Combining Independent Component Analysis and Self-Organizing Maps for Cell Image Classification
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Multivariate image analysis in biomedicine
Journal of Biomedical Informatics
Multiclass cell detection in bright field images of cell mixtures with ECOC probability estimation
Image and Vision Computing
Spermatogonium image recognition using Zernike moments
Computer Methods and Programs in Biomedicine
Data & Knowledge Engineering
Computers in Biology and Medicine
Learning compatibility functions for feature binding and perceptual grouping
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Cell segmentation, tracking, and mitosis detection using temporal context
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Automatic recognition of five types of white blood cells in peripheral blood
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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A neural cell detection system (NCDS) for the automatic quantitation of fluorescent lymphocytes in tissue sections is presented in this paper. The system acquires visual knowledge from a set of training cell-image patches selected by a user. The trained system evaluates an image in 2 min calculating: the number, the positions, and the phenotypes of the fluorescent cells. For validation, the NCDS learning performance was tested by cross validation on digitized images of tissue sections obtained from inherently different types of tissue: diagnostic tissue sections across the human tonsil and across an inflammatory lymphocyte infiltrate of the human skeletal muscle. The NCDS detection results were compared with detection results from biomedical experts and were visually evaluated by our most experienced biomedical expert. Although the micrographs were noisy and the fluorescent cells varied in shape and size, the NCDS detected a minimum of 95% of the cells. In contrast, the cellular counts based on visual cell recognition of the experts were inconsistent and largely unreproducible for approximately 80% of the lymphocytes present in a visual field.