By Topic

A Hybrid System Using Symbolic and Numeric Knowledge for the Semantic Annotation of Sulco-Gyral Anatomy in Brain MRI Images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ammar Mechouche ; INSERM/INRIA/ CNRS, Univ. of Rennes 1, Rennes, France ; Xavier Morandi ; Christine Golbreich ; Bernard Gibaud

This paper describes an interactive system for the semantic annotation of brain magnetic resonance images. The system uses both a numerical atlas and symbolic knowledge of brain anatomical structures depicted using the semantic Web standards. This knowledge is combined with graphical data, automatically extracted from the images by imaging tools. The annotations of parts of gyri and sulci, in a region of interest, rely on constraint satisfaction problem solving and description logics inferences. The system is run on a client-server architecture, using Web services and including a sophisticated visualization tool. An evaluation of the system was done using normal (healthy) and pathological cases. The results obtained so far demonstrate that the system produces annotations with high precision and quality.

Published in:

IEEE Transactions on Medical Imaging  (Volume:28 ,  Issue: 8 )