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README.md

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+# What is ClinicaDL ?
+
+ClinicaDL is an open-source deep learning software for reproducible neuroimaging processing. It can be seen as the deep learning extension of 
+[Clinica](https://aramislab.paris.inria.fr/clinica/docs/public/latest/CAPS/Introduction/), an open-source Python library for neuroimaging preprocessing 
+and analysis. The combination of ClinicaDL and Clinica allows performing an end-to-end neuroimaging analysis, from the download of raw data sets to the 
+interpretation of trained networks, including neuroimaging preprocessing, quality check, label definition, architecture search, and network training and 
+evaluation.
+ClinicaDL has been implemented to bring answers to three common issues encountered by deep learning users who are not always familiar with neuroimaging data: 
+- accessing properly formatted and pre-processed datasets can be difficult, which can be partly tackled by a dataset format established by the community: the Brain Imaging
+  Data Structure (BIDS) - methodological flaws in many studies which results are contaminated by data leakage,
+- a lack of reproducibility that discredits results,
+Employing ClinicaDL serves as an initial measure to avoid such prevalent problems.
+
+This library was at first developed from the AD-DL project, a GitHub repository hosting the source code of a scientific publication on the deep learning classification 
+of brain images in the context of Alzheimer's disease. This is why some functions of ClinicaDL can still be specific to Alzheimer's disease context.
+For moreinformation on this clinical context, please refer to our [tutorial](https://aramislab.paris.inria.fr/clinicadl/tuto/2023/html/index.html).
+If you are new to ClinicaDL, please consider reading the [First steps section](https://clinicadl.readthedocs.io/en/latest/Introduction/) before starting your project!