Papers by Youssry El-Zehiry
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012
Vascular diseases are among the most important health problems. Vessel segmentation is a very cri... more Vascular diseases are among the most important health problems. Vessel segmentation is a very critical task for stenosis measurement and simulation, diagnosis and treatment planning. However, vessel segmentation is much more challenging than blob-like object segmentation due to the thin elongated anatomy of the blood vessels, which can easily appear disconnected in the acquired images due to noise and occlusion. In this paper, we present a generic vessel segmentation approach that extracts the vessels by globally minimizing the surface curvature. The low curvature model enforces surface continuity and prevents the formation of false positives (leakages) and false negatives (holes). We present two contributions: First, we introduce a generic 3D vessel segmentation model by penalizing the boundary surface curvature. Second, we introduce an attraction force as a generalization of the boundary length in the elastica model, which guarantees a complete global solution and avoids shrinkage bias of length regularization. Our results will illustrate that the approach works efficiently across different acquisition modalities and for different applications.
Data driven editing of RIB centerlines
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 2014
International Journal of Computer Vision, 2013
The Mumford-Shah model has been one of the most influential models in image segmentation and deno... more The Mumford-Shah model has been one of the most influential models in image segmentation and denoising. The optimization of the multiphase Mumford-Shah energy functional has been performed using level sets methods that optimize the Mumford-Shah energy by evolving the level sets via the gradient descent. These methods are very slow and prone to getting stuck in local optima due to the use of gradient descent. After the reformulation of the 2-phase Mumford-Shah functional on a graph, several groups investigated the hierarchical extension of the graph representation to multi class. The discrete hierarchical approaches are more effective than hierarchical (or direct) multiphase formulation using level sets. However, they provide approximate solutions and can diverge away from the optimal solution. In this paper, we present a discrete alternating optimization for the discretized Vese-Chan approximation of the piecewise constant multiphase Mumford-Shah functional that directly minimizes the multiphase functional without recursive bisection on the labels. Our approach handles the nonsubmodularity of the multiphase energy function and provides a global optimum if the image estimation data term is known apriori.
Fast global optimization of curvature
ABSTRACT Two challenges in computer vision are to accommodate noisy data and missing data. Many p... more ABSTRACT Two challenges in computer vision are to accommodate noisy data and missing data. Many problems in computer vision, such as segmentation, filtering, stereo, reconstruction, inpainting and optical flow seek solutions that match the data while satisfying an additional regularization, such as total variation or boundary length. A regularization which has received less attention is to minimize the curvature of the solution. One reason why this regularization has received less attention is due to the difficulty in finding an optimal solution to this image model, since many existing methods are complicated, slow and/or provide a suboptimal solution. Following the recent progress of Schoenemann et al., we provide a simple formulation of curvature regularization which admits a fast optimization which gives globally optimal solutions in practice. We demonstrate the effectiveness of this method by applying this curvature regularization to image segmentation.
This paper presents the study of vocal videostroboscopic videos to detect morphological pathologi... more This paper presents the study of vocal videostroboscopic videos to detect morphological pathologies using an active contour segmentation and objective measurements. The ad-hoc designed active contour algorithm permits to obtain a robust and fast segmentation using vocal folds images in RGB format. In this work, we have employed connected component analysis as a post-processing tool. After the segmentation process the image is analyzed and the pathology can be localized automatically and we can extract some features of each fold (such as the size of the polyp or cyst, the glottal space, the position…). Experimental results demonstrate that the proposed method is effective. Our proposal segments correctly the 95% of database test videos and it shows a great advance in design. The objective measurements complete a new method to diagnose vocal folds pathologies.
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Papers by Youssry El-Zehiry