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Application of an RGBD augmented C-arm for minimally invasive scoliosis surgery assistance

Séverine Habert, Ulrich Eck, Pascal Fallavollita, Stefan Parent, Nassir Navab and Farida Cheriet

Article (2017)

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Cite this document: Habert, S., Eck, U., Fallavollita, P., Parent, S., Navab, N. & Cheriet, F. (2017). Application of an RGBD augmented C-arm for minimally invasive scoliosis surgery assistance. Healthcare Technology Letter, 4(5), p. 179-183. doi:10.1049/htl.2017.0069
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Abstract

Minimally invasive surgeries (MISs) are gaining popularity as alternatives to conventional open surgeries. In thoracoscopic scoliosis MIS, fluoroscopy is used to guide pedicle screw placement and to visualise the effect of the intervention on the spine curvature. However, cosmetic external appearance is the most important concern for patients, while correction of the spine and achieving coronal and sagittal trunk balance are the top priorities for surgeons. The authors present the feasibility study of the first intra-operative assistive system for scoliosis surgery composed of a single RGBD camera affixed on a C-arm which allows visualising in real time the surgery effects on the patient trunk surface in the transverse plane. They perform three feasibility experiments from simulated data based on scoliotic patients to live acquisition from non-scoliotic mannequin and person, all showing that the proposed system accuracy is comparable with scoliotic surface reconstruction state of art.

Uncontrolled Keywords

RGBD augmented C-arm; bone; coronal trunk balance; cosmetic external appearance; diagnostic radiography; diseases; first intraoperative assistive system; fluoroscopy; image sensors; live acquisition; medical robotics; minimally invasive scoliosis surgery assistance; nonscoliotic mannequin; patient trunk surface; pedicle screw placement; sagittal trunk balance; scoliotic patients; scoliotic surface reconstruction; single RGBD camera; spine curvature; surgery; thoracoscopic scoliosis MIS; transverse plane

Open Access document in PolyPublie
Subjects: 1900 Génie biomédical > 1901 Technologie biomédicale
2800 Intelligence artificielle > 2800 Intelligence artificielle (Vision artificielle, voir 2603)
Department: Département de génie informatique et génie logiciel
Research Center: LIV4D - Laboratoire d'imagerie et de vision 4D
Funders: Deutsche Forschungsgemeinschaft
Grant number: NA 620/30-1
Date Deposited: 03 Nov 2021 15:23
Last Modified: 04 Nov 2021 01:20
PolyPublie URL: https://publications.polymtl.ca/4916/
Document issued by the official publisher
Journal Title: Healthcare Technology Letter (vol. 4, no. 5)
Publisher: Institution of Engineering and Technology (IET)
Official URL: https://doi.org/10.1049/htl.2017.0069

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