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Abstract #4156

Feasibility of MRI image based synthetic CT generation in radiotherapy using deep convolutional neural network

Yafen Li1, Wen Li1, Yaoqin Xie1, and Jun Xia2

1Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2Department of Radiology, Shenzhen Second People's Hospital (the First Affiliated Hospital of Shenzhen University), Shenzhen, China

Generating electronic density information for MRI images is crucial for MRI-based dose calculation in a MRI-only workflow of radiotherapy. To address this problem, we proposed a deep convolutional neural network plus with an auto-context model to predict synthetic CT from MRI images of routine-sequence. The highly accuracy of generated synthetic CT results shows that the proposed method is effective and robust.

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