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Minimal annotation training for segmentation of microscopy images
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-6148-5174
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.ORCID iD: /0000-0002-8307-7411
2018 (English)In: Proc. 15th International Symposium on Biomedical Imaging, IEEE, 2018, p. 387-390Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2018. p. 387-390
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-368701DOI: 10.1109/ISBI.2018.8363599ISI: 000455045600088ISBN: 978-1-5386-3636-7 (electronic)OAI: oai:DiVA.org:uu-368701DiVA, id: diva2:1268701
Conference
ISBI 2018, April 4–7, Washington, DC
Available from: 2018-12-06 Created: 2018-12-06 Last updated: 2019-02-21Bibliographically approved

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Matuszewski, Damian J.Sintorn, Ida-Maria

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