An Automated Statistical Technique for Counting Distinct Multiple Sclerosis Lesions

Brain scan with lesions in different colors

This study introduces a novel technique for counting pathologically distinct lesions using cross-sectional data, and demonstrates its ability to recover obscured longitudinal information. The proposed count works by incorporating information about the texture of lesion probability maps. Compared to the commonly used connected components count, the proposed count more accurately reproduced gold-standard counts and correlated more closely with disability scores. Dworkin et al. (2018)

ABOUT PENNSIVE

The Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) consists of a group of statisticians studying etiology and clinical practice through medical imaging. 

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