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2017 | Supplement | Chapter

A Bag-of-Features Approach to Predicting TMS Language Mapping Results from DSI Tractography

Authors : Mohammad Khatami, Katrin Sakreida, Georg Neuloh, Thomas Schultz

Published in: Medical Image Computing and Computer Assisted Intervention − MICCAI 2017

Publisher: Springer International Publishing

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Abstract

Transcranial Magnetic Stimulation (TMS) can be used to indicate language-related cortex by highly focal temporary inhibition. Diffusion Spectrum Imaging (DSI) reconstructs fiber tracts that connect specific cortex regions. We present a novel machine learning approach that predicts a functional classification (TMS) from local structural connectivity (DSI), and a formal statistical hypothesis test to detect a significant relationship between brain structure and function. Features are chosen so that their weights in the classifier provide insight into anatomical differences that may underlie specificity in language functions. Results are reported for target sites systematically covering Broca’s region, which constitutes a core node in the language network.

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Appendix
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Metadata
Title
A Bag-of-Features Approach to Predicting TMS Language Mapping Results from DSI Tractography
Authors
Mohammad Khatami
Katrin Sakreida
Georg Neuloh
Thomas Schultz
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-66182-7_74

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