Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jul 21, 2023

Abstract

PURPOSE: Paranasal anomalies are commonly discovered during routine radiological screenings and can present with a wide range of morphological features. This diversity can make it difficult for convolutional neural networks (CNNs) to accurately classify these anomalies, especially when working with limited datasets. Additionally, current approaches to paranasal anomaly classification are constrained to identifying a single anomaly at a time. These challenges necessitate the need for further research and development in this area.

Authors

  • Debayan Bhattacharya
    Institute of Medical Technology and Intelligent Systems, Hamburg University of Technology, 21073, Hamburg, Germany.
  • Finn Behrendt
    Institute of Medical Technology and Intelligent Systems, Hamburg University of Technology, Hamburg, Germany.
  • Benjamin Tobias Becker
    Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Dirk Beyersdorff
    Clinic and Polyclinic for Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Elina Petersen
    Population Health Research Department, University Heart and Vascular Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Marvin Petersen
    Clinic and Polyclinic for Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Bastian Cheng
    Clinic and Polyclinic for Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Dennis Eggert
    Clinic and Polyclinic for Otolaryngology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Christian Betz
    Clinic and Polyclinic for Otolaryngology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Anna Sophie Hoffmann
    Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Alexander Schlaefer
    Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany. schlaefer@tuhh.de.

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