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In vivo observation of cells in the Arabidopsis thaliana root, by time-lapse confocal microscopy, is central to biology research. The research herein described is based on large amount of image data, which must be analyzed to determine the location and state of individual cells. Automating the process of cell tracking is an important step to create tools which will facilitate the analysis of cellspsila...
Computed tomographic colonography (CTC) provides a feasible way for the detection of colorectal polyps and cancer screening. In the clinical practice of CTC, a true colonic polyp will be confirmed with high confidence if a radiologist can find it in both the supine and prone scans. To assist radiologists in CTC reading, we propose a new colonic polyp matching method based on statistical curvature...
Many features have been proposed for the detection of microcalcification clusters (MCCs) or classification of benign/malignant MCCs. However, most of them were designed based on the characteristics of MCC. In this paper, 16 features, which have been commonly adopted in many applications, are examined and six new features based on the linear structure are proposed. To evaluate the effectiveness of...
A mainstay in cancer diagnostics is the classification or grading of cell nuclei based on their appearance. While the analysis of cytological samples has been automated successfully for a long time, the complexity of histological tissue samples has prevented a reliable classification with machine vision techniques. We approach this complex problem in multiple stages, analyzing first image quality,...
In this paper we present the coupled active contours (CAC) model, which is applied to segmentation of the endocardium in ultrasonic images assuming Rayleigh distributed intensities. Comparative experiments, both real and synthetic, with a standard prior model are presented. In the CAC model the prior acts, by affine transformation, on the same image information as the active contour, in addition to...
We present an algorithm for the segmentation of the liver in 2-D computed tomography slice images. The basis for our algorithm is an implicit active shape model. In order to detect the liver boundary and guide the shape model deformation, a boundary classifier has been integrated into the implicit framework in a novel manner. The accuracy of the algorithm has been evaluated for 20 test cases including...
Cellular endocytosis is a mechanism of great interest in biology, for it regulates the communication between the cell and the external medium. With recent advances in fluorescence microscopy, endocytosis has become a popular candidate for image-based high content screening campains. In this context, we have developed an automated framework comprising robust cell segmentation using coupled shape-constrained...
A new deformable model called active b-snake model (ABM) is presented for object boundary extraction. First, an affine-invariant landmark point assignment strategy is proposed to avoid manually assign landmarks. Second, an adaptive control point insertion algorithm is used to enhance the flexibility of B-Snake to describe complex shape. Third, for modeling the shape distribution and appearance characteristics...
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