Interpretable Spiculation Quantification for Lung Cancer Screening. - Wookjin Choi; Saad Nadeem; Sadegh Riyahi; Joseph O. Deasy; Allen R. Tannenbaum; Wei Lu 025 (ShapeMI@MICCAI, 2018)

Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response. - Sadegh Riyahi; Wookjin Choi; Chia-Ju Liu; Saad Nadeem; Shan Tan; Hualiang Zhong; Wengen Chen; Abraham J. Wu; James G. Mechalakos; Joseph O. Deasy; Wei Lu 025 (DATRA/PIPPI@MICCAI, 2018)

Comparison of Patch-Based Conditional Generative Adversarial Neural Net Models with Emphasis on Model Robustness for Use in Head and Neck Cases for MR-Only planning. - Peter Klages; Ilyes Benslimane; Sadegh Riyahi; Jue Jiang; Margie Hunt; Joseph O. Deasy; Harini Veeraraghavan; Neelam Tyagi (CoRR, 2019)

Longitudinal Prediction of Radiation-Induced Anatomical Changes of Parotid Glands During Radiotherapy Using Deep Learning. - Donghoon Lee; Sadegh R. Alam; Saad Nadeem; Jue Jiang; Pengpeng Zhang; Yu-Chi Hu (PRIME@MICCAI, 2020)

Generalizable Cone Beam CT Esophagus Segmentation Using In Silico Data Augmentation. - Sadegh R. Alam; Tianfang Li; Si-Yuan Zhang; Pengpeng Zhang; Saad Nadeem (CoRR, 2020)

Reproducible and Interpretable Spiculation Quantification for Lung Cancer Screening. - Wookjin Choi; Saad Nadeem; Sadegh R. Alam; Joseph O. Deasy; Allen R. Tannenbaum; Wei Lu 025 (Comput. Methods Programs Biomed., 2021)

Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation. - Jue Jiang; Sadegh Riyahi Alam; Ishita Chen; Perry Zhang; Andreas Rimner; Joseph O. Deasy; Harini Veeraraghavan (CoRR, 2021)

Multitask 3D CBCT-to-CT Translation and Organs-at-Risk Segmentation Using Physics-Based Data Augmentation. - Navdeep Dahiya; Sadegh R. Alam; Pengpeng Zhang; Si-Yuan Zhang; Anthony J. Yezzi; Saad Nadeem (CoRR, 2021)

Deformation Driven Seq2Seq Longitudinal Tumor and Organs-at-Risk Prediction for Radiotherapy. - Donghoon Lee; Sadegh R. Alam; Jue Jiang; Pengpeng Zhang; Saad Nadeem; Yu-Chi Hu (CoRR, 2021)