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Proceedings Paper

Computer Classification Of Rosette Forming Cells Using Microscope Images
Author(s): Minami Yamada; Eisaku Takinami; Shinji Ozawa; Hajime Takata; Akira Sonoda; Hisami Iri
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Paper Abstract

This paper presents a computer classification system of rosette forming cells. In clinical immunology, it is important to distinguish lymphocytes into some subpopulations. For this purpose, rosette formation test is one of the most popular and useful methods. But recognizing rosetted and non-rosetted process depends on microscopic examination. We notice that an accumulative histgram of gray-levels presents characteristics of each rosette well. The system proposed here extracts rosettes from microscope image, constructs an accumulative histgrams of gray-levels for each rosette, and classifies rosettes into five groups using several features derived from the accumulative histgrams. Touching rosettes are also treated. The system is tested using 322 samples from 10 images. Total accuracy of classification is 73.3 %. And total correctrate of rosetted and non-rosetted dicision is 86.0 %. It is confirmed that computer classification of rosette forming cells is possible by the proposed method.

Paper Details

Date Published: 3 August 1984
PDF: 7 pages
Proc. SPIE 0515, Medical Images and Icons, (3 August 1984); doi: 10.1117/12.964790
Show Author Affiliations
Minami Yamada, Keio University (Japan)
Eisaku Takinami, Keio University (Japan)
Shinji Ozawa, Keio University (Japan)
Hajime Takata, Keio University (Japan)
Akira Sonoda, Keio University (Japan)
Hisami Iri, Keio University (Japan)


Published in SPIE Proceedings Vol. 0515:
Medical Images and Icons
Andre J. Duerinckx; Murray H. Loew; Judith M. S. Prewitt, Editor(s)

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