Automatic measurement of orbital volume in unilateral coronal synostosis

Vedrana Andersen Dahl, Gudmundur Einarsson, Tron Andre Darvann, Nuno Vibe Hermann, Hanne Buciek Hove, Naoya Kakimoto, Sven Kreiborg, Anders Bjorholm Dahl

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Premature fusion of the coronal suture on one side of the calvaria (unilateral coronal synostosis, UCS) results in asymmetric craniofacial development and the deformation of the orbits. Often this necessitates surgery, where CT scanning is employed to obtain measures of the bony orbit. These measures are typically computed by guided procedures that require expert time. We propose a method with higher degree of automation based on finding an optimal smooth closed surface. CT scans of 17 infants with UCS are included in our experimental validation, where we compare our method to expert guided segmentations. We obtain similar measures, as well as high Dice scores, compared to the experts. The run time for the proposed approach with a prototype implementation is around 3 minutes on a standard laptop, making the method suitable for rapid evaluation of orbital volume in UCS.
Original languageEnglish
Title of host publicationProceedings of the 13th International Symposium on Biomedical Imaging (ISBI 2016)
PublisherIEEE
Publication date2016
Pages889-893
ISBN (Electronic)978-1-4799-2349-6
DOIs
Publication statusPublished - 2016
Event13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Clarion Congress Hotel, Prague, Czech Republic
Duration: 13 Apr 201616 Apr 2016
Conference number: 13
http://biomedicalimaging.org/2016/
https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html%3FConf_ID%3D31200

Conference

Conference13th IEEE International Symposium on Biomedical Imaging
Number13
LocationClarion Congress Hotel
CountryCzech Republic
CityPrague
Period13/04/201616/04/2016
Internet address
SeriesInternational Symposium on Biomedical Imaging. Proceedings
ISSN1945-7928

Keywords

  • Image segmentation
  • Bone
  • Computed tomography (CT)

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