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Abstract #4877

Deep neural network processing of original DCE-MRI data for survival prediction

Junyu Guo1 and Wilburn E. Reddick1

1St Jude Children's Research Hospital, Memphis, TN, United States

DCE-MRI is a valuable tools in many clinical applications, but data analysis is complex. The purpose of this study was to assess whether the original DCE images without complex modeling can be used to predict the clinical results of osteosarcoma using deep convolution neural network (DCNN). We also assess whether the prediction from original images were different from those using the kinetic parameters. We found that DCNN can predict overall survivals with an accuracy of about 0.8 using a set of 2D DCE tumor images, which is not significantly different from results based on kinetic parameter maps.

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