Tyler J. Bradshaw

According to our database, Tyler J. Bradshaw authored at least 16 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

PETAR: Localized Findings Generation with Mask-Aware Vision-Language Modeling for PET Automated Reporting.

Danyal Maqbool, Changhee Lee, Zachary Huemann, Samuel Church, Matthew E. Larson, Scott B. Perlman, Tomas A. Romero, Joshua D. Warner, Meghan G. Lubner, Xin Tie, Jameson Merkow, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw

CoRR, October, 2025

From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification.

Xue Li, Jameson Merkow, Noel C. F. Codella, Alberto Santamaría-Pang, Naiteek Sangani, Alexander Ersoy, Christopher Burt, John W. Garrett, Richard J. Bruce, Joshua D. Warner, Tyler J. Bradshaw, Ivan Tarapov, Matthew P. Lungren, Alan B. McMillan

CoRR, May, 2025

Vision-Language Modeling in PET/CT for Visual Grounding of Positive Findings.

Zachary Huemann, Samuel Church, Joshua D. Warner, Daniel Tran, Xin Tie, Alan B. McMillan, Junjie Hu, Steve Y. Cho, Meghan G. Lubner, Tyler J. Bradshaw

CoRR, February, 2025

COMMA: A Communicative Multimodal Multi-Agent Benchmark.

Timothy Ossowski, Danyal Maqbool, Jixuan Chen, Zefan Cai, Tyler J. Bradshaw, Junjie Hu

Trans. Mach. Learn. Res., 2025

2024

Personalized Impression Generation for PET Reports Using Large Language Models.

Xin Tie, Muheon Shin, Ali Pirasteh, Nevein Ibrahim, Zachary Huemann, Sharon M. Castellino, Kara M. Kelly, John W. Garrett, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw

J. Imaging Inform. Medicine, 2024

ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax.

Zachary Huemann, Xin Tie, Junjie Hu, Tyler J. Bradshaw

J. Imaging Inform. Medicine, 2024

Nuclear Medicine Artificial Intelligence in Action: The Bethesda Report (AI Summit 2024).

Arman Rahmim, Tyler J. Bradshaw, Guido Davidzon, Joyita Dutta, Georges El Fakhri, Munir Ghesani, Nicolas A. Karakatsanis, Quanzheng Li, Chi Liu, Emilie Roncali, Babak Saboury, Tahir Yusufaly, Abhinav K. Jha

CoRR, 2024

Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network.

Xin Tie, Muheon Shin, Changhee Lee, Scott B. Perlman, Zachary Huemann, Amy J. Weisman, Sharon M. Castellino, Kara M. Kelly, Kathleen M. McCarten, Adina L. Alazraki, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw

CoRR, 2024

Deep Learning for Longitudinal Gross Tumor Volume Segmentation in MRI-Guided Adaptive Radiotherapy for Head and Neck Cancer.

Xin Tie, Weijie Chen, Zachary Huemann, Brayden Schott, Nuohao Liu, Tyler J. Bradshaw

Proceedings of the Head and Neck Tumor Segmentation for MR-Guided Applications, 2024

Knowledge-Grounded Adaptation Strategy for Vision-Language Models: Building a Unique Case-Set for Screening Mammograms for Residents Training.

Aisha Urooj Khan, John W. Garrett, Tyler J. Bradshaw, Lonie Salkowski, Jiwoong Jason Jeong, Amara Tariq, Imon Banerjee

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023

Anatomy and Physiology of Artificial Intelligence in PET Imaging.

Tyler J. Bradshaw, Alan B. McMillan

CoRR, 2023

Automatic Personalized Impression Generation for PET Reports Using Large Language Models.

Xin Tie, Muheon Shin, Ali Pirasteh, Nevein Ibrahim, Zachary Huemann, Sharon M. Castellino, Kara M. Kelly, John W. Garrett, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw

CoRR, 2023

ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax.

Zachary Huemann, Junjie Hu, Tyler J. Bradshaw

CoRR, 2023

Domain-adapted large language models for classifying nuclear medicine reports.

Zachary Huemann, Changhee Lee, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw

CoRR, 2023

On the effect of training database size for MR-based synthetic CT generation in the head.

Seyed Iman Zare Estakhraji, Ali Pirasteh, Tyler J. Bradshaw, Alan B. McMillan

Comput. Medical Imaging Graph., 2023

2022

Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine - The Bethesda Report (AI Summit 2022).

Arman Rahmim, Tyler J. Bradshaw, Irène Buvat, Joyita Dutta, Abhinav K. Jha, Paul E. Kinahan, Quanzheng Li, Chi Liu, Melissa D. McCradden, Babak Saboury, Eliot L. Siegel, John J. Sunderland, Richard L. Wahl

CoRR, 2022