Kvasir

The Kvasir Dataset

Dataset Information
Modalities
Images, Videos
Languages
Chinese
Introduced
2017
Homepage

Overview

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

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

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

Research Papers

Recent papers with results on this dataset: