013-01-01

In this paper, a new fractal image compression algorithm is proposed, in which the time of the encoding process is considerably reduced. The algorithm exploits a domain pool reduction approach, along with the use of innovative predefined values for contrast scaling factor, S, instead of searching...

Diagnostic imaging in child abuse

International Nuclear Information System (INIS)

Stoever, B.

2007-01-01

Diagnostic imaging in child abuse plays an important role and includes the depiction of skeletal injuries, soft tissue lesions, visceral injuries in ''battered child syndrome'' and brain injuries in ''shaken baby syndrome''. The use of appropriate imaging modalities allows specific fractures to be detected, skeletal lesions to be dated and the underlying mechanism of the lesion to be described. The imaging results must be taken into account when assessing the clinical history, clinical findings and differential diagnoses. Computed tomography (CT) and magnetic resonance imaging (MRI) examinations must be performed in order to detect lesions of the central nervous system (CNS) immediately. CT is necessary in the initial diagnosis to delineate oedema and haemorrhages. Early detection of brain injuries in children with severe neurological symptoms can prevent serious late sequelae. MRI is performed in follow-up investigations and is used to describe residual lesions, including parenchymal findings. (orig.) [de

Multidetector CT: a new gold standard in the diagnosis of pulmonary embolism? State of the art and diagnostic algorithms

International Nuclear Information System (INIS)

Russo, Vincenzo; Piva, Tommaso; Lovato, Luigi; Fattori, Rossella; Gavelli, Giampaolo

2005-01-01

Purpose: From the early 90s, spiral CT technology has considerably changed the diagnostic capability of Pulmonary Embolism (PE), giving a direct vision of intravascular thrombi. Further technological progress has straightened its diagnostic impact leading to an essential role in clinical practice. The advent of Multi-Detector CT (MDCT) has subsequently increased the reliability of this technique to the point of undermining the role of pulmonary angiography as the gold standard and occupying a central position in diagnostic algorithms. The aim of this paper is to appraise this evolution by means of a meta-analysis of the relevant literature from 1995 to 2004. Results: The review of the literature showed the sensitivity and specificity of CT to have increased from 37-94% and 91-100% (single detector CT) to 87-94% and 94-100% (4-channel multidetector CT), especially thanks to the possibility of depicting subsegmental clots, with an interobserver agreement of 0.63-0.94 (k). Conclusions: CT is one of the most reliable and effective methods in the diagnosis is PE, with the advantage of being extremely fast and providing alternative diagnoses. Recent improvements in MDCT technology confers the highest value of diagnostic accuracy with respect to other imaging modalities such as scintigraphy, angiography, MRI, D-dimer essay and Doppler US [it

An Orthogonal Learning Differential Evolution Algorithm for Remote Sensing Image Registration

Directory of Open Access Journals (Sweden)

Wenping Ma

2014-01-01

Full Text Available We introduce an area-based method for remote sensing image registration. We use orthogonal learning differential evolution algorithm to optimize the similarity metric between the reference image and the target image. Many local and global methods have been used to achieve the optimal similarity metric in the last few years. Because remote sensing images are usually influenced by large distortions and high noise, local methods will fail in some cases. For this reason, global methods are often required. The orthogonal learning (OL strategy is efficient when searching in complex problem spaces. In addition, it can discover more useful information via orthogonal experimental design (OED. Differential evolution (DE is a heuristic algorithm. It has shown to be efficient in solving the remote sensing image registration problem. So orthogonal learning differential evolution algorithm (OLDE is efficient for many optimization problems. The OLDE method uses the OL strategy to guide the DE algorithm to discover more useful information. Experiments show that the OLDE method is more robust and efficient for registering remote sensing images.

HEREDITARY CONNECTIVE TISSUE DISORDERS: NOMENCLATURE AND DIAGNOSTIC ALGORITHM

Directory of Open Access Journals (Sweden)

A. V. Klemenov

2015-01-01

Full Text Available Hereditary connective tissue disorders (HCTDs are a genetically and clinically diverse group of diseases, which encompasses common congenital disorders of fibrous connective tissue structures. Out of the whole variety of the clinical manifestations of NCTDs, only differentiated monogenic syndromes with the agreed guidelines for their diagnosis have been long the focus of the medical community’s attention. Many unclassified forms of the pathology (dysplasia phenotypes have been disregarded while assessing a person’s prognosis and defining treatment policy. With no clear definition of NCTDs or their approved diagnostic algorithm, it is difficult to study their real prevalence in the population, to compare literature data, and to constructively discuss various scientific and practical aspects of this disease. Efforts to systematize individual clinical types of NCTD and to formulate their diagnostic criteria are set forth in the All-Russian Research Society Expert Committee national guidelines approved in 2009 and revised in 2012. The paper gives current views on the nomenclature of NCTDs, considers diagnostic criteria for both classified monogenic syndromes (Marfan's syndrome, Ehlers–Danlos' syndrome, MASS phenotype, primary mitral valve prolapse, joint hypermobility syndrome and unclassified dysplasia phenotypes (MASS-like phenotype, marfanoid appearance, Ehlers–Danlos-like phenotype, benign joint hypermobility syndrome, unclassified phenotype. The above abnormalities are presented as a continuous list drawn up in the decreasing order of the degree of their clinical manifestations and prognostic value (the phenotypic continuum described by M.J. Glesby and R.E. Pyentz: from monogenic syndromes through dysplasia phenotypes to an unclassified phenotype. Emphasis is laid on the clinical NCTD identification difficulties associated with the lack of specificity of external and visceral markers of connective tissue asthenia and with the certain

Image Retrieval Algorithm Based on Discrete Fractional Transforms

Science.gov (United States)

Jindal, Neeru; Singh, Kulbir

2013-06-01

The discrete fractional transforms is a signal processing tool which suggests computational algorithms and solutions to various sophisticated applications. In this paper, a new technique to retrieve the encrypted and scrambled image based on discrete fractional transforms has been proposed. Two-dimensional image was encrypted using discrete fractional transforms with three fractional orders and two random phase masks placed in the two intermediate planes. The significant feature of discrete fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. Security strength was enhanced (1024!)4 times by scrambling the encrypted image. In decryption process, image retrieval is sensitive for both correct fractional order keys and scrambling algorithm. The proposed approach make the brute force attack infeasible. Mean square error and relative error are the recital parameters to verify validity of proposed method.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

Energy Technology Data Exchange (ETDEWEB)

Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch [University of Applied Sciences and Arts Northwestern Switzerland FHNW, 5210 Windisch (Switzerland)

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

Science.gov (United States)

Felix, Simon; Bolzern, Roman; Battaglia, Marina

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

Acceleration of the direct reconstruction of linear parametric images using nested algorithms

International Nuclear Information System (INIS)

Wang Guobao; Qi Jinyi

2010-01-01

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

An algorithm for 4D CT image sorting using spatial continuity.

Science.gov (United States)

Li, Chen; Liu, Jie

2013-01-01

4D CT, which could locate the position of the movement of the tumor in the entire respiratory cycle and reduce image artifacts effectively, has been widely used in making radiation therapy of tumors. The current 4D CT methods required external surrogates of respiratory motion obtained from extra instruments. However, respiratory signals recorded by these external makers may not always accurately represent the internal tumor and organ movements, especially when irregular breathing patterns happened. In this paper we have proposed a novel automatic 4D CT sorting algorithm that performs without these external surrogates. The sorting algorithm requires collecting the image data with a cine scan protocol. Beginning with the first couch position, images from the adjacent couch position are selected out according to spatial continuity. The process is continued until images from all couch positions are sorted and the entire 3D volume is produced. The algorithm is verified by respiratory phantom image data and clinical image data. The primary test results show that the 4D CT images created by our algorithm have eliminated the motion artifacts effectively and clearly demonstrated the movement of tumor and organ in the breath period.

Low dose reconstruction algorithm for differential phase contrast imaging.

Science.gov (United States)

Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni

2011-01-01

Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.

Diagnostic value of imaging in infective endocarditis: a systematic review.

Science.gov (United States)

Gomes, Anna; Glaudemans, Andor W J M; Touw, Daan J; van Melle, Joost P; Willems, Tineke P; Maass, Alexander H; Natour, Ehsan; Prakken, Niek H J; Borra, Ronald J H; van Geel, Peter Paul; Slart, Riemer H J A; van Assen, Sander; Sinha, Bhanu

2017-01-01

Sensitivity and specificity of the modified Duke criteria for native valve endocarditis are both suboptimal, at approximately 80%. Diagnostic accuracy for intracardiac prosthetic material-related infection is even lower. Non-invasive imaging modalities could potentially improve diagnosis of infective endocarditis; however, their diagnostic value is unclear. We did a systematic literature review to critically appraise the evidence for the diagnostic performance of these imaging modalities, according to PRISMA and GRADE criteria. We searched PubMed, Embase, and Cochrane databases. 31 studies were included that presented original data on the performance of electrocardiogram (ECG)-gated multidetector CT angiography (MDCTA), ECG-gated MRI, 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT, and leucocyte scintigraphy in diagnosis of native valve endocarditis, intracardiac prosthetic material-related infection, and extracardiac foci in adults. We consistently found positive albeit weak evidence for the diagnostic benefit of 18 F-FDG PET/CT and MDCTA. We conclude that additional imaging techniques should be considered if infective endocarditis is suspected. We propose an evidence-based diagnostic work-up for infective endocarditis including these non-invasive techniques. Copyright © 2017 Elsevier Ltd. All rights reserved.

A novel highly parallel algorithm for linearly unmixing hyperspectral images

Science.gov (United States)

Guerra, Raúl; López, Sebastián.; Callico, Gustavo M.; López, Jose F.; Sarmiento, Roberto

2014-10-01

Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operations involved in these time-consuming processes. This work proposes an algorithm to estimate the endmembers of a hyperspectral image under analysis and its abundances at the same time. The main advantage of this algorithm is its high parallelization degree and the mathematical simplicity of the operations implemented. This algorithm estimates the endmembers as virtual pixels. In particular, the proposed algorithm performs the descent gradient method to iteratively refine the endmembers and the abundances, reducing the mean square error, according with the linear unmixing model. Some mathematical restrictions must be added so the method converges in a unique and realistic solution. According with the algorithm nature, these restrictions can be easily implemented. The results obtained with synthetic images demonstrate the well behavior of the algorithm proposed. Moreover, the results obtained with the well-known Cuprite dataset also corroborate the benefits of our proposal.

Image quality - physical and diagnostic parameters. The radiologist's viewpoint

International Nuclear Information System (INIS)

Stender, H.St.

1985-01-01

The quality of a radiograph is determined by the diagnostic information it provides. This depends upon the visual detection of diagnostically relevant structures. The technical radiographic requirements are dependent upon the physical measurements and the physiological and optical conditions. Such physical factors as spatial resolution, contrast and noise are quantitative measurements, which must be oriented to the qualitative visual characteristics of the radiograph. The influence of subjective perception and complexity of structural noise on the detectability of details and structures particularly demands attention. Since radiographic quality depends upon the detection of diagnostically relevant structure and features, it is important to define these parameters on the basis of extensive radiographic analysis and the corresponding clinical findings. The diagnostically relevant radiographic parameters and image details and critical structures have been worked out for the examination of the lungs, colon, stomach, urinary tract and skeleton. Good image quality requires coordination of the physical-technical parameters with the visual ability of the observer, since only in this way can the diagnostic information be represented with sufficient clarity. (author)

Algorithms imaging tests comparison following the first febrile urinary tract infection in children.

Science.gov (United States)

Tombesi, María M; Alconcher, Laura F; Lucarelli, Lucas; Ciccioli, Agustina

2017-08-01

To compare the diagnostic sensitivity, costs and radiation doses of imaging tests algorithms developed by the Argentine Society of Pediatrics in 2003 and 2015, against British and American guidelines after the first febrile urinary tract infection (UTI). Inclusion criteria: children ≤ 2 years old with their first febrile UTI and normal ultrasound, voiding cystourethrography and dimercaptosuccinic acid scintigraphy, according to the algorithm established by the Argentine Society of Pediatrics in 2003, treated between 2003 and 2010. The comparisons between algorithms were carried out through retrospective simulation. Eighty (80) patients met the inclusion criteria; 51 (63%) had vesicoureteral reflux (VUR); 6% of the cases were severe. Renal scarring was observed in 6 patients (7.5%). Cost: ARS 404,000. Radiation: 160 millisieverts. With the Argentine Society of Pediatrics' algorithm developed in 2015, the diagnosis of 4 VURs and 2 cases of renal scarring would have been missed. The cost of this omission would have been ARS 301,800 and 124 millisieverts of radiation. British and American guidelines would have missed the diagnosis of all VURs and all cases of renal scarring, with a related cost of ARS 23,000 and ARS 40,000, respectively and 0 radiation. Intensive protocols are highly sensitive to VUR and renal scarring, but they imply high costs and doses of radiation, and result in questionable benefits. Sociedad Argentina de Pediatría

Motion tolerant iterative reconstruction algorithm for cone-beam helical CT imaging

Energy Technology Data Exchange (ETDEWEB)

Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu [Hitachi Medical Corporation, Chiba-ken (Japan). CT System Div.

2011-07-01

We have developed a new advanced iterative reconstruction algorithm for cone-beam helical CT. The features of this algorithm are: (a) it uses separable paraboloidal surrogate (SPS) technique as a foundation for reconstruction to reduce noise and cone-beam artifact, (b) it uses a view weight in the back-projection process to reduce motion artifact. To confirm the improvement of our proposed algorithm over other existing algorithm, such as Feldkamp-Davis-Kress (FDK) or SPS algorithm, we compared the motion artifact reduction, image noise reduction (standard deviation of CT number), and cone-beam artifact reduction on simulated and clinical data set. Our results demonstrate that the proposed algorithm dramatically reduces motion artifacts compared with the SPS algorithm, and decreases image noise compared with the FDK algorithm. In addition, the proposed algorithm potentially improves time resolution of iterative reconstruction. (orig.)

Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding

Directory of Open Access Journals (Sweden)

Yongjian Nian

2013-01-01

Full Text Available A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC is proposed in this paper. The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression. Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information. Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression. Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate. Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.

Diagnostic imaging of the pancreas

International Nuclear Information System (INIS)

Araki, Tsutomu; Itai, Yuji

1981-01-01

Diagnostic imaging of the pancreas, ultrasonography (US), computed tomography (CT), radionuclide (RN) scintigraphy, angiography, and endoscopic retrograde pancreaticography (ERP). First three noninvasive methods, were the most effective to diagnose psudo-cyst or cystoadenoma. Especially, CT gives the clear image of inflammation and shows pancreatic stones and calcification, with high sensitivity. As for pancreatic carcinomas there was no noninvasive methods to apply at an early stage. In order to diagnose the cancer the combination of angiography and ERP was preferable. The problem was how to select the candidates for the investigation of combined method out of the patients with negative CT or US. (Tsunoda, M.)

High-speed computation of the EM algorithm for PET image reconstruction

International Nuclear Information System (INIS)

Rajan, K.; Patnaik, L.M.; Ramakrishna, J.

1994-01-01

The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution backprojection algorithms. However, two major drawbacks have impeded the routine use of the EM algorithm, namely, the long computational time due to slow convergence and the large memory required for the storage of the image, projection data and the probability matrix. In this study, the authors attempts to solve these two problems by parallelizing the EM algorithm on a multiprocessor system. The authors have implemented an extended hypercube (EH) architecture for the high-speed computation of the EM algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs). The authors discuss and compare the performance of the EM algorithm on a 386/387 machine, CD 4360 mainframe, and on the EH system. The results show that the computational speed performance of an EH using DSP chips as PEs executing the EM image reconstruction algorithm is about 130 times better than that of the CD 4360 mainframe. The EH topology is expandable with more number of PEs

Image processing and computer controls for video profile diagnostic system in the ground test accelerator (GTA)

International Nuclear Information System (INIS)

Wright, R.; Zander, M.; Brown, S.; Sandoval, D.; Gilpatrick, D.; Gibson, H.

1992-01-01

This paper describes the application of video image processing to beam profile measurements on the Ground Test Accelerator (GTA). A diagnostic was needed to measure beam profiles in the intermediate matching section (IMS) between the radio-frequency quadrupole (RFQ) and the drift tube linac (DTL). Beam profiles are measured by injecting puffs of gas into the beam. The light emitted from the beam-gas interaction is captured and processed by a video image processing system, generating the beam profile data. A general purpose, modular and flexible video image processing system, imagetool, was used for the GTA image profile measurement. The development of both software and hardware for imagetool and its integration with the GTA control system (GTACS) is discussed. The software includes specialized algorithms for analyzing data and calibrating the system. The underlying design philosophy of imagetool was tested by the experience of building and using the system, pointing the way for future improvements. (Author) (3 figs., 4 refs.)

IMPLANT-ASSOCIATED PATHOLOGY: AN ALGORITHM FOR IDENTIFYING PARTICLES IN HISTOPATHOLOGIC SYNOVIALIS/SLIM DIAGNOSTICS

Directory of Open Access Journals (Sweden)

V. Krenn

2014-01-01

Full Text Available In histopathologic SLIM diagnostic (synovial-like interface membrane, SLIM apart from diagnosing periprosthetic infection particle identification has an important role to play. The differences in particle pathogenesis and variability of materials in endoprosthetics explain the particle heterogeneity that hampers the diagnostic identification of particles. For this reason, a histopathological particle algorithm has been developed. With minimal methodical complexity this histopathological particle algorithm offers a guide to prosthesis material-particle identification. Light microscopic-morphological as well as enzyme-histochemical characteristics and polarization-optical proporties have set and particles are defined by size (microparticles, macroparticles and supra- macroparticles and definitely characterized in accordance with a dichotomous principle. Based on these criteria, identification and validation of the particles was carried out in 120 joint endoprosthesis pathological cases. A histopathological particle score (HPS is proposed that summarizes the most important information for the orthopedist, material scientist and histopathologist concerning particle identification in the SLIM.

Microwave imaging for plasma diagnostics and its applications

International Nuclear Information System (INIS)

Mase, A.; Kogi, Y.; Ito, N.

2007-01-01

Microwave to millimeter-wave diagnostic techniques such as interferometry, reflectometry, scattering, and radiometry have been powerful tools for diagnosing magnetically confined plasmas. Important plasma parameters were measured to clarify the physics issues such as stability, wave phenomena, and fluctuation-induced transport. Recent advances in microwave and millimeter-wave technology together with computer technology have enabled the development of advanced diagnostics for visualization of 2D and 3D structures of plasmas. Microwave/millimeter-wave imaging is expected to be one of the most promising diagnostic methods for this purpose. We report here on the representative microwave diagnostics and their industrial applications as well as application to magnetically-confined plasmas. (author)

Primary ureteral carcinoma: MRI diagnosis and comparison with other diagnostic imaging facilities

International Nuclear Information System (INIS)

An Ningyu; Jiang Bo; Cai Youquan; Liang Yan

2004-01-01

Objective: To investigate MRI examination methods and imaging manifestations of primary ureteral carcinoma, and to evaluate its clinical values when comparing with other diagnostic imaging facilities. Methods: Eighty-seven cases of primary ureteral carcinoma who were operated within recent 8 years came into the study, among which, 35 cases had MRI examinations. For MRI examination, coronal heavy T 2 WI (water imaging) was performed to show the dilated ureter, then axial T 2 WI and T 1 WI were scanned at the obstruction level. 11 cases underwent additional Gd-DTPA dynamic contrast enhanced scans. The original pre-operative diagnostic reports of various imaging facilities were analyzed comparing with the results of operation and pathology. Results: MRI showed ureteral dilatation in 33 of 35 cases, no abnormal appearance in 1 case, and only primary kidney atrophy post renal transplantation in 1 case. Among the 33 cases with ureteral obstruction, soft mass at the obstruction level was detected on axial scans in 32 cases. The lesions showed gradual and homogeneous mild to moderate enhancement on contrast MRI. The overall employment rate of imaging facilities was as follows: ultrasound (94.3%), IVU (59.8%), CT (52.9%), MRI (40.2%), and RUP (35.6%). The accurate diagnostic rate was as follows :MRI (91.4%), RUP (80.6%), CT (63.0%), ultrasound (47.6%), and IVU (11.5%). Conclusion: Combination of MR water imaging and conventional sequences can demonstrate most primary ureteral carcinoma lesions and has a highest diagnostic accuracy among the current diagnostic imaging facilities. It should be taken as the first diagnostic imaging method of choice when primary ureteral carcinoma is suspected after ultrasound screening

Hypercube algorithms suitable for image understanding in uncertain environments

International Nuclear Information System (INIS)

Huntsberger, T.L.; Sengupta, A.

1988-01-01

Computer vision in a dynamic environment needs to be fast and able to tolerate incomplete or uncertain intermediate results. An appropriately chose representation coupled with a parallel architecture addresses both concerns. The wide range of numerical and symbolic processing needed for robust computer vision can only be achieved through a blend of SIMD and MIMD processing techniques. The 1024 element hypercube architecture has these capabilities, and was chosen as the test-bed hardware for development of highly parallel computer vision algorithms. This paper presents and analyzes parallel algorithms for color image segmentation and edge detection. These algorithms are part of a recently developed computer vision system which uses multiple valued logic to represent uncertainty in the imaging process and in intermediate results. Algorithms for the extraction of three dimensional properties of objects using dynamic scene analysis techniques within the same framework are examined. Results from experimental studies using a 1024 element hypercube implementation of the algorithm as applied to a series of natural scenes are reported

Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm

International Nuclear Information System (INIS)

Zhou Xiaolin; Yun Mingkai; Cao Xuexiang; Liu Shuangquan; Wang Lu; Huang Xianchao; Wei Long

2014-01-01

Single-photon emission computerized tomography and positron emission tomography are essential medical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different acquisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose. (authors)

Diagnostic imaging of compression neuropathy

International Nuclear Information System (INIS)

Weishaupt, D.; Andreisek, G.

2007-01-01

Compression-induced neuropathy of peripheral nerves can cause severe pain of the foot and ankle. Early diagnosis is important to institute prompt treatment and to minimize potential injury. Although clinical examination combined with electrophysiological studies remain the cornerstone of the diagnostic work-up, in certain cases, imaging may provide key information with regard to the exact anatomic location of the lesion or aid in narrowing the differential diagnosis. In other patients with peripheral neuropathies of the foot and ankle, imaging may establish the etiology of the condition and provide information crucial for management and/or surgical planning. MR imaging and ultrasound provide direct visualization of the nerve and surrounding abnormalities. Bony abnormalities contributing to nerve compression are best assessed by radiographs and CT. Knowledge of the anatomy, the etiology, typical clinical findings, and imaging features of peripheral neuropathies affecting the peripheral nerves of the foot and ankle will allow for a more confident diagnosis. (orig.) [de

Clustering Batik Images using Fuzzy C-Means Algorithm Based on Log-Average Luminance

Directory of Open Access Journals (Sweden)

Ahmad Sanmorino

2012-06-01

Full Text Available Batik is a fabric or clothes that are made ​​with a special staining technique called wax-resist dyeing and is one of the cultural heritage which has high artistic value. In order to improve the efficiency and give better semantic to the image, some researchers apply clustering algorithm for managing images before they can be retrieved. Image clustering is a process of grouping images based on their similarity. In this paper we attempt to provide an alternative method of grouping batik image using fuzzy c-means (FCM algorithm based on log-average luminance of the batik. FCM clustering algorithm is an algorithm that works using fuzzy models that allow all data from all cluster members are formed with different degrees of membership between 0 and 1. Log-average luminance (LAL is the average value of the lighting in an image. We can compare different image lighting from one image to another using LAL. From the experiments that have been made, it can be concluded that fuzzy c-means algorithm can be used for batik image clustering based on log-average luminance of each image possessed.

Does a Diagnostic Classification Algorithm Help to Predict the Course of Low Back Pain?

DEFF Research Database (Denmark)

Hartvigsen, Lisbeth; Kongsted, Alice; Vach, Werner

2018-01-01

). Objectives To investigate if a diagnostic classification algorithm is associated with activity limitation and LBP intensity at 2-week and 3-month follow up, and 1-year trajectories of LBP intensity, and if it improves prediction of outcome when added to a set of known predictors. Methods 934 consecutive......Study Design A prospective observational study. Background A diagnostic classification algorithm was developed by Petersen et al., consisting of 12 categories based on a standardized examination protocol with the primary purpose of identifying clinically homogeneous subgroups of low back pain (LBP...... adult patients, with new episodes of LBP, who were visiting chiropractic practices in primary care were categorized according to the Petersen classification. Outcomes were disability and pain intensity measured at 2 weeks and 3 months, and 1-year trajectories of LBP based on weekly responses to text...

A Fuzzy Homomorphic Algorithm for Image Enhancement | Nnolim ...

African Journals Online (AJOL)

The implementation and analysis of a novel Fuzzy Homomorphic image enhancement technique is presented. The technique combines the logarithmic transform with fuzzy membership functions to deliver an intuitive method of image enhancement. This algorithm reduces the computational complexity by eliminating the ...

Diagnostic radiology on multiple injured patients: interdisciplinary management

International Nuclear Information System (INIS)

Linsenmaier, U.; Pfeifer, K.J.; Kanz, K.G.; Mutschler, W.

2001-01-01

The presence of a radiologist within the admitting area of an emergency department and his capability as a member of the trauma team have a major impact on the role of diagnostic radiology in trauma care. The knowledge of clinical decision criteria, algorithms, and standards of patient care are essential for the acceptance within a trauma team. We present an interdisciplinary management concept of diagnostic radiology for trauma patients, which comprises basic diagnosis, organ diagnosis, radiological ABC, and algorithms of early clinical care. It is the result of a prospective study comprising over 2000 documented multiple injured patients. The radiologist on a trauma team should support trauma surgery and anesthesia in diagnostic and clinical work-up. The radiological ABC provides a structured approach for diagnostic imaging in all steps of the early clinical care of the multiple injured patient. Radiological ABC requires a reevaluation in cases of equivocal findings or difficulties in the clinical course. Direct communication of radiological findings with the trauma team enables quick clinical decisions. In addition, the radiologist can priority-oriented influence the therapy by using interventional procedures. The clinical radiologist is an active member of the interdisciplinary trauma team, not only providing diagnostic imaging but also participating in clinical decisions. (orig.) [de

Low-dose multiple-information retrieval algorithm for X-ray grating-based imaging

International Nuclear Information System (INIS)

Wang Zhentian; Huang Zhifeng; Chen Zhiqiang; Zhang Li; Jiang Xiaolei; Kang Kejun; Yin Hongxia; Wang Zhenchang; Stampanoni, Marco

2011-01-01

The present work proposes a low dose information retrieval algorithm for X-ray grating-based multiple-information imaging (GB-MII) method, which can retrieve the attenuation, refraction and scattering information of samples by only three images. This algorithm aims at reducing the exposure time and the doses delivered to the sample. The multiple-information retrieval problem in GB-MII is solved by transforming a nonlinear equations set to a linear equations and adopting the nature of the trigonometric functions. The proposed algorithm is validated by experiments both on conventional X-ray source and synchrotron X-ray source, and compared with the traditional multiple-image-based retrieval algorithm. The experimental results show that our algorithm is comparable with the traditional retrieval algorithm and especially suitable for high Signal-to-Noise system.

FPGA implementation of image dehazing algorithm for real time applications

Science.gov (United States)

Kumar, Rahul; Kaushik, Brajesh Kumar; Balasubramanian, R.

2017-09-01

Weather degradation such as haze, fog, mist, etc. severely reduces the effective range of visual surveillance. This degradation is a spatially varying phenomena, which makes this problem non trivial. Dehazing is an essential preprocessing stage in applications such as long range imaging, border security, intelligent transportation system, etc. However, these applications require low latency of the preprocessing block. In this work, single image dark channel prior algorithm is modified and implemented for fast processing with comparable visual quality of the restored image/video. Although conventional single image dark channel prior algorithm is computationally expensive, it yields impressive results. Moreover, a two stage image dehazing architecture is introduced, wherein, dark channel and airlight are estimated in the first stage. Whereas, transmission map and intensity restoration are computed in the next stages. The algorithm is implemented using Xilinx Vivado software and validated by using Xilinx zc702 development board, which contains an Artix7 equivalent Field Programmable Gate Array (FPGA) and ARM Cortex A9 dual core processor. Additionally, high definition multimedia interface (HDMI) has been incorporated for video feed and display purposes. The results show that the dehazing algorithm attains 29 frames per second for the image resolution of 1920x1080 which is suitable of real time applications. The design utilizes 9 18K_BRAM, 97 DSP_48, 6508 FFs and 8159 LUTs.

Color Image Encryption Algorithm Based on TD-ERCS System and Wavelet Neural Network

Directory of Open Access Journals (Sweden)

Kun Zhang

2015-01-01

Full Text Available In order to solve the security problem of transmission image across public networks, a new image encryption algorithm based on TD-ERCS system and wavelet neural network is proposed in this paper. According to the permutation process and the binary XOR operation from the chaotic series by producing TD-ERCS system and wavelet neural network, it can achieve image encryption. This encryption algorithm is a reversible algorithm, and it can achieve original image in the rule inverse process of encryption algorithm. Finally, through computer simulation, the experiment results show that the new chaotic encryption algorithm based on TD-ERCS system and wavelet neural network is valid and has higher security.

TRANSFORMATION ALGORITHM FOR IMAGES OBTAINED BY OMNIDIRECTIONAL CAMERAS

Directory of Open Access Journals (Sweden)

V. P. Lazarenko

2015-01-01

Full Text Available Omnidirectional optoelectronic systems find their application in areas where a wide viewing angle is critical. However, omnidirectional optoelectronic systems have a large distortion that makes their application more difficult. The paper compares the projection functions of traditional perspective lenses and omnidirectional wide angle fish-eye lenses with a viewing angle not less than 180°. This comparison proves that distortion models of omnidirectional cameras cannot be described as a deviation from the classic model of pinhole camera. To solve this problem, an algorithm for transforming omnidirectional images has been developed. The paper provides a brief comparison of the four calibration methods available in open source toolkits for omnidirectional optoelectronic systems. Geometrical projection model is given used for calibration of omnidirectional optical system. The algorithm consists of three basic steps. At the first step, we calculate he field of view of a virtual pinhole PTZ camera. This field of view is characterized by an array of 3D points in the object space. At the second step the array of corresponding pixels for these three-dimensional points is calculated. Then we make a calculation of the projection function that expresses the relation between a given 3D point in the object space and a corresponding pixel point. In this paper we use calibration procedure providing the projection function for calibrated instance of the camera. At the last step final image is formed pixel-by-pixel from the original omnidirectional image using calculated array of 3D points and projection function. The developed algorithm gives the possibility for obtaining an image for a part of the field of view of an omnidirectional optoelectronic system with the corrected distortion from the original omnidirectional image. The algorithm is designed for operation with the omnidirectional optoelectronic systems with both catadioptric and fish-eye lenses

Improving the diagnostic performance of lung scintigraphy in suspected pulmonary embolic disease

International Nuclear Information System (INIS)

Gleeson, F.V.; Turner, S.; Scarsbrook, A.F.

2006-01-01

Aim: to determine the effectiveness of a new imaging algorithm in the investigation of suspected pulmonary embolism (PE). Materials and methods: A new imaging algorithm for suspected PE was introduced following the installation of a multisection computed tomography (CT) machine at our institution. Before its installation, patients with suspected PE were evaluated with ventilation/perfusion (V/Q) scintigraphy. Subsequently, patients were triaged according to chest radiography (CR) and respiratory history to either lung scintigraphy or CT pulmonary angiography (CTPA). Patients with a normal CR and no history of lung disease were evaluated using perfusion (Q) scintigraphy [ventilation (V) scintigraphy was no longer performed]. Patients with an abnormal CR, asthma or chronic lung disease were evaluated using CTPA. All V/Q images in a continuous 3-year period before the introduction of the new imaging algorithm and all Q images performed in a 3-year period after its introduction were retrospectively reviewed. Imaging reports were categorized into normal, non-diagnostic (low or intermediate probability) or high probability for PE. Patients in the later group who subsequently underwent CTPA, were also reviewed. Results: After the policy change the percentage of normal scintigrams significantly increased (39 to 60%; p < 0.001). There was a non-significant increase in the percentage of high probability scintigrams (15 to 18%; p = 0.716). Overall the diagnostic yield of lung scintigraphy improved significantly (54 to 78%; p < 0.001). Conclusion: the diagnostic performance of lung scintigraphy can be improved by careful triage of patients to either Q scintigraphy or CTPA based on clinical history and CR findings. Q scintigraphy remains a valuable diagnostic test in the investigation of suspected PE in carefully selected patients

Linear array implementation of the EM algorithm for PET image reconstruction

International Nuclear Information System (INIS)

Rajan, K.; Patnaik, L.M.; Ramakrishna, J.

1995-01-01

The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution back projection algorithms. However, the PET image reconstruction based on the EM algorithm is computationally burdensome for today's single processor systems. In addition, a large memory is required for the storage of the image, projection data, and the probability matrix. Since the computations are easily divided into tasks executable in parallel, multiprocessor configurations are the ideal choice for fast execution of the EM algorithms. In tis study, the authors attempt to overcome these two problems by parallelizing the EM algorithm on a multiprocessor systems. The parallel EM algorithm on a linear array topology using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PE's) has been implemented. The performance of the EM algorithm on a 386/387 machine, IBM 6000 RISC workstation, and on the linear array system is discussed and compared. The results show that the computational speed performance of a linear array using 8 DSP chips as PE's executing the EM image reconstruction algorithm is about 15.5 times better than that of the IBM 6000 RISC workstation. The novelty of the scheme is its simplicity. The linear array topology is expandable with a larger number of PE's. The architecture is not dependant on the DSP chip chosen, and the substitution of the latest DSP chip is straightforward and could yield better speed performance

A novel algorithm for segmentation of brain MR images

International Nuclear Information System (INIS)

Sial, M.Y.; Yu, L.; Chowdhry, B.S.; Rajput, A.Q.K.; Bhatti, M.I.

2006-01-01

Accurate and fully automatic segmentation of brain from magnetic resonance (MR) scans is a challenging problem that has received an enormous amount of . attention lately. Many researchers have applied various techniques however a standard fuzzy c-means algorithm has produced better results compared to other methods. In this paper, we present a modified fuzzy c-means (FCM) based algorithm for segmentation of brain MR images. Our algorithm is formulated by modifying the objective function of the standard FCM and uses a special spread method to get a smooth and slow varying bias field This method has the advantage that it can be applied at an early stage in an automated data analysis before a tissue model is available. The results on MRI images show that this method provides better results compared to standard FCM algorithms. (author)

[EYECUBE as 3D multimedia imaging in macular diagnostics].

Science.gov (United States)

Hassenstein, Andrea; Scholz, F; Richard, G

2011-11-01

In the new generation of EYECUBE devices, the angiography image and the OCT are included in a 3D illustration as an integration. Other diagnostic procedures such as autofluorescence and ICG can also be correlated to the OCT. The aim was to precisely classify various two-dimensional findings in relation to each other. The new generation of OCT devices enables imaging with a low incidence of motion artefacts with very good fundus image quality - and with that, permits a largely automatic classification. The feature enabling the integration of the EYECUBE was further developed with new software, so that not only the topographic image (red-free, autofluorescence) can be correlated to the Cirrus OCT, but also all other findings gathered within the same time frame can be correlated to each other. These were brightened and projected onto the cube surface in a defined interval. The imaging procedures can be selected in a menu toolbar. Topographic volumetry OCT images can be overlayed. The practical application of the new method was tested on patients with macular disorders. By lightening up the results from various diagnostic procedures, it is possible of late to directly compare pathologies to each other and to the OCT results. In all patients (n = 45 eyes) with good single-image quality, the automated integration into the EYECUBE was possible (to a great extent). The application is not dependent on a certain type of device used in the procedures performed. The increasing level of precision in imaging procedures and the handling of large data volumes has led to the possibility of examining each macular diagnostics procedure from the comparative perspective: imaging (photo) with perfusion (FLA, ICG) and morphology (OCT). The exclusion of motion artefacts and the reliable scan position in the course of the imaging process increases the informative value of OCT. © Georg Thieme Verlag KG Stuttgart · New York.

FCM Clustering Algorithms for Segmentation of Brain MR Images

Directory of Open Access Journals (Sweden)

Yogita K. Dubey

2016-01-01

Full Text Available The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF, Gray Matter (GM, and White Matter (WM, has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed.

[Future perspectives for diagnostic imaging in urology: from anatomic and functional to molecular imaging].

Science.gov (United States)

Macis, Giuseppe; Di Giovanni, Silvia; Di Franco, Davide; Bonomo, Lorenzo

2013-01-01

The future approach of diagnostic imaging in urology follows the technological progress, which made the visualization of in vivo molecular processes possible. From anatomo-morphological diagnostic imaging and through functional imaging molecular radiology is reached. Based on molecular probes, imaging is aimed at assessing the in vivo molecular processes, their physiology and function at cellular level. The future imaging will investigate the complex tumor functioning as metabolism, aerobic glycolysis in particular, angiogenesis, cell proliferation, metastatic potential, hypoxia, apoptosis and receptors expressed by neoplastic cells. Methods for performing molecular radiology are CT, MRI, PET-CT, PET-MRI, SPECT and optical imaging. Molecular ultrasound combines technological advancement with targeted contrast media based on microbubbles, this allowing the selective registration of microbubble signal while that of stationary tissues is suppressed. An experimental study was carried out where the ultrasound molecular probe BR55 strictly bound to prostate tumor results in strong enhancement in the early phase after contrast, this contrast being maintained in the late phase. This late enhancement is markedly significant for the detection of prostatic cancer foci and to guide the biopsy sampling. The 124I-cG250 molecular antibody which is strictly linked to cellular carbonic anhydrase IX of clear cell renal carcinoma, allows the acquisition of diagnostic PET images of clear cell renal carcinoma without biopsy. This WG-250 (RENCAREX) antibody was used as a therapy in metastatic clear cell renal carcinoma. Future advancements and applications will result in early cancer diagnosis, personalized therapy that will be specific according to the molecular features of cancer and leading to the development of catheter-based multichannel molecular imaging devices for cystoscopy-based molecular imaging diagnosis and intervention.

Artificial intelligence as a diagnostic adjunct in cardiovascular nuclear imaging

International Nuclear Information System (INIS)

Duncan, J.S.

1988-01-01

The radiologist and/or nuclear medicine physician is literally bombarded with information from today's diagnostic imaging technologies. As a consequence of this, whereas a decade ago the emphasis in medical image analysis was on improving the extraction of diagnostic information by developing and using more sophisticated imaging modalities, today those working on the development of medical imaging technology are struggling to find ways to handle all gathered information effectively. This chapter gives an introduction to the area of artificial intelligence, with an emphasis on the research ongoing in cardiovascular nuclear imaging. This chapter has reviewed the place of artificial intelligence in cardiovascular nuclear imaging. It is intended to provide a general sense of this new and emerging field, an insight into some of its specific methodologies and applications, and a closer look at the several AI approaches currently being applied in cardiovascular nuclear imaging

A Modified Image Comparison Algorithm Using Histogram Features

OpenAIRE

Al-Oraiqat, Anas M.; Kostyukova, Natalya S.

2018-01-01

This article discuss the problem of color image content comparison. Particularly, methods of image content comparison are analyzed, restrictions of color histogram are described and a modified method of images content comparison is proposed. This method uses the color histograms and considers color locations. Testing and analyzing of based and modified algorithms are performed. The modified method shows 97% average precision for a collection containing about 700 images without loss of the adv...

Segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

Science.gov (United States)

Moradi, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

2011-10-01

Segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5×5 window size is better than the other windows.

Study on the algorithm of computational ghost imaging based on discrete fourier transform measurement matrix

Science.gov (United States)

Zhang, Leihong; Liang, Dong; Li, Bei; Kang, Yi; Pan, Zilan; Zhang, Dawei; Gao, Xiumin; Ma, Xiuhua

2016-07-01

On the basis of analyzing the cosine light field with determined analytic expression and the pseudo-inverse method, the object is illuminated by a presetting light field with a determined discrete Fourier transform measurement matrix, and the object image is reconstructed by the pseudo-inverse method. The analytic expression of the algorithm of computational ghost imaging based on discrete Fourier transform measurement matrix is deduced theoretically, and compared with the algorithm of compressive computational ghost imaging based on random measurement matrix. The reconstruction process and the reconstruction error are analyzed. On this basis, the simulation is done to verify the theoretical analysis. When the sampling measurement number is similar to the number of object pixel, the rank of discrete Fourier transform matrix is the same as the one of the random measurement matrix, the PSNR of the reconstruction image of FGI algorithm and PGI algorithm are similar, the reconstruction error of the traditional CGI algorithm is lower than that of reconstruction image based on FGI algorithm and PGI algorithm. As the decreasing of the number of sampling measurement, the PSNR of reconstruction image based on FGI algorithm decreases slowly, and the PSNR of reconstruction image based on PGI algorithm and CGI algorithm decreases sharply. The reconstruction time of FGI algorithm is lower than that of other algorithms and is not affected by the number of sampling measurement. The FGI algorithm can effectively filter out the random white noise through a low-pass filter and realize the reconstruction denoising which has a higher denoising capability than that of the CGI algorithm. The FGI algorithm can improve the reconstruction accuracy and the reconstruction speed of computational ghost imaging.

Iterative Object Localization Algorithm Using Visual Images with a Reference Coordinate

Directory of Open Access Journals (Sweden)

We-Duke Cho

2008-09-01

Full Text Available We present a simplified algorithm for localizing an object using multiple visual images that are obtained from widely used digital imaging devices. We use a parallel projection model which supports both zooming and panning of the imaging devices. Our proposed algorithm is based on a virtual viewable plane for creating a relationship between an object position and a reference coordinate. The reference point is obtained from a rough estimate which may be obtained from the preestimation process. The algorithm minimizes localization error through the iterative process with relatively low-computational complexity. In addition, nonlinearity distortion of the digital image devices is compensated during the iterative process. Finally, the performances of several scenarios are evaluated and analyzed in both indoor and outdoor environments.

Automatic volumetry on MR brain images can support diagnostic decision making

Directory of Open Access Journals (Sweden)

Aviv Richard I

2008-05-01

Full Text Available Abstract Background Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients' MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing. Methods A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence. Results The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers' diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p Conclusion Volumetric anatomical information extracted from brain

How far can the radiation dose be lowered in head CT with iterative reconstruction? Analysis of imaging quality and diagnostic accuracy

Energy Technology Data Exchange (ETDEWEB)

Wu, Tung-Hsin; Sun, Jing-Yi [National Yang-Ming University, Department of Biomedical Imaging and Radiological Sciences, Taipei (China); Hung, Sheng-Che; Lin, Chung-Jung; Chiu, Chen Fen; Liu, Min-Jsuan; Teng, Michael Mu Huo; Guo, Wan-Yuo; Chang, Cheng-Yen [Taipei Veterans General Hospital, Department of Radiology, Taipei (China); National Yang-Ming University, School of Medicine, Taipei (China); Lin, Chung-Hsien [National Taiwan University, Graduate Institute of Epidemiology and Preventive Medicine, Taipei (China)

2013-09-15

To evaluate the imaging quality of head CT at lowered radiation dose by combining filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Experimental group A (n = 66) underwent CT with 43 % tube current reduction, and group B (n = 58) received an equivalent reduced dose by lowering the tube voltage. An age- and sex-matched control group (n = 72) receiving the conventional radiation dose was retrospectively collected. Imaging for the control group was reconstructed by FBP only, while images for groups A and B were reconstructed by FBP and IR. The signal-to-noise ratios (SNRs), contrast-to-noise ratios (CNRs), sharpness, number of infarcts and severity of subcortical arteriosclerotic encephalopathy (SAE) were compared to assess imaging quality and diagnostic accuracy. There were no significant differences in SNRs and CNRs between group A and the control group. There were significantly decreased SNRs and increased CNRs in group B. Image sharpness decreased in both groups. Correlations between detected infarcts and severity of SAE across FBP and IR were high (r = 0.73-0.93). Head diameter was the only significant factor inversely correlated with infratentorial imaging quality. Head CT with 43 % reduced tube current reconstructed by IR provides diagnostic imaging quality for outpatient management. (orig.)

ProxImaL: efficient image optimization using proximal algorithms

KAUST Repository

Heide, Felix

2016-07-11

Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image processing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the image processing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.

[Radiological diagnostics in CUP syndrome].

Science.gov (United States)