Bleeding recognition technique in wireless capsule endoscopy images using fuzzy logic and principal component analysis

A. Al Mamun, P. P. Em, T. Ghosh, M. M. Hossain, M. G. Hasan, M. G. Sadeque


Wireless Capsule Endoscopy is the most innovative technology to perceive the entire gastrointestinal (GI) tract in recent times. It can diagnose inner diseases like bleeding, ulcer, tumor, Crohn's disease, polyps, etc. in a discretion way. It creates immense pressure and onus for clinicians for the sack of perceiving a huge number of image frames, which is time-consuming and also makes human oversight errors. Therefore a computer-automated system has been introduced for bleeding detection. A unique fuzzy logic technique is proposed to extract the specified bleeding and non-bleeding information from the image data. A particular Quadratic Support Vector Machine (QSVM) classifier is employed to classify the obtained statistical features from the bleeding and non-bleeding images incorporating Principal Component Analysis (PCA). After extensive experiments on clinical data, 98% sensitivity, 98.4% accuracy, 98% specificity, 93% precision, 95.4% F1-score, and 99% negative predicted value have been achieved, which outperforms some of the states of art methods in this regard. It is optimistic that the proposed methodology would bring a significant contribution to bleeding detection techniques and diminish the additional onus of the physicians.


bleeding detection; fuzzy logic; principal component analysis; gastrointestinal tract; QSVM; wireless capsule endoscopy;

Total views : 0 times

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

ISSN 2088-8708, e-ISSN 2722-2578