Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
504056 | Computerized Medical Imaging and Graphics | 2015 | 9 Pages |
Abstract
Detection and classification of cells in histological images is a challenging task because of the large intra-class variation in the visual appearance of various types of biological cells. In this paper, we propose a discriminative dictionary learning paradigm, termed as Cell Words, for modelling the visual appearance of cells which includes colour, shape, texture and context in a unified manner. The proposed framework is capable of distinguishing mitotic cells from non-mitotic cells (apoptotic, necrotic, epithelial) in breast histology images with high accuracy.
Keywords
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Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Korsuk Sirinukunwattana, Adnan M. Khan, Nasir M. Rajpoot,