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In this paper, we propose a Markov random field based method that uses saliency and gradient information for elastic registration of dynamic contrast enhanced (DCE) magnetic resonance (MR) images of the heart. DCE-MR images are characterized by rapid intensity changes over time, thus posing challenges for conventional intensity-based registration methods. Saliency information contributes to a contrast...
Phase unwrapping is an important and challenging problem in phase contrast magnetic resonance imaging (PC-MRI). In this paper, we propose a new algorithm for phase unwrapping based on graph cuts. Our algorithm takes a patch-based approach which has the advantages of simplicity and robustness to phase noise. To make use of temporal information from the neighboring frames as well as spatial information...
Cataract is the leading cause of blindness and posterior subcapsular cataract (PSC) leads to significant visual impairment. An automatic approach for detecting PSC opacity in retro-illumination images is investigated. The features employed include intensity, edge, size and spatial location. The system was tested using 441 images. The automatic detection was compared with the human expert. The sensitivity...
Glaucoma is the second leading cause of blindness. Glaucoma can be diagnosed through measurement of neuro-retinal optic cup-to-disc ratio (CDR). Automatic calculation of optic cup boundary is challenging due to the interweavement of blood vessels with the surrounding tissues around the cup. A Convex Hull based Neuro-Retinal Optic Cup Ellipse Optimization algorithm improves the accuracy of the boundary...
In this paper, we propose a data-driven approach that extracts prior information for segmentation of the left ventricle in cardiac MR images of transplanted rat hearts. In our approach, probabilistic priors are generated from prominent features, i.e., corner points and scale-invariant edges, for both endo- and epi-cardium segmentation. We adopt a level set formulation that integrates probabilistic...
This paper presents a semi-automated segmentation method for short-axis cardiac CT and MR images. The main contributions of this work are: (1) using two different energy functionals for endocardium and epicardium segmentation to account for their distinctive characteristics; (2) proposing a dual-background model that is suitable for representing intensity distributions of the background in epicardium...
Computer aided analysis of medical images, a unique type of non-text media, can facilitate clinical diagnosis. As an example, an automatic opacity detection approach is proposed in this paper to grade cortical cataract more objectively. The automatic pupil detection is performed by detecting the strongest edges on the convex hull and ellipse fitting using nonlinear least square method. The cortical...
In this paper we propose the use of a neurobiology-based saliency measure to improve the performance of a quantitative- qualitative measure of mutual information for rigid registration of 4D renal perfusion MR images. Our registration method assigns greater importance to more salient voxels by applying a soft thresholding function to normalized saliency values. The resulting saliency map is a better...
Feature extraction techniques in the ultrasonic images of a liver were studied firstly. As an initial result, total 25 parameters relating to cirrhosis were extracted. They were obtained from the motion curve of the liver in an M-mode image, and from the texture using a B-mode image. Then the efficiency of every parameter was analyzed, and with the use of a feature fusion method a set of 20 useful...
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