MacDonald, M. EthanVega Lara, Fernando2024-01-252024-01-252024-01-15Vega Lara, F. (2024). Using image translation to synthesize amyloid beta from structural MRI (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.https://hdl.handle.net/1880/11806010.11575/PRISM/42904Amyloid-beta and brain atrophy are known hallmarks of Alzheimer’s Disease (AD) and can be quantified with positron emission tomography (PET) and structural magnetic resonance imaging (MRI), respectively. PET uses radiotracers that bind to amyloid-beta, whereas MRI can measure brain morphology. PET scans have limitations including cost, invasiveness (involve injections and ionizing radiation exposure), and have limited accessibility, making PET not practical for screening early-onset AD. Conversely, MRI is a cheaper, less-invasive (free from ionizing radiation), and is more widely available, however, it cannot provide the necessary molecular information. There is a known relationship between amyloid-beta and brain atrophy. This thesis aims to synthesize amyloid-beta PET images from structural MRI using image translation, an advanced form of machine learning. The developed models have reported high-similarity metrics between the real and synthetic PET images and high-degree of accuracy in radiotracer quantification. The results are highly impactful as it enables amyloid-beta measurements form every MRI, for free!enUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.MRIPETGenerative Adversarial NetworksEngineering--BiomedicalArtificial Intelligencemaster thesis