DWI/FLAIR Mismatch An Automated, Continuous & Clinically Viable Approach

PhD defence by Jacob Johansen

Assessment Committee

Professor Stefan Sommer, Computer Science, University of Copenhagen (Chairperson)
Associate Professor Dimitrios Papadopoulos, DTU Compute
Associate Professor Daniele Ravi, University of Messina

Supervisors

Professor Sune Darkner
Associate Professor Melanie Ganz-Benjaminsen
CTO Akshay Pai

Department

Department of Computer Science

Place

Building: Pioneer Center for AI (P1), Room: Seminar Room, Øster Voldgade 3, 1350 København

Email address to gain access to the thesis: jj@di.ku.dk.
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Short description of the thesis

This thesis explores an automatic, applicable and non-binary solution for determining DWI/FLAIR mismatch, used in treatment selection of unknown onset ischemic stroke patients.
We present a simple method that can be validated in real time by physicians and show that it is comparable to other current methods which rely on complex black box methods.
Lastly, we explore the impact of a non-binary selection criteria and what it might mean for treatment selection going forward