CCE-based index selection for neuro assisted MR-image segmentation

Author

Kosugi, Yukio ; Suganaimi, Yusuke ; Uemoto, Naoko ; Kameyama, Keisuke ; Sase, Mikiya ; Momose, Toshimitsu ; Nishikawa, Junichi

Author_Institution

Tokyo Inst. of Technol., Japan

Volume

1

fYear

1996

fDate

16-19 Sep 1996

Firstpage

249

Abstract

For image segmentation with the aid of neural networks of a reasonable size, it is important to select the most effective combination of secondary indices to be used for the classification. Here, the authors introduce a vector quantized conditional class entropy (VQCCE) criterion to evaluate which indices are effective for pattern classification, without testing on the actual classifiers. The proposed method was successfully applied for brain MR segmentation problems to classify the gray-matter/white-matter regions

Keywords

biomedical NMR; brain; entropy; image classification; image segmentation; medical image processing; neural nets; vector quantisation; MRI; brain MR segmentation problems; gray-matter regions; magnetic resonance imaging; medical diagnostic imaging; pattern classification; secondary indices; vector quantized conditional class entropy criterion; white-matter regions; Biological neural networks; Biomedical imaging; Books; Electronic mail; Entropy; Image segmentation; Medical diagnostic imaging; Testing; Vector quantization; Virtual reality;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.560762

Filename

560762