Deep Learning for Digital Pathology in Limited Data Scenarios. - Stacke, Karin (Linköping : Linkopings Universitet, 2022)
Intro -- Abstract -- Populärvetenskaplig sammanfattning -- Acknowledgments -- List of Publications -- Contributions -- Contents -- I Comprehensive Summary -- 1 Introduction -- 1.1 Digital pathology -- 1.2 Deep learning -- 1.3 Objectives and contributions -- 1.4 Thesis outline -- 2 Background -- 2.1 Medical images -- 2.2 Deep learning -- 2.3 Application on medical image data -- 3 Building robust models -- 3.1 Domain shift -- 3.2 Training strategies -- 3.3 Workflow strategies -- 3.4 Discussion -- 4 Handling limited data access -- 4.1 Utilizing labeled data -- 4.2 Utilizing unlabeled data -- 4.3 Discussion -- 5 Multi-modal training -- 5.1 Correlated feature learning -- 5.2 Discussion -- 6 Summary and discussion -- 6.1 Summary of contributions -- 6.2 Clinical impact -- 6.3 Ethical considerations -- 6.4 Future outlook -- 6.5 Concluding remarks -- Bibliography -- II Appended papers.
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Keywords: Electronic books