This is an open access article published by the IET under the Creative Commons Attribution -NonCommercial License (http://creativecommons.org/licenses/by-nc/3.0/)
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.
References
-
-
1)
-
8. Reyes, M., Clapés, A., Ramrez, J., et al: ‘Automatic digital biometry analysis based on depth maps’, Comput. Ind., 2013, 64, (9), pp. 1316–1325 (doi: 10.1016/j.compind.2013.04.009).
-
2)
-
13. Nguyen, C.V., Izadi, S., Lovell, D.: ‘Modeling Kinect sensor noise for improved 3D reconstruction and tracking’. 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), Zurich, Switzerland, 2012, pp. 524–530.
-
3)
-
3. Buchanan, R., Birch, J.G., Morton, A.A., et al: ‘Do you see what I see? looking at scoliosis surgical outcomes through orthopedists' eyes’, Spine, 2003, 28, (24), pp. 2700–2704 (doi: 10.1097/01.BRS.0000103383.81904.5A).
-
4)
-
12. Patias, P., Grivas, T.B., Kaspiris, A., et al: ‘A review of the trunk surface metrics used as scoliosis and other deformities evaluation indices’, Scoliosis, 2010, 5, (1), p. 12 (doi: 10.1186/1748-7161-5-12).
-
5)
-
9. Seoud, L., Dansereau, J., Labelle, H., et al: ‘Multilevel analysis of trunk surface measurements for noninvasive assessment of scoliosis deformities’, Spine, 2012, 37, (17), pp. E1045–E1053 (doi: 10.1097/BRS.0b013e3182575938).
-
6)
-
7. Castro, A., Pacheco, J., Lourenço, C., et al: ‘Evaluation of spinal posture using microsoft Kinect: a preliminary case-study with 98 volunteers’, Porto Biomed. J., 2016, 2, (1), pp. 18–22 (doi: 10.1016/j.pbj.2016.11.004).
-
7)
-
10. Seoud, L., Dansereau, J., Labelle, H., et al: ‘Noninvasive clinical assessment of trunk deformities associated with scoliosis’, IEEE J. Biomed. Health Inform., 2013, 17, (2), pp. 392–401 (doi: 10.1109/TITB.2012.2222425).
-
8)
-
8. Navab, N., Blum, T., Wang, L.,, et al: ‘First deployments of augmented reality in operating rooms’, Computer, 2012, 45, pp. 48–55 (doi: 10.1109/MC.2012.75).
-
9)
-
14. Birdal, T., Dobryden, I., Ilic, S.: ‘X-tag: A fiducial tag for flexible and accurate bundle adjustment’. 3D Vision (3DV), Stanford, CA, USA, 2016, pp. 556–564.
-
10)
-
17. Boisvert, J., Cheriet, F., Pennec, X., et al: ‘3D reconstruction of the human spine from radiograph (s) using a multi-body statistical model’. SPIE Medical Imaging, Lake Buena Vista, FL, USA, 2009, pp. 72612D–72612D.
-
11)
-
16. Habert, S., Gardiazabal, J., Fallavollita, P., et al: ‘Rgbdx: first design and experimental validation of a mirror-based RGBD X-ray imaging system’. Int. Symp. Mixed and Augmented Reality (ISMAR), Fukuoka, Japan, 2015, pp. 13–18.
-
12)
-
2. Newton, P.O., Perry, A.: ‘Thoracoscopic deformity correction’, Minimally Invasive Spine Surg., 2009, pp. 77–86 (doi: 10.1007/978-0-387-89831-5_8).
-
13)
-
1. Long, K.H., Bannon, M.P., Zietlow, S.P., et al: ‘A prospective randomized comparison of laparoscopic appendectomy with open appendectomy: clinical and economic analyses’, Surgery, 2001, 129, (4), pp. 390–400 (doi: 10.1016/S0039-6060(01)15621-7).
-
14)
-
11. Seoud, L., Cheriet, F., Labelle, H., et al: ‘Changes in trunk appearance after scoliosis spinal surgery and their relation to changes in spinal measurements’, Spine Deformity, 2015, 3, (6), pp. 595–603 (doi: 10.1016/j.jspd.2015.05.001).
-
15)
-
5. Aroeira, R.M., Estevam, B., Pertence, A.E., et al: ‘Non-invasive methods of computer vision in the posture evaluation of adolescent idiopathic scoliosis’, J. Bodywork Mov. Ther., 2016, 20, (4), pp. 832–843 (doi: 10.1016/j.jbmt.2016.02.004).
-
16)
-
6. Bonnet, V., Yamaguchi, T., Dupeyron, A., et al: ‘Automatic estimate of back anatomical landmarks and 3D spine curve from a Kinect sensor’. Biomedical Robotics and Biomechatronics (BioRob), Singapore, 2016, pp. 924–929.
-
17)
-
4. Liu, X., Thometz, J., Tassone, J., et al: ‘Historical review and experience with the use of surface topographic systems in children with idiopathic scoliosis’, OA Musculoskelet. Med., 2013, 1, pp. 1–9.
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