Intraoperative detection and localization of cylindrical implants in cone-beam CT image data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-11

AUTHORS

Joseph Görres, Michael Brehler, Jochen Franke, Karl Barth, Sven Y. Vetter, Andrés Córdova, Paul A. Grützner, Hans-Peter Meinzer, Ivo Wolf, Diana Nabers

ABSTRACT

PURPOSE: Orthopedic fractures are often fixed using metal implants. The correct positioning of cylindrical implants such as surgical screws, rods and guide wires is highly important. Intraoperative 3D imaging is often used to ensure proper implant placement. However, 3D image interaction is time-consuming and requires experience. We developed an automatic method that simplifies and accelerates location assessment of cylindrical implants in 3D images. METHODS: Our approach is composed of three major steps. At first, cylindrical characteristics are detected by analyzing image gradients in small image regions. Next, these characteristics are grouped in a cluster analysis. The clusters represent cylindrical implants and are used to initialize a cylinder-to-image registration. Finally, the two end points are optimized regarding image contrast along the cylinder axis. RESULTS: A total of 67 images containing 420 cylindrical implants were used for testing. Different anatomical regions (calcaneus, spine) and various image sources (two mobile devices, three reconstruction methods) were investigated. Depending on the evaluation set, the detection performance was between 91.7 and 96.1% true- positive rate with a false-positive rate between 2.0 and 3.2%. The end point distance errors ranged from [Formula: see text] to [Formula: see text] mm and the orientation errors from [Formula: see text] to [Formula: see text] degrees. The average computation time was less than 5 seconds. CONCLUSIONS: An automatic method was developed and tested that obviates the need for 3D image interaction during intraoperative assessment of cylindrical orthopedic implants. The required time for working with the viewing software of cone-beam CT device is drastically reduced and leads to a shorter time under anesthesia for the patient. More... »

PAGES

1045-1057

References to SciGraph publications

  • 2014-07. Automated implant segmentation in cone-beam CT using edge detection and particle counting in INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
  • 2006-02. Die klinische Wertigkeit des ISO-C3D bei der Osteosynthese des Fersenbeins in DER UNFALLCHIRURG
  • 2013-07. The Medical Imaging Interaction Toolkit: challenges and advances in INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
  • 2013-02. Intraoperative dreidimensionale Bildgebung – nützlich oder notwendig? in DER UNFALLCHIRURG
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11548-014-0998-8

    DOI

    http://dx.doi.org/10.1007/s11548-014-0998-8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1052270677

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/24744126


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    34 schema:description PURPOSE: Orthopedic fractures are often fixed using metal implants. The correct positioning of cylindrical implants such as surgical screws, rods and guide wires is highly important. Intraoperative 3D imaging is often used to ensure proper implant placement. However, 3D image interaction is time-consuming and requires experience. We developed an automatic method that simplifies and accelerates location assessment of cylindrical implants in 3D images. METHODS: Our approach is composed of three major steps. At first, cylindrical characteristics are detected by analyzing image gradients in small image regions. Next, these characteristics are grouped in a cluster analysis. The clusters represent cylindrical implants and are used to initialize a cylinder-to-image registration. Finally, the two end points are optimized regarding image contrast along the cylinder axis. RESULTS: A total of 67 images containing 420 cylindrical implants were used for testing. Different anatomical regions (calcaneus, spine) and various image sources (two mobile devices, three reconstruction methods) were investigated. Depending on the evaluation set, the detection performance was between 91.7 and 96.1% true- positive rate with a false-positive rate between 2.0 and 3.2%. The end point distance errors ranged from [Formula: see text] to [Formula: see text] mm and the orientation errors from [Formula: see text] to [Formula: see text] degrees. The average computation time was less than 5 seconds. CONCLUSIONS: An automatic method was developed and tested that obviates the need for 3D image interaction during intraoperative assessment of cylindrical orthopedic implants. The required time for working with the viewing software of cone-beam CT device is drastically reduced and leads to a shorter time under anesthesia for the patient.
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