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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