302 232

Cited 0 times in

Automatical Cranial Suture Detection based on Thresholding Method

 Hyunwoo Park  ;  Jiwoo Kang  ;  Yong Oock Kim  ;  Sanghoon Lee 
 Journal of International Society for Simulation Surgery, Vol.2(1) : 33-39, 2015 
Journal Title
 Journal of International Society for Simulation Surgery 
Issue Date
Zcraniosynostosis ; Thresholding Method ; Cranial Suture ; Automatic Diagnosis
Purpose : The head of infants under 24 months old who has Craniosynostosis grows extraordinarily that makes head shape unusual. To diagnose the Craniosynostosis, surgeon has to inspect computed tomography(CT) images of the patient in person. It’s very time consuming process. Moreover, without a surgeon, it’s diffcult to diagnose the Craniosynostosis. Therefore, we developed technique which detects Craniosynostosis automatically from the CT volume. Materials and Methods : At first, rotation correction is performed to the 3D CT volume for detection of the Craniosynostosis. Then, cranial area is extracted using the iterative thresholding method we proposed. Lastly, we diagnose Craniosynostosis by analyzing centroid relationships of clusters of cranial bone which was divided by cranial suture. Results : Using this automatical cranial detection technique, we can diagnose Craniosynostosis correctly. The proposed method resulted in 100% sensitivity and 90% specificity. The method perfectly diagnosed abnormal patients. Conclusion : By plugging-in the software on CT machine, it will be able to warn the possibility of Craniosynostosis. It is expected that early treatment of Craniosynostosis would be possible with our proposed algorithm.
Files in This Item:
T201504068.pdf Download
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Plastic and Reconstructive Surgery (성형외과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Yong Oock(김용욱) ORCID logo https://orcid.org/0000-0002-3756-4809
사서에게 알리기


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.