We developed a deep learning-based segmentation method to rapidly and accurately segment five pelvic organs simultaneously from daily CBCTs.
Adaptive radiotherapy which relies on patient Cone-Beam CT (CBCT) imaged right before dose delivery to update the contouring and treatment plans has the ...
May 11, 2020 · The purpose of this study is to develop a deep learning-based approach to simultaneously segment five pelvic organs including prostate, bladder, ...
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In this study, we proposed a synthetic MRI-aided multi-organ segmentation from cone-beam CT for prostate adaptive radiotherapy. A cycle-consistent generative ...
Apr 22, 2020 · The purpose of this study is to develop a deep learning-based approach to simultaneously segment five pelvic organs including prostate, bladder, ...
Another method designed for segmenting prostate CBCT images [22] trained a CycleGAN model using aligned CBCT and MRI pairs to translate prostate CBCT images to ...
Quantitative cone beam computed tomography (CBCT) imaging is increasing in demand for precise image guided radiation therapy since it provides a foundation ...
CBCT-guided online adaptive radiotherapy (oART) with magnetic resonance (MR) guidance workflow: During treatment, patients underwent MR imaging in treatment ...
Apr 26, 2024 · A previous pilot study used daily Cone Beam CT (CBCT) images to generate delta-radiomics models to predict acute and sub-acute genitourinary (GU) ...
Jun 24, 2024 · Background and purpose The purpose of this study is to develop a deep learning‐based approach to simultaneously segment five pelvic organs ...