Identifying Lymphoma in Microscopy Images with Classificational Cellular Automata

Author

Povalej, Petra ; Verlic, M. ; Kokol, Peter ; Sánchez, José L. ; Sigut, José F.

Author_Institution

Laboratory for Syst. Design, Maribor Univ.

fYear

0

fDate

0-0 0

Firstpage

309

Lastpage

314

Abstract

We present the results of a supervised approach for identification of follicular lymphomas in microscopy images. A new feature extraction approach is presented. The proposed discriminative features intend to emphasize the distinction among pixels on follicle contour. Additionally those features are used for supervised learning using classificational cellular automata (CCA) approach with the aim to obtain a general decision support model for classification of follicle contours on the microscopy images

Keywords

biomedical optical imaging; cancer; cellular automata; decision support systems; feature extraction; image classification; learning (artificial intelligence); medical image processing; classificational cellular automata; feature extraction; follicle contour; follicular lymphomas; general decision support model; microscopy images; supervised learning; Automata; Brightness; Cancer; Density measurement; Feature extraction; Laboratories; Lymphatic system; Microscopy; Pixel; Supervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on

Conference_Location

Salt Lake City, UT

ISSN

1063-7125

Print_ISBN

0-7695-2517-1

Type

conf

DOI

10.1109/CBMS.2006.97

Filename

1647587