Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia
Bibliographic Data
To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia
Algorithm · Cognition · Dementia · Disease · Fluid-attenuated inversion recovery · Hyperintensity · Magnetic resonance imaging · Psychiatry · Radiology · Segmentation · Alzheimer's disease research and treatments · Computer Science · Dementia and Cognitive Impairment Research · Medicine · Neurological Disease Mechanisms and Treatments · Psychology · Artificial Intelligence · Internal Medicine
| Citation velocity | historical |
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| Highly cited | No |