Charlie Budd

According to our database, Charlie Budd authored at least 9 papers between 2022 and 2025.

Collaborative distances:

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

2025

SurgPIS: Surgical-instrument-level Instances and Part-level Semantics for Weakly-supervised Part-aware Instance Segmentation.

Meng Wei, Charlie Budd, Oluwatosin Alabi, Miaojing Shi, Tom Vercauteren

CoRR, July, 2025

X-RAFT: Cross-Modal Non-Rigid Registration of Blue and White Light Neurosurgical Hyperspectral Images.

Charlie Budd, Silvère Ségaud, Matthew Elliot, Graeme Stasiuk, Yijing Xie, Jonathan Shapey, Tom Vercauteren

CoRR, July, 2025

2024

Scribble-Based Interactive Segmentation of Medical Hyperspectral Images.

Zhonghao Wang, Junwen Wang, Charlie Budd, Oscar MacCormac, Jonathan Shapey, Tom Vercauteren

CoRR, 2024

CholecInstanceSeg: A Tool Instance Segmentation Dataset for Laparoscopic Surgery.

Oluwatosin Alabi, Ko Ko Zayar Toe, Zijian Zhou, Charlie Budd, Nicholas Raison, Miaojing Shi, Tom Vercauteren

CoRR, 2024

Transferring Relative Monocular Depth to Surgical Vision with Temporal Consistency.

Charlie Budd, Tom Vercauteren

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

2023

Rapid and robust endoscopic content area estimation: a lean GPU-based pipeline and curated benchmark dataset.

Charlie Budd, Luis C. García-Peraza-Herrera, Martin Huber, Sébastien Ourselin, Tom Vercauteren

Comput. methods Biomech. Biomed. Eng. Imaging Vis., July, 2023

SegMatch: A semi-supervised learning method for surgical instrument segmentation.

Meng Wei, Charlie Budd, Luis C. García-Peraza-Herrera, Reuben Dorent, Miaojing Shi, Tom Vercauteren

CoRR, 2023

Deep Reinforcement Learning Based System for Intraoperative Hyperspectral Video Autofocusing.

Charlie Budd, Jianrong Qiu, Oscar MacCormac, Martin Huber, Christopher E. Mower, Mirek Janatka, Théo Trotouin, Jonathan Shapey, Mads S. Bergholt, Tom Vercauteren

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022

MONAI: An open-source framework for deep learning in healthcare.

M. Jorge Cardoso, Wenqi Li, Richard Brown, Nic Ma, Eric Kerfoot, Yiheng Wang, Benjamin Murray, Andriy Myronenko, Can Zhao, Dong Yang, Vishwesh Nath, Yufan He, Ziyue Xu, Ali Hatamizadeh, Wentao Zhu, Yun Liu, Mingxin Zheng, Yucheng Tang, Isaac Yang, Michael Zephyr, Behrooz Hashemian, Sachidanand Alle, Mohammad Zalbagi Darestani, Charlie Budd, Marc Modat, Tom Vercauteren, Guotai Wang, Yiwen Li, Yipeng Hu, Yunguan Fu, Benjamin Gorman, Hans J. Johnson, Brad W. Genereaux, Barbaros S. Erdal, Vikash Gupta, Andres Diaz-Pinto, Andre Dourson, Lena Maier-Hein, Paul F. Jaeger, Michael Baumgartner, Jayashree Kalpathy-Cramer, Mona Flores, Justin S. Kirby, Lee A. D. Cooper, Holger R. Roth, Daguang Xu, David Bericat, Ralf Floca, S. Kevin Zhou, Haris Shuaib, Keyvan Farahani, Klaus H. Maier-Hein, Stephen R. Aylward, Prerna Dogra, Sébastien Ourselin, Andrew Feng

CoRR, 2022