Search
Abstract
In the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in an unified manner on a common, large movie database of real endoscopy videos. The test results often do not seem to confirm the high efficiency declared by their authors. A maximum of 80% sensitivity and specificity was achieved, while the authors often declared as much as 90%.
Cite as
Full text
download paper
downloaded 29 times
- Publication version
- Accepted or Published Version
- License
-
open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
- Published in:
-
International Journal of Innovative Research in Computer and Communication Engineering
no. 2,
edition 8,
pages 5304 - 5310,
ISSN: 2320-9798 - Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Cychnerski J.: Efficiency comparison of selected endoscopic video analysis algorithms// International Journal of Innovative Research in Computer and Communication Engineering. -Vol. 2., iss. 8 (2014), s.5304-5310
- Verified by:
- Gdańsk University of Technology
seen 88 times