Self-supervised learning for classifying paranasal anomalies in the maxillary sinus.
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| Title: | Self-supervised learning for classifying paranasal anomalies in the maxillary sinus. |
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| Authors: | Bhattacharya D; Institute of Medical Technology and Intelligent Systems, Technische Universitaet Hamburg, Hamburg, Germany. debayan.bhattacharya@tuhh.de.; Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. debayan.bhattacharya@tuhh.de., Behrendt F; Institute of Medical Technology and Intelligent Systems, Technische Universitaet Hamburg, Hamburg, Germany., Becker BT; Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Maack L; Institute of Medical Technology and Intelligent Systems, Technische Universitaet Hamburg, Hamburg, Germany., Beyersdorff D; Clinic and Polyclinic for Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Petersen E; Population Health Research Department, University Heart and Vascular Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Petersen M; Clinic and Polyclinic for Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Cheng B; Clinic and Polyclinic for Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Eggert D; Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Betz C; Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Hoffmann AS; Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Schlaefer A; Institute of Medical Technology and Intelligent Systems, Technische Universitaet Hamburg, Hamburg, Germany. |
| Source: | International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2024 Sep; Vol. 19 (9), pp. 1713-1721. Date of Electronic Publication: 2024 Jun 08. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Germany NLM ID: 101499225 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1861-6429 (Electronic) Linking ISSN: 18616410 NLM ISO Abbreviation: Int J Comput Assist Radiol Surg Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1861-6429 |
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| DOI: | 10.1007/s11548-024-03172-5 |
