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Copy file name to clipboardExpand all lines: README.md
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1. Vision
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* Develop a community of academic, industrial and clinical researchers collaborating and working on a common foundation of standardized tools.
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* Create a state-of-the-art, end-to-end training toolkit for healthcare imaging.
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* Provide academic and industrial researchers with the optimized and standardized way to create and evaluate models
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* Develop a community of academic, industrial and clinical researchers collaborating and working on a common foundation of standardized tools.
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* Create a state-of-the-art, end-to-end training toolkit for healthcare imaging.
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* Provide academic and industrial researchers with the optimized and standardized way to create and evaluate models
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2. Targeted users
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* Primarily focused on the healthcare researchers who develop DL models for medical imaging
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* Primarily focused on the healthcare researchers who develop DL models for medical imaging
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3. Goals
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* Deliver domain-specific workflow capabilities
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* Address the end-end “Pain points” when creating medical imaging deep learning workflows.
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* Provide a robust foundation with a performance optimized system software stack that allows researchers to focus on the research and not worry about software development principles.
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* Deliver domain-specific workflow capabilities
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* Address the end-end “Pain points” when creating medical imaging deep learning workflows.
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* Provide a robust foundation with a performance optimized system software stack that allows researchers to focus on the research and not worry about software development principles.
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4. Guiding principles
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1. Modularity
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* Rigorous risk analysis of choice of foundational software dependencies
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7. Compatible with external software
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* E.g. data visualisation, experiments tracking, management, orchestration
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5. Key capabilities
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<table>
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