
AbstractIn this work, we demonstrate a method for rapid synthesis of high‐quality CT images from unpaired, low‐quality CBCT images, permitting CBCT‐based adaptive radiotherapy. We adapt contrastive unpaired translation (CUT) to be used with medical images and evaluate the results on an institutional pelvic CT dataset. We compare the method against cycleGAN using mean absolute error, structural similarity index, root mean squared error, and Frèchet Inception Distance and show that CUT significantly outperforms cycleGAN while requiring less time and fewer resources. The investigated method improves the feasibility of online adaptive radiotherapy over the present state‐of‐the‐art.
Radiotherapy Planning, Computer-Assisted, Image Processing, Computer-Assisted, Radiation Oncology Physics, Humans, Radiotherapy Dosage, Spiral Cone-Beam Computed Tomography, Cone-Beam Computed Tomography
Radiotherapy Planning, Computer-Assisted, Image Processing, Computer-Assisted, Radiation Oncology Physics, Humans, Radiotherapy Dosage, Spiral Cone-Beam Computed Tomography, Cone-Beam Computed Tomography
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