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This paper presents an algorithm to classify pixels in uterine cervix images into two classes, namely normal and abnormal tissues, and simultaneously select relevant features, using group sparsity. Because of the large variations in image appearance due to changes of illumination, specular reflections and other visual noise, the two classes have a strong overlap in feature space, whether features...
In this work, we introduce a computational approach that automatically detects stained follicles in IHC-stained follicular lymphoma slides using various biomarkers. This novel approach is to process whole-slide and Giga-byte scaled pathology images at multi-resolution levels. The average segmentation accuracy achieves at 83.09±6.25%. Such a computerized analysis of images is expected to provide a...
Generalized cylinder shapes are ubiquitous in biological systems and image processing techniques to identifies these tubular objects in 3D from biomedical imagery in various modalities is a general problem of interest. One such structure that exhibits branching tubular forms are neuronal networks; specifically, recent developments in microscopy imaging technology allow researchers to acquire massive...
Tongue inspection is one of the most important methods of Traditional Chinese Medicine diagnoses. Traditional tongue inspection mainly depends on observations to tongue substance, tongue coating and tongue pattern and diagnostic experience of the doctors. Diagnostic results are restricted by doctor's knowledge level, their experience as well as other subjective factors and affected by the light and...
The goal of this project is to develop an automated computer vision system to acquire and analyze images of adherent cell cultures. These cultures are involved in the establishment of a cell therapy protocol using primary cells. Cultures are stained to facilitate the image segmentation based on color information. Nevertheless, the high density and the uneven dispersion of cells favor nuclei clustering...
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