Meeting Banner
Abstract #1975

3D brain MRI synthesis utilizing 2D SPADE-GAN and 3D CNN architecture

Aymen Ayaz1, Ronald de Jong1, Samaneh Abbasi-Sureshjani1, Sina Amirrajab1, Cristian Lorenz2, Juergen Weese2, and Marcel Breeuwer1,3
1Biomedical Engineering Department, Eindhoven University of Technology, Eindhoven, Netherlands, 2Philips Research Laboratories, Hamburg, Germany, 3MR R&D – Clinical Science, Philips Healthcare, Best, Netherlands


We propose a method to synthesize 3D consistent brain MRI utilizing multiple 2D conditional SPatially-Adaptive (DE)normalization (SPADE) GANs to preserve the spatial information of patient-specific brain anatomy and a 3D CNN based network to improve the image consistency in all directions in a cost-efficient manner. Three individual 2D SPADE-GAN networks are trained across the axial, sagittal and coronal slice directions and their outputs are thereafter used further to train a CNN based 3D image restoration network to combine them into one 3D volume, using real MRI as a reference. The resulting predicted-synthesized 3D brain MRI is evaluated quantitatively and qualitatively.

This abstract and the presentation materials are available to members only; a login is required.

Join Here