TY - GEN
T1 - Texture classification using nonlinear color quantization
T2 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
AU - Sertel, Olcay
AU - Kong, Jun
AU - Lozanski, Gerard
AU - Shana 'Ah, Arwa
AU - Catalyurek, Umit
AU - Saltz, Joel
AU - Gurcan, Metin
PY - 2008
Y1 - 2008
N2 - In this paper, a novel color texture classification approach is introduced and applied to computer-assisted grading of follicular lymphoma from whole-slide tissue samples. The digitized tissue samples of follicular lymphoma were classified into histological grades under a statistical framework. The proposed method classifies the image either into low or high grades based on the amount of cytological components. To further discriminate the lower grades into low and mid grades, we proposed a novel color texture analysis approach. This approach modifies the gray level cooccurrence matrix method by using a non-linear color quantization with self-organizing feature maps (SOFMs). This is particularly useful for the analysis of H&E stained pathological images whose dynamic color range is considerably limited. Experimental results on real follicular lymphoma images demonstrate that the proposed approach outperforms the gray level based texture analysis.
AB - In this paper, a novel color texture classification approach is introduced and applied to computer-assisted grading of follicular lymphoma from whole-slide tissue samples. The digitized tissue samples of follicular lymphoma were classified into histological grades under a statistical framework. The proposed method classifies the image either into low or high grades based on the amount of cytological components. To further discriminate the lower grades into low and mid grades, we proposed a novel color texture analysis approach. This approach modifies the gray level cooccurrence matrix method by using a non-linear color quantization with self-organizing feature maps (SOFMs). This is particularly useful for the analysis of H&E stained pathological images whose dynamic color range is considerably limited. Experimental results on real follicular lymphoma images demonstrate that the proposed approach outperforms the gray level based texture analysis.
KW - Color texture analysis
KW - Computer-aided diagnosis
KW - Self-organizing feature maps
UR - https://www.scopus.com/pages/publications/51449097478
U2 - 10.1109/ICASSP.2008.4517680
DO - 10.1109/ICASSP.2008.4517680
M3 - Conference contribution
AN - SCOPUS:51449097478
SN - 1424414849
SN - 9781424414840
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 597
EP - 600
BT - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Y2 - 31 March 2008 through 4 April 2008
ER -