Feature fusion as a practical solution toward noncooperative iris recognition. - Nima Tajbakhsh; Babak Nadjar Araabi; Hamid Soltanian-Zadeh (FUSION, 2008)

An intelligent decision combiner applied to noncooperative iris recognition. - Nima Tajbakhsh; Babak Nadjar Araabi; Hamid Soltanian-Zadeh (FUSION, 2008)

A Region-Based Iris Feature Extraction Method Based on 2D-Wavelet Transform. - Nima Tajbakhsh; Khashayar Misaghian; Naghmeh Mohammadi Bandari (COST 2101/2102 Conference, 2009)

Noisy Iris Verification: A Modified Version of Local Intensity Variation Method. - Nima Tajbakhsh; Babak Nadjar Araabi; Hamid Soltanian-Zadeh (ICB, 2009)

Robust Iris Verification Based on Local and Global Variations. - Nima Tajbakhsh; Babak Nadjar Araabi; Hamid Soltanian-Zadeh (EURASIP J. Adv. Signal Process., 2010)

Automated Detection of Major Thoracic Structures with a Novel Online Learning Method. - Nima Tajbakhsh; Hong Wu; Wenzhe Xue; Jianming Liang (MLMI, 2011)

Self-adaptive asymmetric on-line boosting for detecting anatomical structures. - Hong Wu; Nima Tajbakhsh; Wenzhe Xue; Jianming Liang (Computer-Aided Diagnosis, 2012)

A Classification-Enhanced Vote Accumulation Scheme for Detecting Colonic Polyps. - Nima Tajbakhsh; Suryakanth R. Gurudu; Jianming Liang (Abdominal Imaging, 2013)

A novel online boosting algorithm for automatic anatomy detection. - Nima Tajbakhsh; Hong Wu; Wenzhe Xue; Michael B. Gotway; Jianming Liang (Mach. Vis. Appl., 2013)

Automatic polyp detection from learned boundaries. - Nima Tajbakhsh; Changching Chi; Suryakanth R. Gurudu; Jianming Liang (ISBI, 2014)

Automatic Assessment of Image Informativeness in Colonoscopy. - Nima Tajbakhsh; Changching Chi; Haripriya Sharma; Qing Wu; Suryakanth R. Gurudu; Jianming Liang (ABDI@MICCAI, 2014)

Automatic Polyp Detection Using Global Geometric Constraints and Local Intensity Variation Patterns. - Nima Tajbakhsh; Suryakanth R. Gurudu; Jianming Liang (MICCAI (2), 2014)

A Comprehensive Computer-Aided Polyp Detection System for Colonoscopy Videos. - Nima Tajbakhsh; Suryakanth R. Gurudu; Jianming Liang (IPMI, 2015)

Automatic polyp detection in colonoscopy videos using an ensemble of convolutional neural networks. - Nima Tajbakhsh; Suryakanth R. Gurudu; Jianming Liang (ISBI, 2015)

Computer-Aided Pulmonary Embolism Detection Using a Novel Vessel-Aligned Multi-planar Image Representation and Convolutional Neural Networks. - Nima Tajbakhsh; Michael B. Gotway; Jianming Liang (MICCAI (2), 2015)

Ensuring High-Quality Colonoscopy by Reducing Polyp Miss-Rates. - Nima Tajbakhsh (2015)

Automating Carotid Intima-Media Thickness Video Interpretation with Convolutional Neural Networks. - Jae Y. Shin; Nima Tajbakhsh; R. Todd Hurst; Christopher B. Kendall; Jianming Liang (CVPR, 2016)

Automated Polyp Detection in Colonoscopy Videos Using Shape and Context Information. - Nima Tajbakhsh; Suryakanth R. Gurudu; Jianming Liang (IEEE Trans. Medical Imaging, 2016)

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? - Nima Tajbakhsh; Jae Y. Shin; Suryakanth R. Gurudu; R. Todd Hurst; Christopher B. Kendall; Michael B. Gotway; Jianming Liang (IEEE Trans. Medical Imaging, 2016)

Automatic Interpretation of Carotid Intima-Media Thickness Videos Using Convolutional Neural Networks. - Nima Tajbakhsh; Jae Y. Shin; R. Todd Hurst; Christopher B. Kendall; Jianming Liang (Deep Learning for Medical Image Analysis, 2017)

Automatic polyp detection in colonoscopy videos. - Zijie Yuan; Mohammadhassan Izadyyazdanabadi; Divya Mokkapati; Rujuta Panvalkar; Jae Y. Shin; Nima Tajbakhsh; Suryakanth R. Gurudu; Jianming Liang (Image Processing, 2017)

Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs. - Nima Tajbakhsh; Kenji Suzuki 001 (Pattern Recognit., 2017)

On the Necessity of Fine-Tuned Convolutional Neural Networks for Medical Imaging. - Nima Tajbakhsh; Jae Y. Shin; Suryakanth R. Gurudu; R. Todd Hurst; Christopher B. Kendall; Michael B. Gotway; Jianming Liang (Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017)

Reduction in training time of a deep learning model in detection of lesions in CT. - Nazanin Makkinejad; Nima Tajbakhsh; Amin Zarshenas; Ashfaq Khokhar 001; Kenji Suzuki 001 (Computer-Aided Diagnosis, 2018)

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)

UNet++: A Nested U-Net Architecture for Medical Image Segmentation. - Zongwei Zhou; Md Mahfuzur Rahman Siddiquee; Nima Tajbakhsh; Jianming Liang (DLMIA/ML-CDS@MICCAI, 2018)

Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization. - Md Mahfuzur Rahman Siddiquee; Zongwei Zhou; Nima Tajbakhsh; Ruibin Feng; Michael B. Gotway; Yoshua Bengio; Jianming Liang (ICCV, 2019)

Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data. - Nima Tajbakhsh; Yufei Hu; Junli Cao; Xingjian Yan; Yi Xiao; Yong Lu; Jianming Liang; Demetri Terzopoulos; Xiaowei Ding (ISBI, 2019)

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis. - Zongwei Zhou; Vatsal Sodha; Md Mahfuzur Rahman Siddiquee; Ruibin Feng; Nima Tajbakhsh; Michael B. Gotway; Jianming Liang (MICCAI (4), 2019)

Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. - Nima Tajbakhsh; Jae Y. Shin; Michael B. Gotway; Jianming Liang (Medical Image Anal., 2019)

ErrorNet: Learning Error Representations from Limited Data to Improve Vascular Segmentation. - Nima Tajbakhsh; Brian Lai; Shilpa P. Ananth; Xiaowei Ding (ISBI, 2020)

Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts. - Gaurav Fotedar; Nima Tajbakhsh; Shilpa P. Ananth; Xiaowei Ding (MICCAI (1), 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)

Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE). - Germán González; Daniel Jimenez-Carretero; Sara Rodríguez-López; Carlos Cano-Espinosa; Miguel Cazorla; Tanya Agarwal; Vinit Agarwal; Nima Tajbakhsh; Michael B. Gotway; Jianming Liang; Mojtaba Masoudi; Noushin Eftekhari; et al. (CoRR, 2020)

Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation. - Nima Tajbakhsh; Laura Jeyaseelan; Qian Li; Jeffrey N. Chiang; Zhihao Wu; Xiaowei Ding (Medical Image Anal., 2020)

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation. - Zongwei Zhou; Md Mahfuzur Rahman Siddiquee; Nima Tajbakhsh; Jianming Liang (IEEE Trans. Medical Imaging, 2020)

A Location-Sensitive Local Prototype Network For Few-Shot Medical Image Segmentation. - Qinji Yu; Kang Dang; Nima Tajbakhsh; Demetri Terzopoulos; Xiaowei Ding (ISBI, 2021)

Guest Editorial Annotation-Efficient Deep Learning: The Holy Grail of Medical Imaging. - Nima Tajbakhsh; Holger Roth; Demetri Terzopoulos; Jianming Liang (IEEE Trans. Medical Imaging, 2021)

MDT-Net: Multi-domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan. - Weinan Song; Gaurav Fotedar; Nima Tajbakhsh; Ziheng Zhou; Xiaowei Ding (CoRR, 2022)

MDT-Net: Multi-Domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan. - Weinan Song; Gaurav Fotedar; Nima Tajbakhsh; Ziheng Zhou; Lei He 001; Xiaowei Ding (ISBI, 2023)

SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs. - Shengzhi Li; Nima Tajbakhsh (CoRR, 2023)

Llama 3 Meets MoE: Efficient Upcycling. - Aditya Vavre; Ethan He; Dennis Liu; Zijie Yan; June Yang; Nima Tajbakhsh; Ashwath Aithal (CoRR, 2024)

Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. - Rohit Jena; Ali Taghibakhshi; Sahil Jain; Gerald Shen; Nima Tajbakhsh; Arash Vahdat (WACV, 2025)

Training Video Foundation Models with NVIDIA NeMo. - Zeeshan Patel; Ethan He; Parth Mannan; Xiaowei Ren; Ryan Wolf; Niket Agarwal; Jacob Samuel Huffman; Zhuoyao Wang; Carl Wang; Jack Chang; Yan Bai; Tommy Huang; et al. (CoRR, 2025)

Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning. - Ali Taghibakhshi; Sharath Turuvekere Sreenivas; Saurav Muralidharan; Marcin Chochowski; Yashaswi Karnati; Raviraj Joshi; Ameya Sunil Mahabaleshwarkar; Zijia Chen; Yoshi Suhara; Oluwatobi Olabiyi; Daniel Korzekwa; Mostofa Patwary; et al. (CoRR, 2025)