DocumentCode
1742949
Title
A multi-window approach to classify histological features
Author
Lam, Ringo W K ; Ip, Horace H S ; Cheung, Kent K T ; Tang, Lilian H Y ; Hanka, R.
Author_Institution
Dept. of Comput. Sci., City Univ. of Hong Kong, China
Volume
2
fYear
2000
fDate
2000
Firstpage
259
Abstract
Medical images are usually composed of different kinds of texture components which are always so much varied that a conventional single window approach cannot capture enough salient information for comparison. This paper applies the widely used multi-channel Gabor filters to demonstrate how a multi-window approach can improve the classification accuracy rate of histological labels. In addition, a most confident window method is proposed to further increase the accuracy rate of the multi-window approach
Keywords
feature extraction; frequency-domain analysis; image texture; medical image processing; spatial filters; Gabor filters; feature extraction; frequency domain analysis; histological labels; image texture; medical image processing; multiple-window method; pattern classification; Biomedical imaging; Biomedical informatics; Computer science; Finite impulse response filter; Frequency; Gabor filters; Image analysis; Image texture analysis; Statistics; Wavelet domain;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.906062
Filename
906062
Link To Document