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Abstract #2641

Accuracy Enhancement of Automatic Prostate Tumor Detection using Additional Deformable Registration Based Atlas Information: Automated Classifier using Permeability Parameters.

Namkug Kim1, JeongKon Kim1

1Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea, Republic of

The prostate is anatomically composed of central, peripheral, and transitional zones. In the peripheral zone, 70% of prostate cancers arise. In addition, 20% of prostate cancers arise in the transitional zone. To exploit this tumor occurrence information, we evaluated accuracy enhancement for prostate tumor detection of automated classifier using deformable registration based atlas information as well as permeability parameters. In thirty seven patients with radical prostatectomy, MR images were obtained, including T2WI and dynamic contrast enhanced MR imaging for Brix permeability analysis. Each prostate was manually segmented into transitional zone and other zone by an expert radiologist and registered by FSL FNIRT deformable registration method. Sensitivity, specificity, accuracy, and AUC of ROC were significantly greater in automated classifier with atlas information (86.50.02%, 95.50.01%, 92.21.08%, 92.90.00 respectively) than in that without atlas information.