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Multimodal MRI segmentation of ischemic stroke lesions

Yacine Kabir 1 Michel Dojat 1, * Benoît Scherrer 1 Florence Forbes 2 Catherine Garbay 3
* Corresponding author
2 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
3 MAGMA - Modélisation d’agents autonomes en univers multi-agents
LIG - Laboratoire d'Informatique de Grenoble
Abstract : The problem addressed in this paper is the automatic segmentation of stroke lesions on MR multi-sequences. Lesions enhance differently depending on the MR modality and there is an obvious gain in trying to account for various sources of information in a single procedure. To this aim, we propose a multimodal Markov random field model which includes all MR modalities simultaneously. The results of the multimodal method proposed are compared with those obtained with a mono-dimensional segmentation applied on each MRI sequence separately. We constructed an Atlas of blood supply territories to help clinicians in the determination of stroke subtypes and potential functional deficit.
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Yacine Kabir, Michel Dojat, Benoît Scherrer, Florence Forbes, Catherine Garbay. Multimodal MRI segmentation of ischemic stroke lesions. EMBS 2007 - 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Aug 2007, Lyon, France. pp.1595-1598, ⟨10.1109/IEMBS.2007.4352610⟩. ⟨inserm-00402278⟩

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