Keywords: Deep learning, Neuroimaging, Data leakage, Reproducibility, Open-source
TL;DR: We present ClinicaDL, a deep learning software for neuroimaging aiming at bypassing common flaws of our domain.
Abstract: This paper presents ClinicaDL, a deep learning software for neuroimaging processing. Its aim is to provide a concrete solution to methodological flaws often found in our field (the difficult use of neuroimaging data sets, data leakage and insufficient reproducibility), but also to raise awareness and discuss these issues with our community. The corresponding journal paper was recently accepted in Computer Methods and Programs in Biomedicine.
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Paper Type: recently published or submitted journal contributions
Primary Subject Area: Validation Study
Secondary Subject Area: Application: Radiology
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