Multimodal MRI segmentation of ischemic stroke lesions.
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.
Kabir
Y
Y
INSERM U836-UJF-CEA-CHU, Grenoble Institute of Neuroscience. yacine.kabir@imag.fr
Dojat
M
M
Scherrer
B
B
Forbes
F
F
Garbay
C
C
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000473:pathology*; D002545:Brain Ischemia / Q000209:etiology / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D020521:Stroke / Q000150:complications / Q000473:pathology*; D013382:Subtraction Technique