Automatic contrast enhancement of white matter lesions in flair MRI

Authors:
April Khademi;Anastasios Venetsanopoulos;Alan Moody
Affiliations:
Department of Electrical and Computer Engineering, University of Toronto, Canada;Department of Electrical and Computer Engineering, University of Toronto, Canada;Department of Electrical and Computer Engineering, University of Toronto, Canada
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

This work concerns the development of a novel contrast enhancement algorithm for FLAIR-weighted cerebral MRI with white matter lesions (WML). The proposed method utilizes both a robust estimate of edge magnitude and intensity values to discriminate between pathological and non-pathological information. These two features are combined through several transformations, such that WML are highlighted, and normal appearing white/gray matter are suppressed. The technique utilizes information solely computed from each image and thus adapts to the input image's characteristics. The results show a significant improvement of the contrast between white matter lesions and other brain tissue (average contrast improvement of 41.1%). To demonstrate the robustness of such an enhancement scheme for WML analysis, a threshold-based segmenter is applied, which extracts the WML with good results.