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.
CONCLUSION: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. ...
CONCLUSION: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the pe …