TY - GEN
T1 - Classification of multicolor fluorescence in-situ hybridization (M-FISH) image using regularized multinomial logistic regression
AU - Li, Jingyao
AU - Cao, Hongbao
AU - Wang, Yu Ping
PY - 2012
Y1 - 2012
N2 - In this paper, we applied a regularized multinomial logistic regression (RMLR) for multicolor fluorescence in-situ hybridization (M-FISH) image analysis, in order to better classify chromosomes. The RMLR integrates complementary information from multi-channel M-FISH images and considers the relationship of these data between different channels. We compared the model with two other regression models, e.g., multinomial logistic regression (MLR) and sparse multinomial logistic regression (SMLR). We show that the correct classification ratio of chromosomal region by the RMLR model is almost 93%, compared with 90% and 76% by the MLR and SMLR model when tested in a comprehensive M-FISH image database that we established and the p-value of these three models indicating that the RMLR model can significantly improve the accuracy of MFISH image analysis.
AB - In this paper, we applied a regularized multinomial logistic regression (RMLR) for multicolor fluorescence in-situ hybridization (M-FISH) image analysis, in order to better classify chromosomes. The RMLR integrates complementary information from multi-channel M-FISH images and considers the relationship of these data between different channels. We compared the model with two other regression models, e.g., multinomial logistic regression (MLR) and sparse multinomial logistic regression (SMLR). We show that the correct classification ratio of chromosomal region by the RMLR model is almost 93%, compared with 90% and 76% by the MLR and SMLR model when tested in a comprehensive M-FISH image database that we established and the p-value of these three models indicating that the RMLR model can significantly improve the accuracy of MFISH image analysis.
KW - Chromosome classification
KW - M-FISH
KW - Regularized multinomial logistic regression
UR - http://www.scopus.com/inward/record.url?scp=84869466099&partnerID=8YFLogxK
U2 - 10.1145/2382936.2383018
DO - 10.1145/2382936.2383018
M3 - Contribución a la conferencia
AN - SCOPUS:84869466099
SN - 9781450316705
T3 - 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012
SP - 551
EP - 554
BT - 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012
T2 - 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012
Y2 - 7 October 2012 through 10 October 2012
ER -