Multimodal MRI segmentation of ischemic stroke lesions

  title={Multimodal MRI segmentation of ischemic stroke lesions},
  author={Yasin Kabir and Michel Dojat and Barbara Scherrer and Catherine Garbay and F. Forbes},
  journal={2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
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… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 35 extracted citations

Automated ischemic lesion detection in a neonatal model of hypoxic ischemic injury.

Journal of magnetic resonance imaging : JMRI • 2011
View 4 Excerpts
Highly Influenced

Computer-assisted delineation of cerebral infarct from diffusion-weighted MRI using Gaussian mixture model

International Journal of Computer Assisted Radiology and Surgery • 2017
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 28 references

Economic evaluation in stroke rese arch

M. Evers et al
J Cerebrovasc Dis 2000;11:82–91 • 2000
View 4 Excerpts
Highly Influenced

A Robust Multidimensional Parametric Method to Segment MS Lesions in MRI

S Capelle
MICCAI • 2005

Based Tissue Segmentation and Partial Volume Effect Quantification in MultiSequence Brain MRI

M Evers
MICCAI 04 , Lecture Notes in ’ Computer Science Saint - Malo , France September • 2004

Hierarchical segmentation of multiple sclerosis lesions in multi-sequence MRI

2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821) • 2004

Similar Papers

Loading similar papers…