AuthorsS. Hicks, A. Petlund, T. de Lange, P. T. Schmidt, P. Halvorsen, M. Riegler, P. Smedsrud, T. B. Haugen, K. R. Randel, K. Pogorelov et al.
EditorsM. Larson, G. Gravier, H. Hung, C. Ngo and W. T. Ooi
TitleACM Multimedia BioMedia 2019 Grand Challenge Overview
AfilliationMachine Learning
Project(s)Department of Holistic Systems
StatusPublished
Publication TypeProceedings, refereed
Year of Publication2019
Conference NameThe ACM International Conference on Multimedia (ACM MM)
Date Published10/2019
PublisherACM Press
Place PublishedNice, FranceNew York, New York, USA
ISBN Number9781450368896
Abstract

The BioMedia 2019 ACM Multimedia Grand Challenge is the first in a series of competitions focusing on the use of multimedia for different medical use-cases. In this year’s challenge, the participants are asked to develop efficient algorithms which automatically detect a variety of findings commonly identified in the gastrointestinal (GI) tract (a part of the human digestive system). The purpose of this task is to develop methods to aid medical doctors performing routine endoscopy inspections of the GI tract. In this paper, we give a detailed description of the four different tasks of this year’s challenge, present the datasets used for training and testing, and discuss how each submission is evaluated both qualitatively and quantitatively.

URLhttp://dl.acm.org/citation.cfm?doid=3343031http://dl.acm.org/citation.cfm?doid=3343031.3356058http://dl.acm.org/ft_gateway.cfm?id=3356058&ftid=2092095&dwn=1
DOI10.1145/334303110.1145/3343031.3356058
Citation Key26858