TY - GEN
T1 - An intelligent system to detect Crohn's disease inflammation in wireless capsule endoscopy videos
AU - Girgis, H. Z.
AU - Mitchell, B. R.
AU - Dassopoulos, T.
AU - Mullin, G.
AU - Hager, G.
PY - 2010/8/9
Y1 - 2010/8/9
N2 - A Wireless Capsule Endoscope (WCE) is a small device that is capable of acquiring thousands of images as it travels through the gastrointestinal track. WCE is becoming a widely accepted method which physicians use in the diagnosis of Crohn's disease, an inflammatory disease that occurs mainly in the small intestine. In this article we present a novel method to detect those images showing inflammation among the thousands of images acquired by the WCE. Further, our method is capable of delineating the inflammation region(s) in each detected frame. Our system utilizes the mean-shift algorithm to find centers of candidate regions that may show Crohn's disease inflammation. Then the system classifies these regions by a trained Support Vector Machine. We have trained, validated and tested our method on three mutually exclusive sets. Our system's testing accuracy, specificity and sensitivity are 87%, 93% and 80% respectively.
AB - A Wireless Capsule Endoscope (WCE) is a small device that is capable of acquiring thousands of images as it travels through the gastrointestinal track. WCE is becoming a widely accepted method which physicians use in the diagnosis of Crohn's disease, an inflammatory disease that occurs mainly in the small intestine. In this article we present a novel method to detect those images showing inflammation among the thousands of images acquired by the WCE. Further, our method is capable of delineating the inflammation region(s) in each detected frame. Our system utilizes the mean-shift algorithm to find centers of candidate regions that may show Crohn's disease inflammation. Then the system classifies these regions by a trained Support Vector Machine. We have trained, validated and tested our method on three mutually exclusive sets. Our system's testing accuracy, specificity and sensitivity are 87%, 93% and 80% respectively.
KW - Crohn's disease
KW - Inflammation detection and the mean shift algorithm
KW - Wireless capsule endoscopy
UR - http://www.scopus.com/inward/record.url?scp=77955220250&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77955220250&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2010.5490253
DO - 10.1109/ISBI.2010.5490253
M3 - Conference contribution
AN - SCOPUS:77955220250
SN - 9781424441266
T3 - 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings
SP - 1373
EP - 1376
BT - 2010 7th IEEE International Symposium on Biomedical Imaging
T2 - 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
Y2 - 14 April 2010 through 17 April 2010
ER -