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Data Storage, Cloud Usage and Artificial Intelligence Pipeline

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Artificial Intelligence in Cardiothoracic Imaging

Part of the book series: Contemporary Medical Imaging ((CMI))

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Abstract

Artificial intelligence (AI), and especially deep learning, requires vast amounts of data for training, testing and validation. Collecting these data and the corresponding annotations requires the implementation of imaging biobanks that provide access to these data in a standardized way. This in turn requires careful design and implementation based on the current standards and guidelines and complying to the current legal restrictions. However, just the realization of proper imaging data collections is not sufficient to train, validate and deploy AI as resource demands are high and requires a careful hybrid implementation of AI pipelines both on premise and in the cloud.

This chapter aims to help the reader when technical considerations have to be made about the AI environment by providing a technical background of different concepts and implementation aspects that are involved in data storage, cloud usage and AI pipelines.

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Correspondence to Peter M. A. van Ooijen .

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van Ooijen, P.M.A., Darzi, E., Dekker, A. (2022). Data Storage, Cloud Usage and Artificial Intelligence Pipeline. In: De Cecco, C.N., van Assen, M., Leiner, T. (eds) Artificial Intelligence in Cardiothoracic Imaging. Contemporary Medical Imaging. Humana, Cham. https://doi.org/10.1007/978-3-030-92087-6_5

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  • DOI: https://doi.org/10.1007/978-3-030-92087-6_5

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  • Publisher Name: Humana, Cham

  • Print ISBN: 978-3-030-92086-9

  • Online ISBN: 978-3-030-92087-6

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