Papers by Georgy Gimel'farb
Medical Physics, 2013
The authors propose 3D (2D + time) novel, fast, robust, bidirectional coupled parametric deformab... more The authors propose 3D (2D + time) novel, fast, robust, bidirectional coupled parametric deformable models that are capable of segmenting left ventricle (LV) wall borders using first- and second-order visual appearance features. The authors examine the effect of the proposed segmentation method on the estimation of global cardiac performance indexes. First-order visual appearance of the cine cardiac magnetic resonance (CMR) signals (inside and outside the boundary of the deformable model) is modeled with an adaptive linear combination of discrete Gaussians (LCDG). Second-order visual appearance of the LV wall is accurately modeled with a translational and rotation-invariant second-order Markov-Gibbs random field (MGRF). The LCDG parameters are estimated using our previously proposed modification of the EM algorithm, and the potentials of rotationally invariant MGRF are computed analytically. The authors tested the proposed segmentation approach on 15 cine CMR data sets using the Dice similarity coefficient (DSC) and the average distance (AD) between the ground truth and automated segmentation contours. The authors documented an average DSC value of 0.926 ± 0.022 and an average AD value of 2.16 ± 0.60 mm compared to two other level set methods that achieve an average DSC values of 0.904 ± 0.033 and 0.885 ± 0.02; and an average AD values of 2.86 ± 1.35 mm and 5.72 ± 4.70 mm, respectively. The proposed segmentation approach demonstrated superior performance over other methods. Specifically, the comparative results on the publicly available MICCAI 2009 Cardiac MR Left Ventricle Segmentation database documented superior performance of the proposed approach over published methods. Additionally, the high accuracy of our segmentation approach leads to accurate estimation of the global performance indexes, as evidenced by the Bland-Altman analyses of the end-systolic volume (ESV), end-diastolic volume (EDV), and the ejection fraction (EF) ratio.
The 10th IEEE International Symposium on Signal Processing and Information Technology, 2010
Abstract Prostate segmentation is an essential step in developing any non-invasive Computer-Assis... more Abstract Prostate segmentation is an essential step in developing any non-invasive Computer-Assisted Diagnostic (CAD) system for the early diagnosis of prostate cancer using Magnetic Resonance Images (MRI). In this paper, we propose, a novel framework for 3D segmentation of the prostate region from Dynamic Contrast Enhancement Magnetic Resonance Images (DCE-MRI). The framework is based on a maximum aposteriori (MAP) estimate of a new log-likelihood function that consists of three descriptors:(i) 1 st-order ...
Computational Intelligence in Biomedical Imaging, 2013
ABSTRACT A novel non-invasive approach for the early diagnosis of prostate cancer from diffusion-... more ABSTRACT A novel non-invasive approach for the early diagnosis of prostate cancer from diffusion-weighted MRI is proposed. The proposed diagnostic approach consists of three main steps. The first step is to isolate the prostate from the surrounding anatomical structures based on a Maximum a Posteriori (MAP) estimate of a new log-likelihood function that accounts for the shape priori, the spatial interaction, and the current appearance of prostate tissues and its background (surrounding anatomical structures). In the second step, a nonrigid registration algorithm is employed to account for any local deformation between the segmented prostates at different b-values that could occur during the scanning process due to patient breathing and local motion. In the final step, a kn-Nearest Neighbor-based classifier is used to classify the prostate into benign or malignant based on four appearance features extracted from registered images. Moreover, in this paper we introduce a new approach to generate color maps that illustrate the propagation of diffusion in prostate tissues based on the analysis of the 3D spatial interaction of the change of the gray level values of prostate voxel using a Generalized Gauss-Markov Random Field (GGMRF) image model. Finally, the tumor boundaries are determined using a level set deformable model controlled by the diffusion information and the spatial interactions between the prostate voxels. Experimental results on 28 clinical diffusion-weighted MRI data sets yield promising results.
Medical Physics, 2013
The authors propose 3D (2D + time) novel, fast, robust, bidirectional coupled parametric deformab... more The authors propose 3D (2D + time) novel, fast, robust, bidirectional coupled parametric deformable models that are capable of segmenting left ventricle (LV) wall borders using first- and second-order visual appearance features. The authors examine the effect of the proposed segmentation method on the estimation of global cardiac performance indexes. First-order visual appearance of the cine cardiac magnetic resonance (CMR) signals (inside and outside the boundary of the deformable model) is modeled with an adaptive linear combination of discrete Gaussians (LCDG). Second-order visual appearance of the LV wall is accurately modeled with a translational and rotation-invariant second-order Markov-Gibbs random field (MGRF). The LCDG parameters are estimated using our previously proposed modification of the EM algorithm, and the potentials of rotationally invariant MGRF are computed analytically. The authors tested the proposed segmentation approach on 15 cine CMR data sets using the Dice similarity coefficient (DSC) and the average distance (AD) between the ground truth and automated segmentation contours. The authors documented an average DSC value of 0.926 ± 0.022 and an average AD value of 2.16 ± 0.60 mm compared to two other level set methods that achieve an average DSC values of 0.904 ± 0.033 and 0.885 ± 0.02; and an average AD values of 2.86 ± 1.35 mm and 5.72 ± 4.70 mm, respectively. The proposed segmentation approach demonstrated superior performance over other methods. Specifically, the comparative results on the publicly available MICCAI 2009 Cardiac MR Left Ventricle Segmentation database documented superior performance of the proposed approach over published methods. Additionally, the high accuracy of our segmentation approach leads to accurate estimation of the global performance indexes, as evidenced by the Bland-Altman analyses of the end-systolic volume (ESV), end-diastolic volume (EDV), and the ejection fraction (EF) ratio.
Abstract���We present a fully featured, web-based, online autostereogram creation system that all... more Abstract���We present a fully featured, web-based, online autostereogram creation system that allows a user to upload their own stereo images, generate depth data via computational stereo vision, and then turn this depth data into an autostereogram. The system can also perform the reverse process and extract depth data from a given autosteregram or generate anaglyphs from them.
The importance of accurate early diagnostics of autism that severely affects personal behavior an... more The importance of accurate early diagnostics of autism that severely affects personal behavior and communication skills cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the cerebral white matter (CWM) in autistic brains. We explore a possibility of distinguishing between autistic and normal brains by a quantitative shape analysis of CWM gyrifications on 3D proton density MRI (PD-MRI) images.
Abstract Using 2D images is one of the most common techniques for the reconstruction of 3D face m... more Abstract Using 2D images is one of the most common techniques for the reconstruction of 3D face models. In this paper, we compare the strengths and weaknesses of different image processing techniques for 3D face generation. It is anticipated that the optimal solution will be applied in the future for 3D face analysis and synthesis. This paper presents binocular stereo using stereo correspondence algorithm, binocular stereo using triangulation, orthogonal views, and photometric stereo as approaches to 3D face modeling.
Abstract The maximum entropy principle is a cornerstone of FRAME (filters, random fields, and max... more Abstract The maximum entropy principle is a cornerstone of FRAME (filters, random fields, and maximum entropy) model considered at times as a first-ever step towards a universal theory of texture modelling or even as" the inevitable texture model". This paper disputes such opinions. That a wealth of exponential families of probability distributions is deduced from the ME principle is well known for decades.
Designing parallel versions of sequential algorithms has attracted renewed attention, due to rece... more Designing parallel versions of sequential algorithms has attracted renewed attention, due to recent hardware advances, including various general-purpose multi-core and many-core processors, as well as special-purpose FPGA implementations. P systems consist of networks of autonomous cells, such that each cell transforms its input signals in accord with its symbol-rewriting rules and feeds the output results into its immediate neighbours.
Abstract���Virtual computational cloud (VCC) architecture is an attractive option for many resear... more Abstract���Virtual computational cloud (VCC) architecture is an attractive option for many researchers in computer vision due to its ability to access and manipulate very large repositories of images remotely. Often an integration of local and remote computational environments and image repositories is required as geographically dispersed collaborating teams do not have unrestricted access to image repositories due to timing, legal, ethical, architectural or bandwidth limitations.
Computer or machine vision pursues the goal of describing and understanding natural 3D scenes usi... more Computer or machine vision pursues the goal of describing and understanding natural 3D scenes using one or more 2D images. Vision guided control in industrial automation or robotics based on image acquisition and understanding but involves specific requirements such as (i) low cost,(ii) reliable operation,(iii) fundamental simplicity,(iv) real-time image analysis, and (v) easiness of scene illumination. These requirements are often diametrically opposed to many known computer vision results.
Abstract Stereo reconstruction is an ill-posed inverse optical problem that always has multiple s... more Abstract Stereo reconstruction is an ill-posed inverse optical problem that always has multiple solutions. To obtain a unique solution, it is typically regularised by combining-in an ad hoc linear combination-a few distinctly different criteria that evaluate deviations from exact similarity and constraints. The combination serves as a joint matching score to be minimized. However, the components weights are selected empirically and small variations dramatically affect the matching accuracy.
Abstract Dyslexia severely impairs learning abilities of children, so that improved diagnostic me... more Abstract Dyslexia severely impairs learning abilities of children, so that improved diagnostic methods are needed. Neuropathological studies have revealed an abnormal anatomy of the Corpus Callosum (CC) in dyslexic brains. We propose a new approach to quantitative analysis of three-dimensional (3D) magnetic resonance images (MRI) of the brain that ensures a more accurate quantification of anatomical differences between the CC of dyslexic and normal subjects.
ABSTRACT A new approach to align an image of a textured object with a given prototype is proposed... more ABSTRACT A new approach to align an image of a textured object with a given prototype is proposed. Visual appearance of the images, after equalizing their signals, is modeled with a Markov-Gibbs random field with pairwise interaction. Similarity to the prototype is measured by a Gibbs energy of signal co-occurrences in a characteristic subset of pixel pairs derived automatically from the prototype. An object is aligned by an affine transformation maximizing the similarity by using an automatic initialization followed by gradient search.
A more accurate identification (estimation of parameters) of simple Markov-Gibbs random field mod... more A more accurate identification (estimation of parameters) of simple Markov-Gibbs random field models of images results in a better segmentation of specific multimodal images and realistic synthesis of some types of natural textures. Identification algorithms for segmentation are based in part on a novel modification of an unsupervised learning algorithm published first in ���Cybernetics and Systems Analysis���(���Kibernetika i Sistemnyi Analiz���) almost four decades ago.
Abstract A recently proposed multi parametric quadratic programming (QP) based approach to image ... more Abstract A recently proposed multi parametric quadratic programming (QP) based approach to image matching under complex photometric variations has shown quite an improvement over other state-of-the-art algorithms. However, it is not an entirely satisfactory solution for many practical applications as it does not account for geometric dissimilarities between the images. We extend the QP-based method and propose a new method for robust rigid image registration under both photometric and geometric deviations.
Abstract Automatic detection of lung nodules is an important problem in computer analysis of ches... more Abstract Automatic detection of lung nodules is an important problem in computer analysis of chest radiographs. In this paper, we propose a novel algorithm for isolating lung abnormalities (nodules) from spiral chest low-dose CT (LDCT) scans. The proposed algorithm consists of three main steps. The first step isolates the lung nodules, arteries, veins, bronchi, and bronchioles from the surrounding anatomical structures.
Abstract We have improved our concurrent stereo matching (CSM) algorithm, which abandons the sear... more Abstract We have improved our concurrent stereo matching (CSM) algorithm, which abandons the search for'best'matches and determine matches that lie within admissible ranges using a noise model. We estimate photometric deviations between corresponding regions of stereo pairs with photometric transformations and mismatched or occluded regions. We allow for global, disparity dependent contrast and offset (gain and dark noise) distortions as well as multiple outliers.
Abstract The importance of accurate early diagnostics of autism that severely affects personal be... more Abstract The importance of accurate early diagnostics of autism that severely affects personal behavior and communication skills cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the Corpus Callosum (CC) in autistic brains. We propose a new approach to quantitative analysis of three-dimensional (3D) magnetic resonance images (MRI) of the brain that ensures a more accurate quantification of anatomical differences between the CC of autistic and normal subjects.
A promising approach for the automatic classification of normal and acute rejection transplants f... more A promising approach for the automatic classification of normal and acute rejection transplants from Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is proposed. The proposed approach consists of three main steps.
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Papers by Georgy Gimel'farb