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Abstract #4740

Accelerating DCE-MRI Analysis for Prostate Cancer Diagnosis with Deep Neural Networks

Kai Zhao1, Haoxin Zheng1, and Kyunghyun Sung1
1Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Data Analysis, dynamic contrast enhancedA deep learning based DCE-MRI analysis method was proposed with a dedicated neural network architecture and data generation framework. The proposed method does not need DCE-MRI data acquisition or annotation for training. Compared to conventional non-linear least square (NLLS) fitting methods, the proposed method significantly reduced the average processing time from hours to few minutes while preserved the estimation quality.

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Keywords