Efficiency comparison of selected endoscopic video analysis algorithms
Department of Computer Architecture, Gda´nsk University of Technology, Poland
|Related article at Pubmed, Scholar Google|
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%.