Colorectal Gland Segmentation:

Kvasir-SEG is an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated by a medical doctor and then verified by an experienced gastroenterologist. Source: Kvasir-SEG: A Segmented Polyp Dataset Image Source: https://datasets.simula.no/kvasir-seg/

The STARE (Structured Analysis of the Retina) dataset is a dataset for retinal vessel segmentation. It contains 20 equal-sized (700×605) color fundus images. For each image, two groups of annotations are provided.. Source: DPN: Detail-Preserving Network with High Resolution Representation for Efficient Segmentation of Retinal Vessels Image Source: https://www.researchgate.net/figure/Results-of-the-different-methods-applied-to-the-STARE-dataset-a-original-image-b_fig4_279215756

The KVASIR Dataset was released as part of the medical multimedia challenge presented by MediaEval. It is based on images obtained from the GI tract via an endoscopy procedure. The dataset is composed of images that are annotated and verified by medical doctors, and captures 8 different classes. The classes are based on three anatomical landmarks (z-line, pylorus, cecum), three pathological findings (esophagitis, polyps, ulcerative colitis) and two other classes (dyed and lifted polyps, dyed resection margins) related to the polyp removal process. Overall, the dataset contains 8,000 endoscopic images, with 1,000 image examples per class. Source: Two-Stream Deep Feature Modelling for Automated Video Endoscopy Data Analysis Image Source: https://datasets.simula.no/kvasir/