Automated cerebral microbleed (CMB) detection on ex-vivo MRI is key to enabling MRI-pathology studies in large community-based cohorts where manual CMB annotation is time consuming and prone to error. The aim of this study is to develop a CMB detection algorithm to aid in the quantization and localization of CMBs on ex-vivo T2*-weighted gradient echo MRI in community-based cohorts. A CMB synthesis algorithm is proposed and synthetic CMBs are used to train a neural network for CMB detection. A model trained with both synthetic and real data is shown to outperform models trained on synthetic or real data alone.
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