Abstract #1290

GAN-based analysis for investigation of disease specific image pattern in SWI data of patients suffering from multiple sclerosis

Alina Lopatina^1,2, Stefan Ropele³, Renat Sibgatulin¹, Jürgen R Reichenbach^1,2,4, and Daniel Güllmar¹

¹Medical Physics Group / IDIR, Jena University Hospital, Jena, Germany, ²Michael-Stifel-Center for Data-Driven and Simulation Science, Jena, Germany, ³Department of Neurology, Medical University of Graz, Graz, Austria, ⁴Center of Medical Optics and Photonics Jena, Jena, Germany

We propose a method to transform susceptibility-weighted images of multiple sclerosis (MS) patients to images reflecting healthy volunteers based on generative adversarial networks (GANs). This method helps to identify MS by changing voxel information corresponding to the disease. The results showed that voxels around the central veins and ventricles are identified as MS-specific by the method. This finding may contribute to improvements in MS diagnosis and encourage future studies based on the presented findings.

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