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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