Title :
Expert system for patient realignment in MRI [magnetic resonance imaging]
Author :
Young, H.S. ; Dalton, B. ; Saeed, N. ; Marshall, S. ; Durrani, T.S.
Author_Institution :
Dept. of Electr. & Electron., Eng., Strathclyde Univ., Glasgow, UK
Abstract :
Describes an approach for carrying out automatic patient realignment using a completely separate knowledge based system which calls on a series of low level image/signal analysis tools to extract low level features from the images. These features are compared using the knowledge based expert system to measure and then correct the positional inaccuracies. Higher level features such as the labyrinth and individual sulci can then be extracted and used to fine tune the realignment. While the feature extraction and image analysis operations are implemented in a standard numerical programming language, the symbolic reasoning is carried out using an expert system shell. The authors discuss some of the reasons for adopting this type of approach and describe how breaking the problem up as an intelligent overseer driving a series of low level image processing algorithms, has led and guided the work
Keywords :
biomedical NMR; computerised picture processing; expert systems; automatic patient realignment; expert system; feature extraction; image analysis; individual sulci; intelligent overseer; knowledge based system; labyrinth; magnetic resonance imaging; symbolic reasoning;
Conference_Titel :
Application of Artificial Intelligence Techniques to Signal Processing , IEE Colloquium on
Conference_Location :
London