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Abstract #2640

Computerized Quantitative Data Integration of Multi-Protocol MRI for Identification of High Grade Prostate Cancer In Vivo.

Pallavi Tiwari1, John Kurhanewicz2, Anant Madabhushi1

1Biomedical Engineering, Rutgers University, Piscataway, NJ, United States; 2Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, United States

In this work we present a novel multi-protocol MRI classifier, semi-supervised multi-kernel (SeSMiK), for quantitatively combining features from T2-w magnetic resonance (MR) imaging (T2