An object-based approach for detecting small brain lesions: Application to 
Virchow-Robin spaces

Descombes, X.; Kruggel, F.; Wollny, Gert; Gertz, H. J.

doi:10.1109/TMI.2003.823061

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An object-based approach for detecting small brain lesions: Application to Virchow-Robin spaces

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Kruggel, F.
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Descombes, X., Kruggel, F., Wollny, G., & Gertz, H. J. (2004). An object-based approach for detecting small brain lesions: Application to Virchow-Robin spaces. IEEE Transactions on Medical Imaging, 23(2), 246-255. doi:10.1109/TMI.2003.823061.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-9D4C-B

Abstract

This paper is concerned with the detection of multiple small brain lesions from magnetic resonance imaging (MRI) data. A model based on the marked point process framework is designed to detect Virchow-Robin spaces (VRSs). These tubular shaped spaces are due to retraction of the brain parenchyma from its supplying arteries. VRS are described by simple geometrical objects that are introduced as small tubular structures. Their radiometric properties are embedded in a data term. A prior model includes interactions describing the clustering property of VRS. A Reversible Jump Markov Chain Monte Carlo algorithm (RJMCMC) optimizes the proposed model, obtained by multiplying the prior and the data model. Example results are shown on T1-weighted MRI datasets of elderly subjects.