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Classification of pediatric brain tumors based on MR-images using deep learning
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). 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, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-7061-7995
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-0555-8877
2022 (English)Conference paper, Oral presentation with published abstract (Other academic)
Place, publisher, year, edition, pages
Luleå, 2022.
National Category
Medical Imaging
Identifiers
URN: urn:nbn:se:liu:diva-187769OAI: oai:DiVA.org:liu-187769DiVA, id: diva2:1691413
Conference
Medicinteknikdagarna 2022, 4-6 oktober, Luleå, Sweden
Funder
Swedish Childhood Cancer FoundationLinköpings universitetAvailable from: 2022-08-30 Created: 2022-08-30 Last updated: 2025-02-09Bibliographically approved

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Tampu, Iulian EmilEklund, AndersHaj-Hosseini, Neda

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Bianchessi, TamaraTampu, Iulian EmilEklund, AndersHaj-Hosseini, Neda
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Division of Biomedical EngineeringFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)The Division of Statistics and Machine Learning
Medical Imaging

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