Abstract #5040

Amyloid-Beta Axial Plane PET Synthesis from Structural MRI: An Image Translation Approach for Screening Alzheimer’s Disease

Fernando Vega^1,2,3, Abdoljalil Addeh^1,2,3, Ahmed Elmenshawi², and M. Ethan MacDonald^1,2,3,4

¹Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada, ²Electrical & Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada, ³Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada, ⁴Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Alzheimer's Disease, MRI, PET, Image TranslationIn this work, an image translation model is implemented to produce synthetic amyloid-beta PET images from structural MRI that are quantitatively accurate. Image pairs of amyloid-beta PET and structural MRI were used to train the model. We found that the synthetic PET images could be produced with a high degree of similarity to truth in terms of shape, contrast and overall high SSIM and PSNR. This work demonstrates that performing structural to quantitative image translation is feasible to enable the access amyloid-beta information from only MRI.

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