TY - GEN
T1 - Computer-aided gleason grading of prostate cancer histopathological images using texton forests
AU - Khurd, Parmeshwar
AU - Bahlmann, Claus
AU - Maday, Peter
AU - Kamen, Ali
AU - Gibbs-Strauss, Summer
AU - Genega, Elizabeth M.
AU - Frangioni, John V.
PY - 2010
Y1 - 2010
N2 - The Gleason score is the single most important prognostic indicator for prostate cancer candidates and plays a significant role in treatment planning. Histopathological imaging of prostate tissue samples provides the gold standard for obtaining the Gleason score, but the manual assignment of Gleason grades is a labor-intensive and errorprone process. We have developed a texture classification system for automatic and reproducible Gleason grading. Our system characterizes the texture in images belonging to a tumor grade by clustering extracted filter responses at each pixel into textons (basic texture elements). We have used random forests to cluster the filter responses into textons followed by the spatial pyramid match kernel in conjunction with an SVM classifier. We have demonstrated the efficacy of our system in distinguishing between Gleason grades 3 and 4.
AB - The Gleason score is the single most important prognostic indicator for prostate cancer candidates and plays a significant role in treatment planning. Histopathological imaging of prostate tissue samples provides the gold standard for obtaining the Gleason score, but the manual assignment of Gleason grades is a labor-intensive and errorprone process. We have developed a texture classification system for automatic and reproducible Gleason grading. Our system characterizes the texture in images belonging to a tumor grade by clustering extracted filter responses at each pixel into textons (basic texture elements). We have used random forests to cluster the filter responses into textons followed by the spatial pyramid match kernel in conjunction with an SVM classifier. We have demonstrated the efficacy of our system in distinguishing between Gleason grades 3 and 4.
KW - Gleason grading
KW - Prostate cancer
KW - Texture classification
UR - http://www.scopus.com/inward/record.url?scp=77955217140&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77955217140&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2010.5490096
DO - 10.1109/ISBI.2010.5490096
M3 - Conference contribution
AN - SCOPUS:77955217140
SN - 9781424441266
T3 - 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings
SP - 636
EP - 639
BT - 2010 7th IEEE International Symposium on Biomedical Imaging
T2 - 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
Y2 - 14 April 2010 through 17 April 2010
ER -