Generalized image models and their application as statistical models of images

A generalized image model (GIM) is presented. Images are represented as sets of four-dimensional (4D) sites combining position and intensity information, as well as their associated uncertainty and joint variation. This model seamlessly allows for the representation of both images and statistical mo...

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Bibliographic Details
Published in:Medical image analysis 2004-09, Vol.8 (3), p.361-369
Main Authors: González Ballester, Miguel Ángel, Pennec, Xavier, George Linguraru, Marius, Ayache, Nicholas
Format: Article
Language:English
Subjects:
Algorithms
Bioengineering
Brain - anatomy & histology
Brain Mapping - methods
Computer Science
Engineering Sciences
Generalized image models
Humans
ICP
Image Processing, Computer-Assisted - methods
Imaging
Kalman filter
Life Sciences
Magnetic Resonance Imaging
Medical Imaging
Modeling and Simulation
Models, Statistical
Registration
Signal and Image processing
Statistical shape models
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Summary:A generalized image model (GIM) is presented. Images are represented as sets of four-dimensional (4D) sites combining position and intensity information, as well as their associated uncertainty and joint variation. This model seamlessly allows for the representation of both images and statistical models (such as those used for classification of normal/abnormal anatomy and for inter-patient registration), as well as other representations such as landmarks or meshes. A GIM-based registration method aimed at the construction and application of statistical models of images is proposed. A procedure based on the iterative closest point (ICP) algorithm is modified to deal with features other than position and to integrate statistical information. Furthermore, we modify the ICP framework by using a Kalman filter to efficiently compute the transformation. The initialization and update of the statistical model are also described. Preliminary results show the feasibility of the approach and its potentialities.
ISSN:1361-8415
1361-8423
DOI:10.1016/j.media.2004.06.012