The Kvasir Dataset
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/
Variants: Kvasir-SEG, Kvasir
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Image Classification | HiFuse_Small | HiFuse: Hierarchical Multi-Scale Feature Fusion … | 2022-09-21 |
Image Classification | HiFuse_Tiny | HiFuse: Hierarchical Multi-Scale Feature Fusion … | 2022-09-21 |
Image Classification | HiFuse_Base | HiFuse: Hierarchical Multi-Scale Feature Fusion … | 2022-09-21 |
Recent papers with results on this dataset: