Abstract #1318
Adapting a white matter lesion segmentation algorithm for large cohort studies
Leonie Lampe 1,2 , Alexander Schaefer 1,3 , Christopher J. Steele 1 , Katrin Arlin 1,2 , Dominik Fritzsch 4 , Matthias L. Schroeter 1,2 , Arno Villringer 1,2 , and Pierre-Louis Bazin 1
1
Department of Neurology, Max Planck
Institute for Human Cognitive and Brain Sciences,
Leipzig, Germany,
2
Leipzig
Research Centre for Civilization Diseases & Clinic of
Cognitive Neurology, University of Leipzig, Germany,
3
Clinical
Imaging Research Centre & Singapore Institute for
Neurotechnology, National University of Singapore,
Singapore,
4
Department
of Neuroradiology, University Hospital Leipzig, Germany
Here we adapted and validated a lesion segmentation
algorithm previously aimed at MS lesions for white
matter lesions (WML) segmentation within the general
population. WML in the normal aging brain display
diversity in pattern, intensity and extent. By means of
iteratively re-normalising the contrast of the FLAIR
images to better separate lesions from healthy tissue a
dice coefficient of 0.63 was obtained. The validation
was performed with 5 subjects with diverse lesions. The
algorithm was applied to a large cohort study (age range
19-80 years) with approximately 1200 subjects.
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