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A Dependable Massive Storage Service for Medical Imaging.

Marco Antonio Núñez-GaonaRicardo Marcelín-JiménezJosefina Gutiérrez-MartínezHeriberto Aguirre-MenesesJosé Luis Gonzalez-Compean
Published in: Journal of digital imaging (2019)
We present the construction of Babel, a distributed storage system that meets stringent requirements on dependability, availability, and scalability. Together with Babel, we developed an application that uses our system to store medical images. Accordingly, we show the feasibility of our proposal to provide an alternative solution for massive scientific storage and describe the software architecture style that manages the DICOM images life cycle, utilizing Babel like a virtual local storage component for a picture archiving and communication system (PACS-Babel Interface). Furthermore, we describe the communication interface in the Unified Modeling Language (UML) and show how it can be extended to manage the hard work associated with data migration processes on PACS in case of updates or disaster recovery.
Keyphrases
  • healthcare
  • life cycle
  • deep learning
  • convolutional neural network
  • optical coherence tomography
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  • autism spectrum disorder
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