Homologue classification of human chromosome images using an iterative centromere segmentation algorithm

TitleHomologue classification of human chromosome images using an iterative centromere segmentation algorithm
Publication TypeConference Paper
Year of Publication2000
AuthorsMousavi, P., R. K. Ward, M. Sameti, P. M. Lansdorp, and S. S. Fels
Conference NameEngineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Pagination2033 -2036 vol.3
Keywordsbio-optics, biology computing, cancer, cancer genetics, cellular biophysics, error backpropagation, error function, fluorescence, fluorescence microscopy, fuzzy membership value, fuzzy set theory, genetics, gradient descent method, gradient methods, homologue classification, human chromosome images, image classification, image segmentation, iterative centromere segmentation algorithm, iterative fuzzy algorithm, iteratively updating, medical image processing, optical microscopy
Abstract

Segmentation of centromeres is a major step towards classification of homologous chromosomes, which in turn, is essential to advanced studies of cancer genetics. This paper describes an iterative fuzzy algorithm, which successfully segments the centromeres of human chromosome images. The algorithm is based on assigning a fuzzy membership value to each pixel and iteratively updating an error function, Chromosome 22 is then used to verify the centromere segmentation method

URLhttp://dx.doi.org/10.1109/IEMBS.2000.900522
DOI10.1109/IEMBS.2000.900522

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