| Literature DB >> 17280945 |
Herbert Ramoser1, Vincent Laurain, Horst Bischof, Rupert Ecker.
Abstract
The detection and classification of leukocytes in blood smear images is a routine task in medical diagnosis. In this paper we present a fully automated approach to leukocyte segmentation that is robust with respect to cell appearance and image quality. A set of features is used to describe cytoplasm and nucleus properties. Pairwise SVM classification is used to discriminate between different cell types. Evaluation on a set of 1166 images (13 classes) resulted in 95% correct segmentations and 75% to 99% correct classification (with reject option).Year: 2005 PMID： 17280945 DOI： 10.1109/IEMBS.2005.1617200
Source DB: PubMed Journal: Conf Proc IEEE Eng Med Biol Soc ISSN： 1557-170X