SurgiSR4K: A High-Resolution Endoscopic Video Dataset for Robotic-Assisted Minimally Invasive Procedures
Fengyi Jiang, Xiaorui Zhang, Lingbo Jin, Ruixing Liang, Yuxin Chen, Adi Chola Venkatesh, Jason Culman, Tiantian Wu, Lirong Shao, Wenqing Sun, Cong Gao, Hallie McNamara, Jingpei Lu, Omid Mohareri

TL;DR
SurgiSR4K is the first publicly available native 4K surgical video dataset designed to improve computer vision tasks in robotic-assisted minimally invasive procedures.
Contribution
It introduces a diverse, high-resolution dataset capturing realistic surgical scenarios to facilitate research in high-res surgical imaging and related AI applications.
Findings
Enables development of super resolution and smoke removal techniques.
Supports training of surgical instrument detection and 3D tissue reconstruction.
Fosters advancements in vision-language models for surgical contexts.
Abstract
High-resolution imaging is crucial for enhancing visual clarity and enabling precise computer-assisted guidance in minimally invasive surgery (MIS). Despite the increasing adoption of 4K endoscopic systems, there remains a significant gap in publicly available native 4K datasets tailored specifically for robotic-assisted MIS. We introduce SurgiSR4K, the first publicly accessible surgical imaging and video dataset captured at a native 4K resolution, representing realistic conditions of robotic-assisted procedures. SurgiSR4K comprises diverse visual scenarios including specular reflections, tool occlusions, bleeding, and soft tissue deformations, meticulously designed to reflect common challenges faced during laparoscopic and robotic surgeries. This dataset opens up possibilities for a broad range of computer vision tasks that might benefit from high resolution data, such as super…
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