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Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction Models ⋆

Unknown authors · 2023
hash_id: 511212fbc18b2fdd4f393e4924c297da890ab4c41655e8df7fc888d150144f34 · DOI: 10.1101/2023.05.10.540134

Abstract Brain age is an estimate of chronological age obtained from T1-weighted magnetic resonance images (T1w MRI) and represents a simple diagnostic biomarker of brain ageing and associated diseases. While the current best accuracy of brain age predictions on T1w MRIs of healthy subjects ranges from two to three years, comparing results from different studies is challenging due to differences in the datasets, T1w preprocessing pipelines, and performance metrics used. This paper investigates the impact of T1w image preprocessing on the performance of four deep learning brain age models presented in recent literature. Four preprocessing pipelines were evaluated, differing in terms of registration, grayscale correction, and software implementation. The results showed that the choice of software or preprocessing steps can …

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