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Gabriel Maher

PhD Candidate, Institute for Computational & Mathematical Engineering
Story originally published on May 2016
I am working with the Cardiovascular Biomechanics Computation Lab.

This lab is working to build and run simulations of the cardiovascular system, so we can better understand how it works, how it responds to surgeries, biomedical implants, etc. In order to perform these simulations, we currently take MRI or CT scan data and manually construct 3D models of the cardiovascular system. The process takes a very long time. I am working to figure out how we can automate the construction of accurate cardiovascular models to speed up this process. This comes down to an artificial intelligence question of how do we teach a computer to recognize where blood vessels are in MRI or CT scan data. Essentially, we are trying to teach a computer how to analyze MRI data, and then we’re working to optimize this process using machine learning, artificial intelligence, deep learning and comprehensive algorithms. If we’re able to successfully automate 3D cardiovascular model construction, this would make it easier to study and come to better understandings of the causes of particular cardiovascular diseases, or how particular surgeries affect the cardiovascular system. With better simulations, we could also potentially optimize surgical processes. Simulations allow a surgical team to run through a couple of potential surgery options, and then choose the best possible surgery for a patient.

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