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Predicting behavioral variant frontotemporal dementia with pattern classification in multi-center structural MRI

Sebastian Meyer¹, Karsten Mueller¹, Katharina Stuke¹

¹Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Neuroimage. Clinical

|March 29, 2017

Summary

This summary is machine-generated.

This study shows that magnetic resonance imaging (MRI) can accurately predict behavioral variant frontotemporal dementia (bvFTD) in individual patients. This imaging approach may lead to personalized diagnostic strategies for early-onset dementia.

Failed At:

2026-06-19T13:46:44.943175+00:00

Keywords:

Atrophy Behavioral variant frontotemporal dementia Diagnostic criteria FEW, family wise error FTLD, frontotemporal lobar degeneration Frontotemporal lobar degeneration GMD, gray matter density MNI, Montreal Neurological Institute MPRAGE, magnetization-prepared rapid gradient echo MRI MRI, magnetic resonance imaging Pattern classification SVM, support vector machine VBM, voxel based morphometry bvFTD, behavioral variant frontotemporal dementia

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