Stereo Correspondence and Reconstruction of Endoscopic Data Challenge

TL;DR

This paper presents a challenge on stereo correspondence and 3D reconstruction of endoscopic data, including participating methods, results, and dataset issues, to advance medical imaging techniques.

Contribution

It introduces a structured challenge for dense depth estimation in endoscopic data, including new methods and dataset analysis, to improve surgical imaging accuracy.

Findings

Multiple methods evaluated on endoscopic stereo data

Identification of dataset issues affecting reconstruction quality

Benchmark results highlighting current state-of-the-art performance

Abstract

The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. The task was to perform dense depth estimation using 7 training datasets and 2 test sets of structured light data captured using porcine cadavers. These were provided by a team at Intuitive Surgical. 10 teams participated in the challenge day. This paper contains 3 additional methods which were submitted after the challenge finished as well as a supplemental section from these teams on issues they found with the dataset.