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Updated: Jun 16, 2026
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
Published on: September 25, 2019
New multispectral MRI data fusion technique for white matter lesion segmentation: method and comparison with
Maria del C Valdés Hernández1, Karen J Ferguson, Francesca M Chappell
1SFC Brain Imaging Research Centre, SINAPSE Collaboration, Division of Clinical Neurosciences, School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK. mvhernan@staffmail.ed.ac.uk
Objective:
Brain tissue segmentation by conventional threshold-based techniques may have limited accuracy and repeatability in older subjects. We present a new multispectral magnetic resonance (MR) image analysis approach for segmenting normal and abnormal brain tissue, including white matter lesions (WMLs).
Methods:
We modulated two 1.5T MR sequences in the red/green colour space and calculated the tissue volumes using minimum variance quantisation. We tested it on 14 subjects, mean age 73.3 +/- 10 years, representing the full range of WMLs and atrophy. We compared the results of WML segmentation with those using FLAIR-derived thresholds, examined the effect of sampling location, WML amount and field inhomogeneities, and tested observer reliability and accuracy.
Results:
FLAIR-derived thresholds were significantly affected by the location used to derive the threshold (P = 0.0004) and by WML volume (P = 0.0003), and had higher intra-rater variability than the multispectral technique (mean difference +/- SD: 759 +/- 733 versus 69 +/- 326 voxels respectively). The multispectral technique misclassified 16 times fewer WMLs.
Conclusion:
Initial testing suggests that the multispectral technique is highly reproducible and accurate with the potential to be applied to routinely collected clinical MRI data.
