This dataset consists of manually segmented 2D static upper airway images acquired at the University of Iowa 3T research scanner. The images were captured using a fast GRE sequence in the midsagittal
The dataset folder is divided into two parts. The first part is the Train dataset, which contains 900 Kvasir-SEG data sets and 550 CVC-ClinicDB data sets, with a total of 1450 training images. image i
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 i