Riegler, Michael, Lux, Mathias, Griwodz, Carsten, Spampinato, Concetto, de Lange, Thomas, Eskeland, Sigrun, Pogorelov, Konstantin, Tavanapong, Wallapak, Schmidt, Peter, Gurrin, Cathal ORCID: 0000-0003-2903-3968, Johansen, Dag ORCID: 0000-0001-7067-6477, Johansen, Håvard ORCID: 0000-0002-1637-7262 and Halvorsen, Pål (2016) Multimedia and medicine: teammates for better disease detection and survival. In: ACM Multimedia 2016, 15-19 Oct 2016, Amsterdam, Netherlands. ISBN 978-1-4503-3603-1
Abstract
Health care has a long history of adopting technology to save lives and improve the quality of living. Visual information is frequently applied for disease detection and assessment, and the established fields of computer vision and medical imaging provide essential tools. It is, however, a misconception that disease detection and assessment are provided exclusively by these fields and that they provide the solution for all challenges. Integration and analysis of data from several sources, real-time processing, and the assessment of usefulness for end-users are core competences of the multime- dia community and are required for the successful improvement of health care systems. For the benefit of society, the multimedia community should recognize the challenges of the medical world that they are uniquely qualified to address. We have conducted initial investigations into two use cases surrounding diseases of the gastrointestinal (GI) tract, where the detection of abnormali- ties provides the largest chance of successful treatment if the initial observation of disease indicators occurs before the patient notices any symptoms. Although such detection is typically provided vi- sually by applying an endoscope, we are facing a multitude of new multimedia challenges that differ between use cases. In real-time assistance for colonoscopy, we combine sensor information about camera position and direction to aid in detecting, investigate means for providing support to doctors in unobtrusive ways, and assist in reporting. In the area of large-scale capsular endoscopy, we investigate questions of scalability, performance and energy efficiency for the recording phase, and combine video summarization and retrieval questions for analysis.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Medical; |
Subjects: | Computer Science > Multimedia systems Medical Sciences > Health |
DCU Faculties and Centres: | Research Institutes and Centres > INSIGHT Centre for Data Analytics DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing |
Published in: | Proceedings of the 2016 ACM Conference on Multimedia. . ACM. ISBN 978-1-4503-3603-1 |
Publisher: | ACM |
Official URL: | http://dx.doi.org/10.1145/2964284.2976760 |
Copyright Information: | © 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 22422 |
Deposited On: | 02 Jul 2018 10:15 by Cathal Gurrin . Last Modified 15 Dec 2021 16:13 |
Documents
Full text available as:
Preview |
PDF (Conference Paper)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
6MB |
Metrics
Altmetric Badge
Dimensions Badge
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record