Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia.
Gaubert M, Dell'Orco A, Lange C, Garnier-Crussard A, Zimmermann I, Dyrba M, Duering M, Ziegler G, Peters O, Preis L, Priller J, Spruth EJ, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Maier F, Glanz W, Buerger K, Janowitz D, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Munk MH, Spottke A, Roy N, Dobisch L, Ewers M, Dechent P, Haynes JD, Scheffler K, Düzel E, Jessen F, Wirth M; DELCODE study group.
Gaubert M, et al.
Front Psychiatry. 2023 Jan 12;13:1010273. doi: 10.3389/fpsyt.2022.1010273. eCollection 2022.
Front Psychiatry. 2023.
PMID: 36713907
Free PMC article.
Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared t …
Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), l …