Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network. - Abdullah-Al-Zubaer Imran; Ali Hatamizadeh; Shilpa P. Ananth; Xiaowei Ding; Demetri Terzopoulos; Nima Tajbakhsh (DLMIA/ML-CDS@MICCAI, 2018)

Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIs. - Andriy Myronenko; Ali Hatamizadeh (BrainLes@MICCAI (2), 2019)

Deep Active Lesion Segmentation. - Ali Hatamizadeh; Assaf Hoogi; Debleena Sengupta; Wuyue Lu 001; Brian Wilcox; Daniel L. Rubin; Demetri Terzopoulos (MLMI@MICCAI, 2019)

End-to-End Boundary Aware Networks for Medical Image Segmentation. - Ali Hatamizadeh; Demetri Terzopoulos; Andriy Myronenko (MLMI@MICCAI, 2019)

Deep Dilated Convolutional Nets for the Automatic Segmentation of Retinal Vessels. - Ali Hatamizadeh; Hamid Hosseini; Zhengyuan Liu; Steven D. Schwartz; Demetri Terzopoulos (MLDM (1), 2019)

Boundary Aware Networks for Medical Image Segmentation. - Ali Hatamizadeh; Demetri Terzopoulos; Andriy Myronenko (CoRR, 2019)

3D Kidneys and Kidney Tumor Semantic Segmentation using Boundary-Aware Networks. - Andriy Myronenko; Ali Hatamizadeh (CoRR, 2019)

End-to-End Deep Convolutional Active Contours for Image Segmentation. - Ali Hatamizadeh; Debleena Sengupta; Demetri Terzopoulos (CoRR, 2019)

End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery. - Ali Hatamizadeh; Debleena Sengupta; Demetri Terzopoulos (ECCV (12), 2020)

Fast and automatic segmentation of pulmonary lobes from chest CT using a progressive dense V-network. - Abdullah-Al-Zubaer Imran; Ali Hatamizadeh; Shilpa P. Ananth; Xiaowei Ding; Nima Tajbakhsh; Demetri Terzopoulos (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020)

Edge-Gated CNNs for Volumetric Semantic Segmentation of Medical Images. - Ali Hatamizadeh; Demetri Terzopoulos; Andriy Myronenko (CoRR, 2020)

Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation. - Ali Hatamizadeh (CoRR, 2020)

Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation. - Ali Hatamizadeh (2020)

Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images. - Ali Hatamizadeh; Vishwesh Nath; Yucheng Tang; Dong Yang 005; Holger R. Roth; Daguang Xu (BrainLes@MICCAI (1), 2021)

Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports. - Riddhish Bhalodia; Ali Hatamizadeh; Leo K. Tam; Ziyue Xu 001; Xiaosong Wang 001; Evrim Turkbey; Daguang Xu (MICCAI (2), 2021)

The Power of Proxy Data and Proxy Networks for Hyper-parameter Optimization in Medical Image Segmentation. - Vishwesh Nath; Dong Yang 005; Ali Hatamizadeh; Anas A. Abidin; Andriy Myronenko; Holger R. Roth; Daguang Xu (MICCAI (3), 2021)

UNETR: Transformers for 3D Medical Image Segmentation. - Ali Hatamizadeh; Dong Yang 005; Holger Roth; Daguang Xu (CoRR, 2021)

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. - Raghav Mehta; Angelos Filos; Ujjwal Baid; Chiharu Sako; Richard McKinley; Michael Rebsamen; Katrin Dätwyler; Raphael Meier; Piotr Radojewski; Gowtham Krishnan Murugesan; Sahil S. Nalawade; Chandan Ganesh; et al. (CoRR, 2021)

GradViT: Gradient Inversion of Vision Transformers. - Ali Hatamizadeh; Hongxu Yin; Holger Roth; Wenqi Li 001; Jan Kautz; Daguang Xu; Pavlo Molchanov 001 (CVPR, 2022)

HyperSegNAS: Bridging One-Shot Neural Architecture Search with 3D Medical Image Segmentation using HyperNet. - Cheng Peng 008; Andriy Myronenko; Ali Hatamizadeh; Vishwesh Nath; Md Mahfuzur Rahman Siddiquee; Yufan He; Daguang Xu; Rama Chellappa; Dong Yang 005 (CVPR, 2022)

Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis. - Yucheng Tang; Dong Yang 005; Wenqi Li 001; Holger R. Roth; Bennett A. Landman; Daguang Xu; Vishwesh Nath; Ali Hatamizadeh (CVPR, 2022)

Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation. - An Xu; Wenqi Li 001; Pengfei Guo; Dong Yang 005; Holger Roth; Ali Hatamizadeh; Can Zhao 001; Daguang Xu; Heng Huang; Ziyue Xu 001 (CVPR, 2022)

Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation. - Pengfei Guo; Dong Yang 005; Ali Hatamizadeh; An Xu; Ziyue Xu 001; Wenqi Li 001; Can Zhao 001; Daguang Xu; Stephanie A. Harmon; Evrim Turkbey; Baris Turkbey; Bradford J. Wood; et al. (ECCV (21), 2022)

Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-modal Brain Tumor Segmentation. - Holger R. Roth; Ali Hatamizadeh; Ziyue Xu 001; Can Zhao 001; Wenqi Li 001; Andriy Myronenko; Daguang Xu (DeCaF/FAIR@MICCAI, 2022)

UNETR: Transformers for 3D Medical Image Segmentation. - Ali Hatamizadeh; Yucheng Tang; Vishwesh Nath; Dong Yang 005; Andriy Myronenko; Bennett A. Landman; Holger R. Roth; Daguang Xu (WACV, 2022)

UNetFormer: A Unified Vision Transformer Model and Pre-Training Framework for 3D Medical Image Segmentation. - Ali Hatamizadeh; Ziyue Xu 001; Dong Yang 005; Wenqi Li 001; Holger Roth; Daguang Xu (CoRR, 2022)

Global Context Vision Transformers. - Ali Hatamizadeh; Hongxu Yin; Jan Kautz; Pavlo Molchanov 001 (CoRR, 2022)

MONAI: An open-source framework for deep learning in healthcare. - M. Jorge Cardoso; Wenqi Li 001; Richard Brown 004; Nic Ma; Eric Kerfoot; Yiheng Wang; Benjamin Murray; Andriy Myronenko; Can Zhao 001; Dong Yang 005; Vishwesh Nath; Yufan He; et al. (CoRR, 2022)

RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imaging. - Ali Hatamizadeh; Hamid Hosseini; Niraj Patel; Jinseo Choi; Cameron C. Pole; Cory M. Hoeferlin; Steven D. Schwartz; Demetri Terzopoulos (IEEE J. Biomed. Health Informatics, 2022)

Global Context Vision Transformers. - Ali Hatamizadeh; Hongxu Yin; Greg Heinrich; Jan Kautz; Pavlo Molchanov 001 (ICML, 2023)

DAST: Differentiable Architecture Search with Transformer for 3D Medical Image Segmentation. - Dong Yang 005; Ziyue Xu 001; Yufan He; Vishwesh Nath; Wenqi Li 001; Andriy Myronenko; Ali Hatamizadeh; Can Zhao 001; Holger R. Roth; Daguang Xu (MICCAI (3), 2023)

ViR: Vision Retention Networks. - Ali Hatamizadeh; Michael Ranzinger; Jan Kautz (CoRR, 2023)

Do Gradient Inversion Attacks Make Federated Learning Unsafe? - Ali Hatamizadeh; Hongxu Yin; Pavlo Molchanov 001; Andriy Myronenko; Wenqi Li 001; Prerna Dogra; Andrew Feng; Mona G. Flores; Jan Kautz; Daguang Xu; Holger R. Roth (IEEE Trans. Medical Imaging, 2023)

DiffiT: Diffusion Vision Transformers for Image Generation. - Ali Hatamizadeh; Jiaming Song; Guilin Liu; Jan Kautz; Arash Vahdat (ECCV (8), 2024)

FasterViT: Fast Vision Transformers with Hierarchical Attention. - Ali Hatamizadeh; Greg Heinrich; Hongxu Yin; Andrew Tao; José M. Álvarez 004; Jan Kautz; Pavlo Molchanov 001 (ICLR, 2024)

An Empirical Study of Mamba-based Language Models. - Roger Waleffe; Wonmin Byeon; Duncan Riach; Brandon Norick; Vijay Korthikanti; Tri Dao; Albert Gu; Ali Hatamizadeh; Sudhakar Singh 003; Deepak Narayanan; Garvit Kulshreshtha; Vartika Singh; et al. (CoRR, 2024)

MambaVision: A Hybrid Mamba-Transformer Vision Backbone. - Ali Hatamizadeh; Jan Kautz (CVPR, 2025)

Gated Delta Networks: Improving Mamba2 with Delta Rule. - Songlin Yang; Jan Kautz; Ali Hatamizadeh (ICLR, 2025)