AAPM | COMP Joint Meeting · Vancouver · July 19-22
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To evaluate two prototype deep learning–based synthetic CT (sCT) generation models for pelvic and abdominal anatomies using T1-weighted and T2-weighted MR sequences. This study aims to validate their potential to enable MR-only r...
Cycle generative adversarial network (GAN) has a difficulty in maintaining the structural integrity in a synthesized image for complex organs and tissues. In this study, we proposed a CycleGAN including multi-scale blocks and att...
MRI provides advantages for tumor and critical structure delineation in head-and-neck (H&N) radiotherapy. However, H&N MR-only workflows remain challenging due to the large field-of-view and susceptibility artifacts arising from...
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