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VISE affiliates win Best Paper Award at 2016 IEEE BHI

Posted by on Monday, June 13, 2016 in News.

Yuan Liu, PhD candidate in computer science, and Benoit Dawant, Cornelius Vanderbilt Professor of Engineering and Director of the Vanderbilt Institute in Surgery and Engineering, won the 2016 IEEE BHI Best Paper Award. The award was presented during the third IEEE EMBS International Conference on Biomedical and Health Informatics. The BHI is a special topic conference of the IEEE Engineering in Medicine and Biology Society. The main theme for BHI2016 was integrative informatics for precision and preventative medicine.

The paper, “Multi-Modal Learning Based Pre-Operative Targeting in Deep Brain Stimulation Procedures,” focuses on automatic targeting for surgical treatment of movement disorders such as Parkinson’s disease. Finding optimal target location for electrode implantation is crucial to maximize therapeutic benefits of such treatment. The proposed method exploits multi-contrast information from preoperative MR images and learns a statistical model of the target position from a large collection of previous patients. It achieves target localization at millimetric level of accuracy in unseen patients. It is advantageous to state-of-the-art techniques in terms of both accuracy and speed while operating on completely different principles. This opens new avenues for quality control functionality in existing clinical processing pipelines and the integration of “big data” techniques to advance current surgical practices.


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