Anomaly Detection Differentiates between Normal Liver Parenchyma and Various Malignancies in Optical Coherence Tomography Images: A Novel Machine-learning Approach
HPB, vol. 27, pp. S380
Authors 9
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Affiliation as printed
Fraunhofer Austria Research GmbH, Visual Computing, Graz, Austria
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Affiliation as printed
Fraunhofer Austria Research GmbH, Visual Computing, Graz, Austria
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Fraunhofer Institute for Production Technology IPT
Affiliation as printed
Fraunhofer-Institut für Produktionstechnologie IPT, Optical Metrology and Imaging Techniques, Aachen, Germany
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Fraunhofer Institute for Production Technology IPT
Affiliation as printed
Fraunhofer-Institut für Produktionstechnologie IPT, Optical Metrology and Imaging Techniques, Aachen, Germany
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Fraunhofer Institute for Production Technology IPT
Affiliation as printed
Fraunhofer-Institut für Produktionstechnologie IPT, Optical Metrology and Imaging Techniques, Aachen, Germany
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S. Büsker Aachen
Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
University Hospital RWTH Aachen, Pathology, Aachen, Germany
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Daniel Truhn Aachen
Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
University Hospital RWTH Aachen, Diagnostic and Interventional Radiology, Aachen, Germany
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
University Hospital RWTH Aachen, General, Visceral, Pediatric, and Transplantation Surgery, Aachen, Germany
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
University Hospital RWTH Aachen, General, Visceral, Pediatric, and Transplantation Surgery, Aachen, Germany
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