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We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization...
Cell image segmentation is the base of further medicinal analysis, and the quality of segmentation has a great influence on cell identify and analyzing. Although there are many segmentation algorithms on recent papers, it is difficult to find one that can be applicable to general cases, and the adhesive cell will affect the cell analysis. So this paper developed a cell image segmentation method using...
We present a computational framework to identify prostate specific cancer biomarkers using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data collected at the Eastern Virginia Medical School (EVMS). Protein profiles of a tumor and its surrounding area from one prostate tissue sample were analyzed. The data contain 974 spectra (27 cancer, 947 normal). We proposed...
In this paper, a hybrid method for the segmentation of medical ultrasound images is proposed. The method is composed of two parts as region growing and region merging. First, we initially segment the images into many small regions using a region growing method. The region growing algorithm is based on some pixels we specially choose as growing centers. The initially segmented images acquired from...
Traditionally, the gradient magnitude of an image pixel was the only feature in various image edge detection methods. However, this feature does not have good performance in noisy and low-contrast conditions, such as medical ultrasound images. A new edge detection feature, based on two brightness change direction angles difference (DAD) of one pixel in two different calculation methods, is proposed...
While CT colonography (CTC) is becoming a more prevalent and accepted method to diagnose colon cancer, the leading cause of nondiagnostic segmental evaluation of CT colonography is colonic diverticular disease (CDD). An essential element of detecting CDD in conjunction with CT colonography (CTC) is the accurate segmentation of the colonic wall. We have developed a level set based method to determine...
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