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Abstract #1748

Improved Prostate Cancer Detection using DCE-MRI and Probability Maps

Huang X, Wang Q, Wang X, Bao S, Xu Y
The Key Lab of Medical Physics and Engineering,Peking University

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been used for the assessment of prostate diseases by examining the kinetic properties of MR time-intensity curve (TIC) variations. The feature parameters to describe the enhancement of TIC are usually evaluated and referenced separately. We combined these parameters with logistic regression to determine the statistical probability model on whether a prostate region is cancerous or not and improved detection of prostate cancer by computing the prostate cancer probability maps.