Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025
Abstract
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms that will enable them. With these goals in mind we have invited the surgical data science community to participate in a yearly competition hosted through the Medical Imaging Computing and Computer Assisted Interventions (MICCAI) conference. With varying changes from year to year, we have challenged the community to solve difficult machine learning problems in the context of advanced RA applications. Here we document the results of these challenges, focusing on surgical tool localization (SurgToolLoc) and surgical visual understanding (SurgVU). The publicly released dataset that accompanies these challenges is detailed in a separate paper arXiv:2501.09209 [1].
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Cite
@article{arxiv.2305.07152,
title = {Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025},
author = {Aneeq Zia and Max Berniker and Rogerio Garcia Nespolo and Xiaorui Zhang and Conor Perreault and Kiran Bhattacharyya and Xi Liu and Ziheng Wang and Satoshi Kondo and Satoshi Kasai and Kousuke Hirasawa and Bo Liu and David Austin and Yiheng Wang and Michal Futrega and Jean-Francois Puget and Zhenqiang Li and Yoichi Sato and Ryo Fujii and Ryo Hachiuma and Mana Masuda and Hideo Saito and An Wang and Mengya Xu and Mobarakol Islam and Long Bai and Winnie Pang and Hongliang Ren and Chinedu Nwoye and Luca Sestini and Nicolas Padoy and Maximilian Nielsen and Samuel Schüttler and Thilo Sentker and Hümeyra Husseini and Ivo Baltruschat and Rüdiger Schmitz and René Werner and Aleksandr Matsun and Mugariya Farooq and Numan Saaed and Jose Renato Restom Viera and Mohammad Yaqub and Neil Getty and Fangfang Xia and Zixuan Zhao and Xiaotian Duan and Xing Yao and Ange Lou and Hao Yang and Jintong Han and Jack Noble and Jie Ying Wu and Tamer Abdulbaki Alshirbaji and Nour Aldeen Jalal and Herag Arabian and Ning Ding and Knut Moeller and Weiliang Chen and Quan He and Muhammad Bilal and Taofeek Akinosho and Adnan Qayyum and Massimo Caputo and Hunaid Vohra and Michael Loizou and Anuoluwapo Ajayi and Ilhem Berrou and Faatihah Niyi-Odumosu and Charlie Budd and Oluwatosin Alabi and Tom Vercauteren and Ruoxi Zhao and Ayberk Acar and John Han and Jumanh Atoum and Yinhong Qin and Surong Hua and Lu Ping and Wenming Wu and Rongfeng Wei and Jinlin Wu and You Pang and Zhen Chen and Tim Jaspers and Amine Yamlahi and Piotr Kalinowski and Dominik Michael and Tim Rädsch and Marco Hübner and Danail Stoyanov and Stefanie Speidel and Lena Maier-Hein and Jie Tian and Ruxin Zhang and Khang Hoang Nguyen and Anh Quoc Nguyen and Tam Minh Nguyen and Khoi Dinh Tran and Minh Nguyen Dang Nhat and Trinh Thi Doan Pham and Linh Van Nguyen and Chunyang Jiang and Dewei Yang and Haitao Li and Yannick Prudent and Thibaut Boissin and Mahmood Alam and Shazad Ashraf and Andrew D. Beggs and Lukman Akanbi and Manuel D. Delgado and Narain Gupta and Amir M. Hajiyavand and Iqbal Qasim and Hafiz A. Alaka and Junaid Qadir and Shu Yang and Yihui Wang and Hao Chen and Shin Paul and Yosuke Yamagishi and Zhang Dong and Hongyun Li and Hongyu Gu and Xiaoliu Ding and Xiaoyao Liu and Xingyu Zhao and Mariana Ribeiro and Tiago Jesus and André Ferreira and Guilherme Barbosa and João Carvalho and Leonardo Barroso and Nuno Gomes and Rafael Peixoto and Rodrigo Ralha and Victor Alves and Stephanie and Nattapat Ittikosil and Achita Chitrapan and Quan Huu Cap and Jiayuan Huang and Shreyas C Dhake and Sergi Kavtaradze and Mobarak I Hoque and Ka Young Kim and Su Yong Yun and Young Tae Kim and Hyeon Bae Kim and Seong Tae Kim and Zuxing Deng and Ling Li and Jieyu Zheng and Xiaojian Li and Anthony Jarc},
journal= {arXiv preprint arXiv:2305.07152},
year = {2026}
}