TY - GEN
T1 - A training based Support Vector Machine technique for blood detection in wireless capsule endoscopy images
AU - Li, Jie
AU - Ma, Jinwen
AU - Tillo, Tammam
AU - Zhang, Bailing
AU - Lim, Eng Gee
PY - 2012
Y1 - 2012
N2 - Wireless capsule endoscopy (WCE) is a non-invasive technique which could detect variety of abnormalities in the small bowel. However, in many cases it is difficult for doctors to distinguish obscure gastrointestinal bleeding of patients; moreover, the diagnosis process of the obtained video could take long time due to the huge number of generated frames. This project provides a method to automatically detect bleeding areas in the WCE images by using Support Vector Machine (SVM) classifier as the main engine with learning based mechanism in order to increase the accuracy. The experiment results show that this could not only advance the accuracy of WCE diagnosis, but also reduce the diagnosis time effectively. To further improve the performance of the proposed approach the length of the learning-based database was also tuned1.
AB - Wireless capsule endoscopy (WCE) is a non-invasive technique which could detect variety of abnormalities in the small bowel. However, in many cases it is difficult for doctors to distinguish obscure gastrointestinal bleeding of patients; moreover, the diagnosis process of the obtained video could take long time due to the huge number of generated frames. This project provides a method to automatically detect bleeding areas in the WCE images by using Support Vector Machine (SVM) classifier as the main engine with learning based mechanism in order to increase the accuracy. The experiment results show that this could not only advance the accuracy of WCE diagnosis, but also reduce the diagnosis time effectively. To further improve the performance of the proposed approach the length of the learning-based database was also tuned1.
KW - Support Vector Machine
KW - Wireless capsule endoscopy
KW - bleeding detection
KW - learning based mechanism
UR - http://www.scopus.com/inward/record.url?scp=84876774920&partnerID=8YFLogxK
U2 - 10.1109/IECBES.2012.6498194
DO - 10.1109/IECBES.2012.6498194
M3 - Conference Proceeding
AN - SCOPUS:84876774920
SN - 9781467316668
T3 - 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012
SP - 826
EP - 830
BT - 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012
T2 - 2012 2nd IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012
Y2 - 17 December 2012 through 19 December 2012
ER -