Keywords: Analysis/Processing, Liver, MR radiotherapy, medical image synthesis，
Motivation: MRI-only radiotherapy requires synthesizing MR images into CT-equivalent images to calculate the radiation dose. However, the current synthesis methods are limited when applied to small anatomical regions, such as tumors.
Goal(s): Our goal was to develop a novel MR-to-CT synthesis algorithm that produces better results for small anatomical structures.
Approach: We introduced a multi-branch hybrid perceptual generative model incorporating an attention mechanism to synthesize different scales anatomical structures.
Results: Our proposed algorithms yield favorable results for small anatomical structures based on physician feedback and quantitative assessments.
Impact: The proposed synthesis algorithm simplifies and speeds up MRI-only radiotherapy workflow. It is also applicable to other fields of medical image synthesis, such as multi-modal image diagnosis treatment.
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