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A Holistic Multimedia System for Gastrointestinal Tract Disease Detection

Authors: 

Konstantin Pogorelov, Sigrun Losada Eskeland, Thomas de Lange, Carsten Griwodz, Kristin Ranheim Randel, Håkon Kvale Stensland, Duc Tien Dang Nguyen, Concetto Spampinato, Dag Johansen, Michael Riegler, Pål Halvorsen

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
Analysis of medical videos for detection of abnormalities and dis- eases requires both high precision and recall, but also real-time processing for live feedback and scalability for massive screening of entire populations. Existing work on this field does not provide the necessary combination of retrieval accuracy and performance. In this paper, a multimedia system is presented where the aim is to tackle automatic analysis of videos from the human gastrointestinal (GI) tract. The system includes the whole pipeline from data collection, processing and analysis, to visualization. The system combines filters using machine learning, image recognition and extraction of global and local image features. Furthermore, it is built in a modular way so that it can easily be extended. At the same time, it is developed for efficient processing in order to provide real-time feedback to the doctors. Our experimental evaluation proves that our system has detection and localisation accuracy at least as good as existing systems for polyp detection, it is capable of detecting a wider range of diseases, it can analyse video in real-time, and it has a low resource consumption for scalability.
Conference Name: 
ACM Multimedia System 2017
Proceedings: 
ACM Multimedia System 2017
Digital Object Identifer (DOI): 
10.1145/3083187.3083189
Publication Date: 
20/06/2017
Conference Location: 
Taiwan, Province of China
Research Group: 
Institution: 
Dublin City University (DCU)
Open access repository: 
Yes