Ureteroscopy Lumen Segmentation Dataset

This is a dataset for lumen segmentation. The dataset is composed of 1,754 endoscopic images from 23 patients undergoing Ureteroscopy. The dataset is composed of a total 2,187 endoscopic images with its respective masks highlighting the lumen in .png format. The dataset is divided by folders in train/val/test, train and val folders are divided in two sub-folders (image / label) For each image there is a corresponding mask with the same name. The training and validation data is the one described in [1]. The test folder is composed of 3 patient cases, test_01, test_02 and test_03. For more details please check the referred publication associated with this dataset. J. F. Lazo et al., "A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture," 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, 2021, pp. 9203-9210, doi: 10.1109/ICPR48806.2021.9411924.