Segmentation of the iliac crest from CT-data for virtual surgical planning of facial reconstruction surgery using deep learning.

Journal: Scientific reports
PMID: 39773990

Abstract

BACKGROUND AND OBJECTIVES: For the planning of surgical procedures involving the bony reconstruction of the mandible, the autologous iliac crest graft, along with the fibula graft, has become established as a preferred donor region. While computer-assisted planning methods are increasingly gaining importance, the necessary preparation of geometric data based on CT imaging remains largely a manual process. The aim of this work was to develop and test a method for the automated segmentation of the iliac crest for subsequent reconstruction planning.

Authors

  • Stefan Raith
    Department of Dental Materials and Biomaterials Research, RWTH Aachen University Hospital, Aachen, Germany. Electronic address: sraith@ukaachen.de.
  • Tobias Pankert
    Department of Oral and Maxillofacial Surgery, RWTH Aachen University Hospital, Aachen, Germany. tpankert@ukaachen.de.
  • Jônatas de Souza Nascimento
    Inzipio GmbH, Krantzstr. 7 Building 80, 52070, Aachen, Germany.
  • Srikrishna Jaganathan
    Inzipio GmbH, Krantzstr. 7 Building 80, 52070, Aachen, Germany.
  • Florian Peters
    Department of Oral and Maxillofacial Surgery, RWTH Aachen University Hospital, Aachen, Germany.
  • Mathias Wien
    Institute of Imaging and Computer Vision, RWTH Aachen University, Kopernikusstraße 16, 52074, Aachen, Germany.
  • Frank Hölzle
    Department of Oral and Maxillofacial Surgery, RWTH Aachen University Hospital, Aachen, Germany.
  • Ali Modabber
    Department of Oral and Maxillofacial Surgery, RWTH Aachen University Hospital, Aachen, Germany.

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