Objective classification system for sagittal craniosynostosis based on suture segmentation

Medical Physics
Xiaohua QianXiaobo Zhou

Abstract

Spring-assisted surgery is an effective and minimally invasive treatment for sagittal craniosynostosis (CSO). The principal barrier to the advancement of spring-assisted surgery is the patient-specific spring selection. The selection of spring force depends on the suture involved, subtypes of sagittal CSO, and age of the infant, among other factors. Clinically, physicians manually judge the subtype of sagittal CSO patients based on their CT image data, which may cause bias from different clinicians. An objective system would be helpful to stratify the sagittal CSO patients and make spring choice less subjective. The authors developed a novel informatics system to automatically segment and characterize sutures and classify sagittal CSO. The proposed system is composed of three phases: preprocessing, sutures segmentation, and classification. First, the three-dimensional (3D) skull was extracted from the CT images and aligned with the symmetry of the cranial vault. Second, a "hemispherical projection" algorithm was developed to transform 3D surface of the skull to a polar two-dimensional plane. Through the transformation, an "effective" projected region can be obtained to enable easy segmentation of sutures. Then, the different ty...Continue Reading

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Citations

Dec 12, 2017·The Journal of Craniofacial Surgery·Alexander Haosi Sun, John A Persing
Oct 2, 2019·Biomechanics and Modeling in Mechanobiology·Alessandro BorghiSilvia Schievano
Apr 24, 2020·International Journal of Molecular Medicine·Zhiyu YangXiaohua Qian

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