Abstract

Abstract FLAIR images are usually acquired in the context of multiple sclerosis (MS) because lesions appear hyperintense in this particular image weight. However, their intensity profile overlaps with white matter (WM) and gray matter (GM) tissues, posing difficulties for accurate segmentation. We propose a lesion enhancement technique to dim down WM and GM regions and highlight hyperintensities by creating a hyperintensity probability map. A byproduct of our proposal is the estimation of a mask encompassing WM and MS lesions. We observed that the lesion intensity profile in FLAIR was 25% and 19% brighter than WM and GM, respectively; comparatively, the same profile in our enhanced images was 444% and 264% brighter. On the mask estimation, we achieved a sensitivity of 99% and specificity of 98%. The results indicate significant improvement in the intensity distinction between lesions and tissues and can aid both experts and automated techniques in segmentation tasks.

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