C3VDv2提升结肠镜3D数据集真实感，助力算法训练与评估
C3VDv2 -- Colonoscopy 3D video dataset with enhanced realism
- 采用高保真硅胶结肠模型拍摄192段视频，含16.9万帧画面
- 提供169个视频的深度、法向量、光流等多维度真实标注
- 涵盖粪便、黏液、出血等复杂场景，适合评估3D重建算法
空间计算机视觉技术有望提升结肠镜诊断性能，但缺乏用于训练和验证的3D结肠镜数据集制约了其发展。本文推出高分辨率结肠镜3D视频数据集第二版C3VDv2，通过增强真实性，支持3D结肠重建算法的量化评估。共采集192段视频序列，总计169,371帧，基于60个独特高保真硅胶结肠模型。为169个结肠镜视频提供了真实深度、表面法向量、光流、遮挡、漫反射图、六自由度位姿、覆盖图及3D模型。另包含8段由胃肠科医生模拟筛查拍摄的视频，附带真实位姿标注。此外，还包含15段含结肠形变的视频，用于定性评估。C3VDv2模拟了多种复杂挑战场景：粪便残留、黏液池、出血、镜头遮挡、正视视角、快速相机运动等。其增强的真实感可促进3D重建算法更稳健、更具代表性的开发与评估。项目页面：https://durrlab.github.io/C3VDv2/
原文摘要 · Abstract (English)
Spatial computer vision techniques have the potential to improve the diagnostic performance of colonoscopy. However, the lack of 3D colonoscopy datasets for training and validation hinders their development. This paper introduces C3VDv2, the second version (v2) of the high-definition Colonoscopy 3D Video Dataset, featuring enhanced realism designed to facilitate the quantitative evaluation of 3D colon reconstruction algorithms. 192 video sequences totaling 169,371 frames were captured by imaging 60 unique, high-fidelity silicone colon phantom segments. Ground truth depth, surface normals, optical flow, occlusion, diffuse maps, six-degree-of-freedom pose, coverage map, and 3D models are provided for 169 colonoscopy videos. Eight simulated screening colonoscopy videos acquired by a gastroenterologist are provided with ground truth poses. Lastly, the dataset includes 15 videos with colon deformations for qualitative assessment. C3VDv2 emulates diverse and challenging scenarios for 3D reconstruction algorithms, including fecal debris, mucous pools, blood, debris obscuring the colonoscope lens, en-face views, and fast camera motion. The enhanced realism of C3VDv2 will allow for more robust and representative development and evaluation of 3D reconstruction algorithms. Project Page - https://durrlab.github.io/C3VDv2/
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