Autonomous Intraluminal Navigation Dataset

This is a dataset for lumen segmentation. The dataset is composed of 1,873 images taken from endoscopic videos of 10 different phantoms. For each endoscopic image there is its corresponding mask in png format. The dataset is divided by folders in train/val/test. The training and validation data is the one used for training the networks described in [1]. The test folder is composed of two folders from a single phantom case. For more details please check the referred publication associated with this dataset. 

[1]. J. F. Lazo et al., "Autonomous Intraluminal Navigation of a Soft Robot using Deep-Learning-based Visual Servoing," 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan, 2022, pp. 6952-6959, doi: 10.1109/IROS47612.2022.9982141.