Simcol3D - 3D Reconstruction during Colonoscopy Challenge Dataset

Colorectal cancer is one of the most common cancers in the world. By establishing a benchmark, SimCol3D aimed to facilitate data-driven navigation during colonoscopy. More details about the challenge and corresponding data can be found in the challenge paper on arXiv. <br> The challenge consisted of simulated colonoscopy data and images from real patients. This data release encompasses the synthetic portion of the challenge. The synthetic data includes three different anatomies derived from real human CT scans. Each anatomy provides several randomly generated trajectories with RGB renderings, camera intrinsics, ground truth depths, and ground truth poses. In total, this dataset includes more than 37,000 labelled images. <br> The real colonoscopy data used in the SimCol3D challenge consists of images extracted from the EndoMapper dataset. The real data is available on the EndoMapper Synapse page. <br> The synthetic colonoscopy data is made available in this repository.

结直肠癌（Colorectal cancer）是全球范围内最为高发的癌症之一。SimCol3D旨在通过构建基准测试框架，为结肠镜检查过程中的数据驱动导航提供支撑。更多关于该挑战赛及对应数据集的细节，可查阅arXiv平台上的挑战赛官方论文。
本次挑战赛涵盖模拟结肠镜检查数据与真实患者临床影像。本数据集发布仅包含挑战赛中的合成数据子集。该合成数据基于三例经真实人体CT扫描重建的解剖模型生成，每个解剖模型均配套若干条随机生成的检查轨迹，附带RGB渲染图像、相机内参、真实深度真值与真实位姿真值。本数据集总计包含超过37000张标注图像。
SimCol3D挑战赛所使用的真实结肠镜检查数据，提取自EndoMapper数据集，相关真实数据可在EndoMapper的Synapse页面获取。
本仓库现已发布该合成结肠镜检查数据集。

搜集汇总

背景与挑战

背景概述

Simcol3D数据集是一个用于结肠镜检查期间3D重建的挑战数据集，包含合成数据和真实患者图像。合成数据部分基于真实人类CT扫描，提供超过37,000张标记图像，包括RGB渲染、相机内参、深度和姿态信息，旨在促进数据驱动的结肠镜检查导航。