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Comparison of state-of-the-art models for slide-level pediatric brain tumor histology classification
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7582-1706
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-0555-8877
2024 (English)Conference paper, Poster (with or without abstract) (Other academic)
Place, publisher, year, edition, pages
Athens, 2024.
Keywords [en]
cancer, brain tumor, digital pathology, deep learning, AI
National Category
Medical Engineering Cancer and Oncology
Identifiers
URN: urn:nbn:se:liu:diva-203313OAI: oai:DiVA.org:liu-203313DiVA, id: diva2:1856425
Conference
IEEE International Symposium on Biomedical Imaging (ISBI)
Funder
Swedish Childhood Cancer FoundationLinköpings universitet, Cancer Strength AreaAvailable from: 2024-05-06 Created: 2024-05-06 Last updated: 2024-05-15Bibliographically approved

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Spyretos, ChristoforosTampu, Iulian EmilHaj-Hosseini, Neda

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Spyretos, ChristoforosTampu, Iulian EmilPardo Ladino, Juan ManuelHaj-Hosseini, Neda
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Center for Medical Image Science and Visualization (CMIV)Division of Biomedical EngineeringFaculty of Science & EngineeringThe Division of Statistics and Machine Learning
Medical EngineeringCancer and Oncology

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