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Abstract #3519

Using Dimensionality Reduction to Explore Virtual Reality Lobectomies

Allen Q. Ye 1 , Olusola Ajilore 2 , Alessandro Febretti 3 , Andrew Johnson 3 , Johnson GadElkarim 2 , Shaolin Yang 2 , Richard Magin 1 , Anand Kumar 2 , and Alex D. Leow 2

1 Dept. of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 2 Dept. of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States, 3 Dept. of Computer Science, University of Illinois at Chicago, Chicago, IL, United States

This abstract presents the utility of using dimensionality reduction to visualize lobectomies in a virtual reality environment. Exploration of a Monte Carlo simulation of lobectomies, along with targeted rich club removal was performed and displayed using the Omegalib framework. Results show a significant increase in overall distance for the dimensionality reduced embedding for the targeted versus random removal. Qualitative results also show a stark change between random removals and targeted removal.

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