A

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

  1. Fraunhofer Austria

    Affiliation as printed

    Fraunhofer Austria Research GmbH, Visual Computing, Graz, Austria

  2. Fraunhofer Austria

    Affiliation as printed

    Fraunhofer Austria Research GmbH, Visual Computing, Graz, Austria

  3. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer-Institut für Produktionstechnologie IPT, Optical Metrology and Imaging Techniques, Aachen, Germany

  4. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer-Institut für Produktionstechnologie IPT, Optical Metrology and Imaging Techniques, Aachen, Germany

  5. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer-Institut für Produktionstechnologie IPT, Optical Metrology and Imaging Techniques, Aachen, Germany

  6. S. Büsker Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen, Pathology, Aachen, Germany

  7. Daniel Truhn Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen, Diagnostic and Interventional Radiology, Aachen, Germany

  8. Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen, General, Visceral, Pediatric, and Transplantation Surgery, Aachen, Germany

  9. Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen, General, Visceral, Pediatric, and Transplantation Surgery, Aachen, Germany

Cited by 0 stored of 0

No patents citing this paper on Lens.org (checked 2026-10-06).

References 0