Self-supervised region-aware segmentation of COVID-19 CT images using 3D GAN and contrastive learning. - Siyavash Shabani; Morteza Homayounfar; Varut Vardhanabhuti; Mohammad-Ali Nikouei Mahani; Mohamad Koohi-Moghadam (Comput. Biol. Medicine, 2022)

Multi-Aperture Fusion of Transformer-Convolutional Network (MFTC-Net) for 3D Medical Image Segmentation and Visualization. - Siyavash Shabani; Muhammad Sohaib; Sahar A. Mohammed; Bahram Parvin (CoRR, 2024)

A Novel 3D Decoder with Weighted and Learnable Triple Attention for 3D Microscopy Image Segmentation. - Siyavash Shabani; Sahar A. Mohammed; Bahram Parvin (CVPR Workshops, 2025)

Logsage: Log-Based Saliency for Guided Encoding in Robust Nuclei Segmentation of Immunofluorescence Histology Images. - Sahar A. Mohammed; Siyavash Shabani; Muhammad Sohaib; Corina Nicolescu; Mary Helen Barcellos-Hoff; Bahram Parvin (ISBI, 2025)

Coupled Swin Transformers and Multi-Apertures Network(CSTA-NET) Improves Medical Image Segmentation. - Siyavash Shabani; Muhammad Sohaib; Sahar A. Mohammed; Bahram Parvin (ISBI, 2025)

Multi-Aperture Transformers for 3D (MAT3D) Segmentation of Clinical and Microscopic Images. - Muhammad Sohaib; Siyavash Shabani; Sahar A. Mohammed; Garrett Winkelmaier; Bahram Parvin (WACV, 2025)

3D-Organoid-SwinNet: High-Content Profiling of 3D Organoids. - Muhammad Sohaib; Siyavash Shabani; Sahar A. Mohammed; Bahram Parvin (IEEE J. Biomed. Health Informatics, 2025)