Sigrun Losada Eskeland

TL;DR: KVASIR is a dataset containing images from inside the gastrointestinal (GI) tract that contains two categories of images related to endoscopic polyp removal and is important for research on both single and multi-disease computer aided detection.

TL;DR: The HyperKvasir dataset is presented, the largest image and video dataset of the gastrointestinal tract available today and can play a valuable role in developing better algorithms and computer-assisted examination systems not only for gastro- and colonoscopy, but also for other fields in medicine.

TL;DR: Nerthus, a dataset containing videos from inside the gastrointestinal (GI) tract, showing different degrees of bowel cleansing, is presented and invited multimedia researchers to contribute in the medical field by making systems automatically evaluate the quality of bowel cleaning for colonoscopy.

TL;DR: Initial experiments show that the complete end-to-end multimedia system presented has multi-class detection accuracy and polyp localization precision at least as good as state-of-the-art systems, and provides additional novelty in terms of real-time performance, low resource consumption and ability to extend with support for new classes of diseases.

TL;DR: Initial investigations into two use cases surrounding diseases of the gastrointestinal (GI) tract are conducted, where the detection of abnormalities provides the largest chance of successful treatment if the initial observation of disease indicators occurs before the patient notices any symptoms.