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Clinical deep brain stimulation region prediction using regression forests from high-field MRI

Publication ,  Conference
Kim, J; Duchin, Y; Sapiro, G; Vitek, J; Harel, N
Published in: Proceedings - International Conference on Image Processing, ICIP
December 9, 2015

This paper presents a prediction framework of brain subcortical structures which are invisible on clinical low-field MRI, learning detailed information from ultrahigh-field MR training data. Volumetric segmentation of Deep Brain Stimulation (DBS) structures within the Basal ganglia is a prerequisite process for reliable DBS surgery. While ultrahigh-field MR imaging (7 Tesla) allows direct visualization of DBS targeting structures, such ultrahigh-fields are not always clinically available, and therefore the relevant structures need to be predicted from the clinical data. We address the shape prediction problem with a regression forest, non-linearly mapping predictors to target structures with high confidence, exploiting ultrahigh-field MR training data. We consider an application for the subthalamic nucleus (STN) prediction as a crucial DBS target. Experimental results on Parkinson's patients validate that the proposed approach enables reliable estimation of the STN from clinical 1.5T MRI.

Duke Scholars

Published In

Proceedings - International Conference on Image Processing, ICIP

DOI

ISSN

1522-4880

Publication Date

December 9, 2015

Volume

2015-December

Start / End Page

2480 / 2484
 

Citation

APA
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MLA
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Kim, J., Duchin, Y., Sapiro, G., Vitek, J., & Harel, N. (2015). Clinical deep brain stimulation region prediction using regression forests from high-field MRI. In Proceedings - International Conference on Image Processing, ICIP (Vol. 2015-December, pp. 2480–2484). https://doi.org/10.1109/ICIP.2015.7351248
Kim, J., Y. Duchin, G. Sapiro, J. Vitek, and N. Harel. “Clinical deep brain stimulation region prediction using regression forests from high-field MRI.” In Proceedings - International Conference on Image Processing, ICIP, 2015-December:2480–84, 2015. https://doi.org/10.1109/ICIP.2015.7351248.
Kim J, Duchin Y, Sapiro G, Vitek J, Harel N. Clinical deep brain stimulation region prediction using regression forests from high-field MRI. In: Proceedings - International Conference on Image Processing, ICIP. 2015. p. 2480–4.
Kim, J., et al. “Clinical deep brain stimulation region prediction using regression forests from high-field MRI.” Proceedings - International Conference on Image Processing, ICIP, vol. 2015-December, 2015, pp. 2480–84. Scopus, doi:10.1109/ICIP.2015.7351248.
Kim J, Duchin Y, Sapiro G, Vitek J, Harel N. Clinical deep brain stimulation region prediction using regression forests from high-field MRI. Proceedings - International Conference on Image Processing, ICIP. 2015. p. 2480–2484.

Published In

Proceedings - International Conference on Image Processing, ICIP

DOI

ISSN

1522-4880

Publication Date

December 9, 2015

Volume

2015-December

Start / End Page

2480 / 2484