43 citations · 66 across the 4 of their papers we have counts for
4 papers
Deformation Driven Seq2Seq Longitudinal Tumor and Organs-at-Risk Prediction for Radiotherapy
Donghoon Lee, Sadegh R Alam, Jue Jiang +3
Purpose: Radiotherapy presents unique challenges and clinical requirements for longitudinal tumor and organ-at-risk (OAR) prediction during treatment. The challenges include tumor…
Multitask 3D CBCT-to-CT Translation and Organs-at-Risk Segmentation Using Physics-Based Data Augmentation
Navdeep Dahiya, Sadegh R Alam, Pengpeng Zhang +3
In current clinical practice, noisy and artifact-ridden weekly cone-beam computed tomography (CBCT) images are only used for patient setup during radiotherapy. Treatment planning i…
Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation
Jue Jiang, Sadegh Riyahi Alam, Ishita Chen +4
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…
Generalizable Cone Beam CT Esophagus Segmentation Using Physics-Based Data Augmentation
Sadegh R Alam, Tianfang Li, Pengpeng Zhang +2
Automated segmentation of esophagus is critical in image guided/adaptive radiotherapy of lung cancer to minimize radiation-induced toxicities such as acute esophagitis. We develope…