Ge Precision Healthcare LLC

Jurgen Germann

Thomas Kwok-Fah Foo

Andres M Lozano

Desmond Teck Beng Yeo

John Karigiannis

Radhika Madhavan

Afis Ajala

Alexandre Boutet

Jianwei Qiu

A system for optimizing DBS parameters for a subject includes automatically performing actions via a processor. The actions include obtaining functional MRI data of a brain of the subject acquired utilizing an MRI system during DBS of the brain utilizing a first set of DBS parameters. The actions include generating functional MRI response maps from the functional MRI data. The actions include extracting, utilizing an unsupervised autoencoder-based neural network, features from the functional MRI response maps. The actions include determining, utilizing a deep learning-based DBS parameter classification model, whether the first set of DBS parameters are optimal DBS parameters for the subject based on the features. The actions include, when the first set of DBS parameters are not the optimal DBS parameters, predicting, utilizing a deep learning-based DBS parameter prediction model, a second set of DBS parameters that are the optimal DBS parameters for the subject based on the features.

Deep learning-based automated parameter optimization and therapy system for deep brain stimulation

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Toronto, Canada

Jurgen Germann