Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation.
Journal:
Medical physics
Published Date:
May 25, 2021
Abstract
PURPOSE: Despite the widespread availability of in-treatment room cone beam computed tomography (CBCT) imaging, due to the lack of reliable segmentation methods, CBCT is only used for gross set up corrections in lung radiotherapies. Accurate and reliable auto-segmentation tools could potentiate volumetric response assessment and geometry-guided adaptive radiation therapies. Therefore, we developed a new deep learning CBCT lung tumor segmentation method.
