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Proceedings Paper

Probabilistic framework for subject-specific and population-based analysis of longitudinal changes and disease progression in brain MR images
Author(s): Annemie Ribbens; Jeroen Hermans; Frederik Maes; Dirk Vandermeulen; Paul Suetens
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Paper Abstract

Aging and many neurological diseases cause progressive changes in brain morphology. Both subject-specific detection and measurement of these changes, as well as their population-based analysis are of great interest in many clinical studies. Generally, both problems are handled separately. However, as population-based knowledge facilitates subject-specific analysis and vice versa, we propose a unified statistical framework for subject-specific and population-based analysis of longitudinal brain MR image sequences of subjects suffering from the same neurological disease. The proposed method uses a maximum a posteriori formulation and the expectation maximization algorithm to simultaneously and iteratively segment all images in separate tissue classes, construct a global probabilistic 3D brain atlas and non-rigidly deform the atlas to each of the images to guide their segmentation. In order to enable a population-based analysis of the disease progression, an intermediate 4D probabilistic brain atlas is introduced, representing a discrete set of disease progression stages. The 4D atlas is simultaneously constructed with the 3D brain atlas by incorporating assignments of each input image (voxelwise) to a particular disease progression stage in the statistical framework. Moreover, these assignments enable both temporal and spatial subject-specific disease progression analysis. This includes detecting delayed or advanced disease progression and indicating the affected regions. The method is validated on a publicly available data set on which it shows promising results.

Paper Details

Date Published: 11 March 2011
PDF: 9 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796219 (11 March 2011); doi: 10.1117/12.877543
Show Author Affiliations
Annemie Ribbens, Katholieke Univ. Leuven (Belgium)
Jeroen Hermans, Katholieke Univ. Leuven (Belgium)
Frederik Maes, Katholieke Univ. Leuven (Belgium)
Dirk Vandermeulen, Katholieke Univ. Leuven (Belgium)
Paul Suetens, Katholieke Univ. Leuven (Belgium)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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