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Advances in Radiation Oncology|July 18, 2022
Automatic Contour Refinement for Deep Learning Auto-segmentation of Complex Organs in MRI-guided Adaptive Radiation TherapyJie Ding, Ying Zhang, Asma Amjad, et al.
Physics in Medicine and Biology|May 30, 2023
Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumorsErgun Ahunbay, Abdul K Parchur, Jiaofeng Xu, et al.
Physics and Imaging in Radiation Oncology|May 20, 2026
Auto-segmentation and dose accuracy evaluation of synthetic computed tomography generated from pelvis cone-beam computed tomography images using a cycle-generative adversarial network with a novel loss functionSilambarasan Anbumani, Andrew Keeler, Jiaofeng Xu, et al.
Frontiers in Oncology|July 24, 2023
Deep learning auto-segmentation on multi-sequence magnetic resonance images for upper abdominal organsAsma Amjad, Jiaofeng Xu, Dan Thill, et al.
Medical Physics|January 30, 2022
General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvisAsma Amjad, Jiaofeng Xu, Dan Thill, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|January 25, 2024
Evaluating AI-generated CBCT-based synthetic CT images for target delineation in palliative treatments of pelvic bone metastasis at conventional C-arm linacsNienke Hoffmans-Holtzer, Alba Magallon-Baro, Ilse de Pree, et al.
Physics and Imaging in Radiation Oncology|July 3, 2025
A method for sensitivity analysis of automatic contouring algorithms across different contrast weightings using synthetic magnetic resonance imagingLucas McCullum, Zayne Belal, Warren Floyd, et al.
Medrxiv : the Preprint Server for Health Sciences|January 20, 2025
A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMRLucas McCullum, Zayne Belal, Warren Floyd, et al.
Frontiers in Oncology|November 25, 2022
Deep-learning-based generation of synthetic 6-minute MRI from 2-minute MRI for use in head and neck cancer radiotherapyKareem A Wahid, Jiaofeng Xu, Dina El-Habashy, et al.
Medical Physics|July 21, 2023
Investigation of autosegmentation techniques on T2-weighted MRI for off-line dose reconstruction in MR-linac workflow for head and neck cancersBrigid A McDonald, Carlos E Cardenas, Nicolette O'Connell, et al.
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