Abstract #1612

A Fully Automatic Blind Estimation of Tumor Microvascular Permeability using Embedded Unsupervised Regularizations based on Prostate DCE-MRI

Junjie Wu¹, Ya Cao¹, Xiaodong Zhang², Xiaoying Wang², and Jue Zhang¹

¹Peking University, Beijing, China, ²Peking University First Hospital, Beijing, China

Vascular permeability can reflect tumorigenesis and metastasis. Previous dynamic contrast-enhanced magnetic resonance imaging based pharmacokinetic parameters estimation needs to manually select arterial input function (AIF) or reference regions (RR), and the results depend sensitively on the AIF selection. Our goal is to develop a more robust estimation approach without previously provided AIF or RR regions, for examining bone metastases from prostate cancer.

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