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Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images

Claudia Chevrefils, Farida Cheriet, Guy Grimard, Marie-Claude Miron and Carl-Éric Aubin

Article (2012)

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Cite this document: Chevrefils, C., Cheriet, F., Grimard, G., Miron, M.-C. & Aubin, C.-É. (2012). Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images. BMC Medical Imaging, 12. doi:10.1186/1471-2342-12-26
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Abstract

Background: For some scoliotic patients the spinal instrumentation is inevitable. Among these patients, those with stiff curvature will need thoracoscopic disk resection. The removal of the intervertebral disk with only thoracoscopic images is a tedious and challenging task for the surgeon. With computer aided surgery and 3D visualisation of the interverterbral disk during surgery, surgeons will have access to additional information such as the remaining disk tissue or the distance of surgical tools from critical anatomical structures like the aorta or spinal canal. We hypothesized that automatically extracting 3D information of the intervertebral disk from MR images would aid the surgeons to evaluate the remaining disk and would add a security factor to the patient during thoracoscopic disk resection.Methods: This paper presents a quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images. The automatic segmentation method is based on the watershed technique and morphological operators. The 3D Dice Similarity Coefficient (DSC) is the main statistical metric used to validate the automatically detected preoperative disk volumes. The automatic detections of intervertebral disks of real clinical MR images are compared to manual segmentation done by clinicians.Results: Results show that depending on the type of MR acquisition sequence, the 3D DSC can be as high as 0.79 (+/- 0.04). These 3D results are also supported by a 2D quantitative evaluation as well as by robustness and variability evaluations. The mean discrepancy (in 2D) between the manual and automatic segmentations for regions around the spinal canal is of 1.8 (+/- 0.8) mm. The robustness study shows that among the five factors evaluated, only the type of MRI acquisition sequence can affect the segmentation results. Finally, the variability of the automatic segmentation method is lower than the variability associated with manual segmentation performed by different physicians.Conclusions: This comprehensive evaluation of the automatic segmentation and 3D reconstruction of intervertebral disks shows that the proposed technique used with specific MRI acquisition protocol can detect intervertebral disk of scoliotic patient. The newly developed technique is promising for clinical context and can eventually help surgeons during thoracoscopic intervertebral disk resection.

Uncontrolled Keywords

Adolescent; Algorithms; Child; Female; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Intervertebral Disc Displacement; Magnetic Resonance Imaging; Male; Pattern Recognition, Automated; Reproducibility of Results; Scoliosis; Sensitivity and Specificity; Young Adult

Open Access document in PolyPublie
Subjects: 2100 Génie mécanique > 2100 Génie mécanique
9000 Sciences médicales > 9000 Sciences médicales
Department: Département de génie informatique et génie logiciel
Département de génie mécanique
Institut de génie biomédical
Research Center: Non applicable
Funders: CRSNG/NSERC, Canada Research Chair, Fonds Québécois de la Recherche sur la Nature et les Technologies (FQRNT)
Date Deposited: 07 Dec 2018 12:54
Last Modified: 08 Dec 2018 01:20
PolyPublie URL: https://publications.polymtl.ca/3414/
Document issued by the official publisher
Journal Title: BMC Medical Imaging (vol. 12)
Publisher: BioMed Central
Official URL: https://doi.org/10.1186/1471-2342-12-26

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