Title :
Extracting clinical information from endoscopic capsule exams using MPEG-7 visual descriptors
Author :
Coimbra, M. ; Campos, P. ; Cunha, J. P Silva
Author_Institution :
Dept. of Electron. & Telecommun., Univ. of Aveiro, Aveiro, Portugal
fDate :
Nov. 30 2005-Dec. 1 2005
Abstract :
The endoscopic capsule is a recent technological breakthrough with high clinical importance. Exam analysis duration is its main setback, requiring an average of two hours from a trained specialist. Automation is required and this paper presents a topographic segmentation tool using low-level features that can reduce annotation times up to 15 minutes per exam. This is accomplished using Bayesian classifiers and MPEG-7 visual descriptors.
Keywords :
Bayes methods; endoscopes; feature extraction; image segmentation; information retrieval; medical image processing; Bayesian classifier; MPEG-7 visual descriptor; clinical information extraction; endoscopic capsule; topographic segmentation tool;
Conference_Titel :
Integration of Knowledge, Semantics and Digital Media Technology, 2005. EWIMT 2005. The 2nd European Workshop on the (Ref. No. 2005/11099)
Conference_Location :
London
Print_ISBN :
0-86341-595-4