Skip to main content

Computer-Aided Orthopaedic Surgery: State-of-the-Art and Future Perspectives

  • Chapter
  • First Online:

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1093))

Abstract

Introduced more than two decades ago, computer-aided orthopaedic surgery (CAOS) has emerged as a new and independent area, due to the importance of treatment of musculoskeletal diseases in orthopaedics and traumatology, increasing availability of different imaging modalities and advances in analytics and navigation tools. The aim of this chapter is to present the basic elements of CAOS devices and to review state-of-the-art examples of different imaging modalities used to create the virtual representations, of different position tracking devices for navigation systems, of different surgical robots, of different methods for registration and referencing, and of CAOS modules that have been realized for different surgical procedures. Future perspectives will be outlined. It is expected that the recent advancement on smart instrumentation, medical robotics, artificial intelligence, machine learning, and deep learning techniques, in combination with big data analytics, may lead to smart CAOS systems and intelligent orthopaedics in the near future.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. WHO (2003) The burden of musculoskeletal conditions at the start of the new millennium. Report of a WHO Scientific Group. WHO Technical Report Series, 919, Geneva, 2003, pp 218. ISBN: 92-4-120919-4

    Google Scholar 

  2. Digioia AM 3rd, Jaramaz B, Plakseychuk AY, Moody JE Jr, Nikou C, Labarca RS, Levison TJ, Picard F (2002) Comparison of a mechanical acetabular alignment guide with computer placement of the socket. J Arthroplast 17:359–364

    Article  Google Scholar 

  3. Amiot LP, Labelle H, DeGuise JA, Sati M, Brodeur P, Rivard CH (1995) Image-guided pedicle screw fixation – a feasibility study. Spine 20(10): 1208–1212

    Article  CAS  PubMed  Google Scholar 

  4. Nolte LP, Zamorano LJ, Jiang Z, Wang Q, Langlotz F, Berlemann U (1995) Image-guided insertion of transpedicular screws. A laboratory set-up. Spine (Phila Pa 1976) 20(4):497–500

    Article  CAS  Google Scholar 

  5. Mittelstadt B, Kazanzides P, Zuhars J, Williamson B, Cain P, Smith F, Bargar WL (1996) The evolution of a surgical robot from prototype to human clinical use. In: Taylor RH, Lavallée S, Burdea GC, Mösges R (eds) Computer integrated surgery. The MIT Press, Cambridge, pp 397–407

    Google Scholar 

  6. Martel AL, Heid O, Slomczykowski M, Kerslake R, Nolte LP (1998) Assessment of 3-dimensional magnetic resonance imaging fast low angle shot images for computer assisted spinal surgery. Comput Aided Surg 3:40–44

    Article  CAS  PubMed  Google Scholar 

  7. Cho HS, Park IH, Jeon IH, Kim YG, Han I, Kim HS (2011) Direct application of MR images to computer-assisted bone tumor surgery. J Orthop Sci 16:190–195

    Article  PubMed  Google Scholar 

  8. Jacob AL, Messmer P, Kaim A, Suhm N, Regazzoni P, Baumann B (2000) A whole-body registration-free navigation system for image-guided surgery and interventional radiology. Invest Radiol 35: 279–288

    Article  CAS  PubMed  Google Scholar 

  9. Hofstetter R, Slomczykowski M, Bourquin Y, Nolte LP (1997) Fluoroscopy based surgical navigation: concept and clinical applications. In: Lemke HU, Vannier MW, Inamura K (eds) Computer assisted radiology and surgery. Elsevier Science, Amsterdam, pp 956–960

    Google Scholar 

  10. Joskowicz L, Milgrom C, Simkin A, Tockus L, Yaniv Z (1998) FRACAS: a system for computer-aided image-guided long bone fracture surgery. Comput Aided Surg 36:271–288

    Article  Google Scholar 

  11. Foley KT, Simon DA, Rampersaud YR (2001) Virtual fluoroscopy: image-guided fluoroscopic navigation. Spine 26:347–351

    Article  CAS  PubMed  Google Scholar 

  12. Ritter D, Mitschke M, Graumann R (2002) Markerless navigation with the intra-operative imaging modality SIREMOBIL Iso-C3D. Electromedica 70:47–52

    Google Scholar 

  13. Grützner PA, Waelti H, Vock B, Hebecker A, Nolte L-P, Wentzensen A (2004) Navigation using fluoro-CT technology. Eur J Trauma 30:161–170

    Google Scholar 

  14. Rajasekaran S, Karthik K, Chandra VR, Rajkumar N, Dheenadhayalan J (2010) Role of intraoperative 3D C-arm-based navigation in percutaneous excision of osteoid osteoma of lone bones in children. J Pediatr Orthop 19:195–200

    Article  Google Scholar 

  15. Lin EL, Park DK, Whang PG, An HS, Phillips FM (2008) O-Arm surgical imaging system. Semin Spine Surg 20:209–213

    Article  Google Scholar 

  16. Qureshi S, Lu Y, McAnany S, Baird E (2014) Three-dimensional intraoperative imaging modalities in orthopaedic surgery: a narrative review. J Am Acad Orthop Surg 22(12):800–809

    Article  PubMed  Google Scholar 

  17. Sati M, Stäubli HU, Bourquin Y, Kunz M, Nolte LP (2002) Real-time computerized in situ guidance system for ACL graft placement. Comput Aided Surg 7:25–40

    CAS  PubMed  Google Scholar 

  18. Fleute M, Lavallée S, Julliard R (1999) Incorporating a statistically based shape model into a system for computer assisted anterior cruciate ligament surgery. Med Image Anal 3:209–222

    Article  CAS  PubMed  Google Scholar 

  19. Stindel E, Briard JL, Merloz P, Plaweski S, Dubrana F, Lefevre C, Troccaz J (2002) Bone morphing: 3D morphological data for total knee arthroplasty. Comput Aided Surg 7:156–168

    Article  CAS  PubMed  Google Scholar 

  20. Zheng G, Dong X, Rajamani KT, Zhang X, Styner M, Thoranaghatte RU, Nolte L-P, Ballester MA (2007) Accurate and robust reconstruction of a surface model of the proximal femur from sparse-point data and a dense-point distribution model for surgical navigation. IEEE Trans Biomed Eng 54:2109–2122

    Article  PubMed  Google Scholar 

  21. Zheng G, Kowal J, Gonzalez Ballester MA, Caversaccio M, Nolte L-P (2007) Registration technique for computer navigation. Curr Orthop 21:170–179

    Article  Google Scholar 

  22. Lavallée S (1996) Registration for computer-integrated surgery: methodology, start of the art. In: Taylor RH, Lavallée S, Burdea GC, Mösges R (eds) Computer integrated surgery. The MIT Press, Cambridge, pp 77–97

    Google Scholar 

  23. Bargar WL, Bauer A, Börner M (1998) Primary and revision total hip replacement using the Robodoc system. Clin Orthop 354:82–91

    Article  Google Scholar 

  24. Nogler M, Maurer H, Wimmer C, Gegenhuber C, Bach C, Krismer M (2001) Knee pain caused by a fiducial marker in the medial femoral condyle: a clinical and anatomic study of 20 cases. Acta Orthop Scand 72:477–480

    Article  CAS  PubMed  Google Scholar 

  25. Besl PJ, McKay ND (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal 14(2):239–256

    Article  Google Scholar 

  26. Baechler R, Bunke H, Nolte L-P (2001) Restricted surface matching – numerical optimization and technical evaluation. Comput Aid Surg 6: 143–152

    Article  Google Scholar 

  27. Maurer CR, Gaston RP, Hill DLG, Gleeson MJ, Taylor MG, Fenlon MR, Edwards PJ, Hawkes DJ (1999) AcouStick: a tracked A-mode ultrasonography system for registration in image-guided surgery. In: Taylor C, Colchester A (eds) Medical image computing and image-guided intervention – MICCAI’99. Springer, Berlin, pp 953–962

    Chapter  Google Scholar 

  28. Oszwald M, Citak M, Kendoff D, Kowal J, Amstutz C, Kirchhoff T, Nolte L-P, Krettek C, Hüfner T (2008) Accuracy of navigated surgery of the pelvis after surface matching with an a-mode ultrasound proble. J Orthop Res 26:860–864

    Article  CAS  PubMed  Google Scholar 

  29. Kowal J, Amstutz C, Langlotz F, Talib H, Gonzalez Ballester MA (2007) Automated bone contour detection in ultrasound B-mode images for minimally invasive registration in image-guided surgery – an in vitro evaluation. Int J Med Rob Comput Assisted Surg 3:341–348

    Article  Google Scholar 

  30. Schumann S, Nolte L-P, Zheng G (2012) Compensation of sound speed deviations in 3D B-mode ultrasound for intraoperative determination of the anterior pelvic plane. IEEE Trans Inf Technol Biomed 16(1):88–97

    Article  PubMed  Google Scholar 

  31. Wein W, Karamalis A, Baumgarthner A, Navab N (2015) Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery. Int J Comput Assist Radiol Surg 10(6):971–979

    Article  PubMed  Google Scholar 

  32. Radermacher K, Portheine F, Anton M et al (1998) Computer assisted orthopaedic surgery with image based individual templates. Clin Orthop Relat Res 354:28–38

    Article  Google Scholar 

  33. Hafez MA, Chelule KL, Seedhom BB, Sherman KP (2006) Computer-assisted total knee arthroplasty using patient-specific templating. Clin Orthop Relat Res 444:184–192

    Article  CAS  PubMed  Google Scholar 

  34. Kunz M, Rudan JF, Xenoyannis GL, Ellis RE (2010) Computer-assisted hip resurfacing using individualized drill templates. J Arthroplast 25:600–606

    Article  Google Scholar 

  35. Shandiz MA, MacKenzie JR, Hunt S, Anglin C (2014 Sept) Accuracy of an adjustable patient-specific guide for acetabular alignment in hip replacement surgery (Optihip). Proc Inst Mech Eng H 228(9):876–889

    Article  PubMed  Google Scholar 

  36. Honl M, Dierk O, Gauck C, Carrero V, Lampe F, Dries S, Quante M, Schwieger K, Hille E, Morlock MM (2003) Comparison of robotic-assisted and manual implantation of a primary total hip replacement. A prospective study. J Bone Joint Surg 85A8:1470–1478

    Article  Google Scholar 

  37. Oszwald M, Ruan Z, Westphal R, O’Loughlin PF, Kendoff D, Hüfner T, Wahl F, Krettek C, Gosling T (2008) A rat model for evaluating physiological responses to femoral shaft fracture reduction using a surgical robot. J Orthop Res 26: 1656–1659

    Article  PubMed  Google Scholar 

  38. Oszwald M, Westphal R, Bredow J, Calafi A, Hüfner T, Wahl F, Krettek C, Gosling T (2010) Robot-assisted fracture reduction using three-dimensional intraoperative fracture visualization: an experimental study on human cadaver femora. J Orthop Res 28:1240–1244

    Article  PubMed  Google Scholar 

  39. Jaramaz B, Nikou C (2012) Precision freehand sculpting for unicondylar knee replacement: design and experimental validation. Biomed Tech 57(4):293–299

    Article  Google Scholar 

  40. Conditt MA, Roche MW (2009) Minimally invasive robotic-arm-guided unicompartmental knee arthroplasty. J Bone Joint Surg 91(Suppl 1):63–68

    Article  PubMed  Google Scholar 

  41. Ritschl P, Machacek F, Fuiko R (2003) Computer assisted ligament balancing in TKR using the Galileo system. In: Langlotz F, Davies BL, Bauer A (eds) Computer assisted orthopaedic surgery – 3rd annual meeting of CAOS-International (Proceedings). Steinkopff, Darmstadt, pp 304–305

    Google Scholar 

  42. Shoham M, Burman M, Zehavi E, Joskowicz L, Batkilin E, Kunicher Y (2003) Bone-mounted miniature robot for surgical procedures: concept and clinical applications. IEEE Trans Rob Autom 19:893–901

    Article  Google Scholar 

  43. de Siebenthal J, Gruetzner PA, Zimolong A, Rohrer U, Langlotz F (2004) Assessment of video tracking usability for training simulators. Comput Aided Surg 9:59–69

    Article  PubMed  Google Scholar 

  44. Clarke JV, Deakin AH, Nicol AC, Picard F (2010) Measuring the positional accuracy of computer assisted surgical tracking systems. Comput Aided Surg 15:13–18

    Article  CAS  PubMed  Google Scholar 

  45. Meskers CG, Fraterman H, van der Helm FC, Vermeulen HM, Rozing PM (1999) Calibration of the “Flock of Birds” electromagnetic tracking device and its application in shoulder motion studies. J Biomech 32:629–633

    Article  CAS  PubMed  Google Scholar 

  46. Wagner A, Schicho K, Birkfellner W, Figl M, Seemann R, Konig F, Kainberger F, Ewers R (2002) Quantitative analysis of factors affecting intraoperative precision and stability of optoelectronic and electromagnetic tracking systems. Med Phys 29:905–912

    Article  CAS  PubMed  Google Scholar 

  47. Nam D, Cody EA, Nguyen JT, Figgie MP, Mayman DJ (2014) Extramedullary guides versus portable, accelerometer-based navigation for tibial alignment in total knee arthroplasty: a randomized, controlled trial: winner of the 2013 Hap Paul Award. J Arthroplast 29(2):288–294

    Article  Google Scholar 

  48. Huang EH, Copp SN, Bugbee WD (2015) Accuracy of a handheld accelerometer-based navigation system for femoral and tibial resection in total knee arthroplasty. J Arthroplast 30(11):1906–1910

    Article  Google Scholar 

  49. Walti J, Jost GF, Cattin PC (2014) A new cost-effective approach to pedicular screw placement. In: AE-CAI 2014, LNCS 8678. Springer, Heidelberg, pp 90–97

    Google Scholar 

  50. Pflugi S, Liu L, Ecker TM, Schumann S, Cullmann JL, Siebenrock K, Zheng G (2016) A cost-effective surgical navigation solution for periacetabular osteotomy (PAO) surgery. Int J Comput Assist Radiol Surg 11(2):271–280

    Article  PubMed  Google Scholar 

  51. Pflugi S, Vasireddy R, Lerch T, Ecker TM, Tannast T, Boemake N, Siebenrock K, Zheng G (2018) A cost-effective surgical navigation solution for periacetabular osteotomy (PAO) surgery. Int J Comput Assist Radiol Surg 13(2):291–304

    Article  PubMed  Google Scholar 

  52. Nolte LP, Visarius H, Arm E, Langlotz F, Schwarzenbach O, Zamorano L (1995) Computer-aided fixation of spinal implants. J Imag Guid Surg 1:88–93

    Article  CAS  Google Scholar 

  53. Foley KT, Smith MM (1996) Image-guided spine surgery. Neurosurg Clin N Am 7:171–186

    Article  CAS  PubMed  Google Scholar 

  54. Glossop ND, Hu RW, Randle JA (1996) Computer-aided pedicle screw placement using frameless stereotaxis. Spine 21:2026–2034

    Article  CAS  PubMed  Google Scholar 

  55. Kalfas IH, Kormos DW, Murphy MA, McKenzie RL, Barnett GH, Bell GR, Steiner CP, Trimble MB, Weisenberger JP (1995) Application of frameless stereotaxy to pedicle screw fixation of the spine. J Neurosurg 83:641–647

    Article  CAS  PubMed  Google Scholar 

  56. Merloz P, Tonetti J, Pittet L, Coulomb M, Lavallée S, Sautot P (1998) Pedicle screw placement using image guided techniques. Clin Orthop 354:39–48

    Article  Google Scholar 

  57. Amiot LP, Lang K, Putzier M, Zippel H, Labelle H (2000) Comparative results between conventional and image-guided pedicle screw installation in the thoracic, lumbar, and sacral spine. Spine 25: 606–614

    Article  CAS  PubMed  Google Scholar 

  58. Laine T, Lund T, Ylikoski M, Lohikoski J, Schlenzka D (2000) Accuracy of pedicle screw insertion with and without computer assistance: a randomised controlled clinical study in 100 consecutive patients. Eur Spine J 9:235–240

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Schwarzenbach O, Berlemann U, Jost B, Visarius H, Arm E, Langlotz F, Nolte LP, Ozdoba C (1997) Accuracy of image-guided pedicle screw placement. An in vivo computed tomography analysis. Spine 22:452–458

    Article  CAS  PubMed  Google Scholar 

  60. Digioia AM 3rd, Simon DA, Jaramaz B et al (1999) HipNav: pre-operative planning and intra-operative navigational guidance for acetabular implant placement in total hip replacement surgery. In: Nolte LP, Ganz E (eds) Computer Assisted Orthopaedic Surgery (CAOS). Hogrefe & Huber, Seattle, pp 134–140

    Google Scholar 

  61. Croitoru H, Ellis RE, Prihar R, Small CF, Pichora DR (2001) Fixation based surgery: a new technique for distal radius osteotomy. Comput Aided Surg 6:160–169

    Article  CAS  PubMed  Google Scholar 

  62. Siebert W, Mai S, Kober R, Heeckt PF (2002) Technique and first clinical results of robot-assisted total knee replacement. Knee 9:173–180

    Article  PubMed  Google Scholar 

  63. Delp SL, Stulberg SD, Davies B, Picard F, Leitner F (1998) Computer assisted knee replacement. Clin Orthop 354:49–56

    Article  Google Scholar 

  64. Dessenne V, Lavallée S, Julliard R, Orti R, Martelli S, Cinquin P (1995) Computer assisted knee anterior cruciate ligament reconstruction: first clinical tests. J Image Guid Surg 1:59–64

    Article  CAS  PubMed  Google Scholar 

  65. Nolte LP, Slomczykowski MA, Berlemann U, Strauss MJ, Hofstetter R, Schlenzka D, Laine T, Lund T (2000) A new approach to computer-aided spine surgery: fluoroscopy-based surgical navigation. Eur Spine J 9:S78–S88

    Article  PubMed  Google Scholar 

  66. Zheng G, Marx A, Langlotz U, Widmer KH, Buttaro M, Nolte LP (2002) A hybrid CT-free navigation system for total hip arthroplasty. Comput Aided Surg 7:129–145

    Article  PubMed  Google Scholar 

  67. Suhm N, Jacob AL, Nolte LP, Regazzoni P, Messmer P (2000) Surgical navigation based on fluoroscopy – clinical application for image-guided distal locking of intramedullary implants. Comput Aided Surg 5:391–400

    Article  CAS  PubMed  Google Scholar 

  68. Sadoghi P (2015) Current concepts in total knee arthroplasty: patient specific instrumentation. World J Orthop 6(6):446–448

    Article  PubMed  PubMed Central  Google Scholar 

  69. Camarda L, D'Arienzo A, Morello S, Peri G, Valentino B, D’Arienzo M (2015 Apr) Patient-specific instrumentation for total knee arthroplasty: a literaturereview. Musculoskelet Surg 99(1):11–18

    Article  CAS  PubMed  Google Scholar 

  70. Olsen M, Naudie DD, Edwards MR, Sellan ME, McCalden RW, Schemitsch EH (2014 Mar) Evaluation of a patient specific femoral alignment guide for hip resurfacing. J Arthroplasty 29(3):590–595

    Article  PubMed  Google Scholar 

  71. Cartiaux O, Paul L, Francq BG, Banse X, Docquier PL (2014) Improved accuracy with 3D planning and patient-specific instruments during simulated pelvic bone tumor study. Ann Biomed Eng 42(1):205–213

    Article  PubMed  Google Scholar 

  72. Personal communication with Prof. Dr. K. Siebenrock, Inselspital, University of Bern

    Google Scholar 

  73. Rahmathulla G, Nottmeier E, Pirris S, Deen H, Pichelmann M (2014) Intraoperative image-guided spinal navigation: technical pitfalls and their avoidance. Neurosurg Focus 36(3):E3

    Article  PubMed  Google Scholar 

  74. Wang L, Traub J, Weidert S, Heining SM, Euler E, Navab N (2010) Parallax-free intra-operative x-ray image stitching. Med Image Anal 14(5):674–686

    Article  PubMed  Google Scholar 

  75. Chen C, Kojcev R, Haschtmann D, Fekete T, Nolte L, Zheng G (2015) Ruler based automatic C-arm image stitching without overlapping constraint. J Digit Imaging 28(4):474–480

    Article  PubMed  PubMed Central  Google Scholar 

  76. Chang J, Zhou L, Wang S, Clifford Chao KS (2012) Panoramic cone beam computed tomography. Med Phys 39(5):2930–2946

    Article  PubMed  Google Scholar 

  77. Chen C, Belavy D, Yu W, Chu C, Armbrecht G, Bansmann M, Felsenberg D (2015 Aug) G Zheng. Localization and segmentation of Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation. IEEE Trans Med Imaging 34(8):1719–1729

    Article  PubMed  Google Scholar 

  78. Zheng G, Li S, Székely G (2017) Statistical shape and deformation analysis: methods, implementation and applications. Elesvier, London

    Google Scholar 

  79. Zheng G, Gollmer S, Schumann S, Dong X, Feilkas T, González Ballester MA (2009 Dec) A 2D/3D correspondence building method for reconstruction of a patient-specific 3D bone surface model using point distribution models and calibrated X-ray images. Med Image Anal 13(6):883–899

    Article  PubMed  Google Scholar 

  80. Yu W, Tannast M, Zheng G (2017) Non-rigid free-form 2D-3D registration using b-spline-based statistical deformation model. Pattern Recongn 63: 689–699

    Article  Google Scholar 

  81. Driscoll M, Mac-Thiong JM, Labelle H, Parent S (2013) Development of a detailed volumetric finite element model of the spine to simulate surgical correction of spinal deformities. Biomed Res Int 2013:931741

    Article  PubMed  PubMed Central  Google Scholar 

  82. Majdouline Y, Aubin CE, Wang X, Sangole A, Labelle H (2012 Nov 26) Preoperative assessment and evaluation of instrumentation strategies for the treatment of adolescent idiopathic scoliosis: computer simulation and optimization. Scoliosis 7(1):21

    Article  PubMed  PubMed Central  Google Scholar 

  83. Murphy RJ, Armiger RS, Lepistö J, Mears SC, Taylor RH, Armand M (2015 Apr) Development of a biomechanical guidance system for periacetabular osteotomy. Int J Comput Assist Radiol Surg 10(4):497–508

    Article  PubMed  Google Scholar 

  84. Crottet D, Kowal J, Sarfert SA, Maeder T, Bleuler H, Nolte LP, Dürselen L (2007) Ligament balancing in TKA: Evaluation of a force-sensing device and the influence of patellar eversion and ligament release. J Biomech 40(8):1709–1715

    Article  PubMed  Google Scholar 

  85. De Keyser W, Beckers L (2010 Dec) Influence of patellar subluxation on ligament balancing in total knee arthroplasty through a subvastus approach. An in vivo study. Acta Orthop Belg 76(6):799–805

    PubMed  Google Scholar 

  86. de Steiger RN, Liu YL, Graves SE (2015 Apr 15) Computer navigation for total knee arthroplasty reduces revision rate for patients less than sixty-five years of age. J Bone Joint Surg Am 97(8):635–642

    Article  PubMed  Google Scholar 

  87. Jolesz FA (2014) Introduction. In: Jolesz FA (ed) Intraoperative imaging and image-guided therapy. Springer, London, pp 1–23

    Chapter  Google Scholar 

  88. Dubousset J, Charpak G, Skalli W, Deguise J, Kalifa G (2010) EOS: A new imaging system with low dose radiation in standing position for spine and bone & joint disorders. J Musculoskeleta Res 13: 1–12

    Article  Google Scholar 

  89. Wybier M, Bossard P (2013 May) Musculoskeletal imaging in progress: the EOS imaging system. Joint Bone Spine 80(3):238–243

    Article  PubMed  Google Scholar 

  90. Illés T, Somoskeöy S (2012) The EOS imaging system and its use in daily orthopaedic practice. Int Orthop 36:1325–1331

    Article  PubMed  PubMed Central  Google Scholar 

  91. Wade R, Yang H, McKenna C et al (2013) A systematic review of the clinical effectivenss of EOS 2D/3D x-ray imaging system. Eur Spine J 22: 296–304

    Article  PubMed  Google Scholar 

  92. Deschenes S, Charron G, Beaudoin G et al (2010) Diagnostic imaging of spinal deformities – Reducing patients radiation dose with a new slot-scanning x-ray imager. Spine 35:989–994

    Article  PubMed  Google Scholar 

  93. Langlois K, Pillet H, Lavaste F, Rochcongar G, Rouch P, Thoreux P, Skalli W (2015 Oct) Assessing the accuracy and precision of manual registration of both femur and tibia using EOS imaging system with multiple views. Comput Methods Biomech Biomed Eng 18(Suppl 1):1972–1973

    Article  Google Scholar 

  94. Ferrero E, Lafage R, Challier V, Diebo B, Guigui P, Mazda K, Schwab F, Skalli W, Lafage V (2015 Sept) Clinical and stereoradiographic analysis of adult spinal deformity with and without rotatory subluxation. Orthop Traumatol Surg Res 101(5): 613–618

    Article  CAS  PubMed  Google Scholar 

  95. Glaser DA, Doan J, Newton PO (2012) Comparison of 3-Dimensional spinal reconstruction accuracy. Spine 37:1391–1397

    Article  PubMed  Google Scholar 

  96. Lazennec JY, Rousseau MA, Rangel A, Gorin M, Belicourt C, Brusson A, Catonne Y (2011) Pelvis and total hip arthroplasty acetabular component orientation in sitting and standing positions: measurements reproductibility with EOS imaging system versus conventional radiographies. Orthop Traumatol Surg Res 97:373–380

    Article  CAS  PubMed  Google Scholar 

  97. Lazennec JY, Brusson A, Dominique F, Rousseau MA, Pour AE (2015) Offset and anteversion reconstruction after cemented and uncemented total hip arthroplasty: an evaluation with the low-dose EOS system comaring two- and three-dimensional imaging. Int Orthop. 39(7):1259–1267

    Article  PubMed  Google Scholar 

  98. Folinais D, Thelen P, Delin C, Radier C, Catonne Y, Lazennec JY (2011) Measuring femoral and rotational alignment: EOS system versus computed tomography. Orthop Traumatol Surg Res 99: 509–516

    Article  Google Scholar 

  99. Zheng G, Schumann S, Alcoltekin A, Jaramaz B, Nolte L-P (2016) Patient-specific 3D reconstruction of a complete lower extremity from 2D X-rays. In: Proceedings of MIAR 2016, LNCS 9805. Springer, Heidelberg, pp 404–414

    Google Scholar 

  100. Hommel H, Alcoltekin A, Thelen B, Stifter J, Schwägli T, Zheng G (2017) 3X-Plan: A novel technology for 3D prosthesis planning using 2D X-ray radiographs. Proc CAOS 2017:93–95

    Google Scholar 

  101. Glocker B, Feulner J, Criminisi A, Haynor DR, Konukoglu E (2012) Automatic localization and identification of vertebrae in arbitrary field-of-view CT scans. In: Proceedings of MICCAI 2012; 15(Pt3). Springer, Heidelberg, pp 590–598

    Google Scholar 

  102. Liu Q, Wang Q, Zhang L, Gao Y, Sheng D (2015) Multi-atlas context forests for knee MR image segmentation. MLMI@MICCAI 2015:186–193

    Google Scholar 

  103. Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, van der Laak JAWM, van Ginneken B, Sánchez CI (2017) A survey on deep learning in medical image analysis. Med Image Anal 42:60–88

    Article  PubMed  Google Scholar 

  104. Krizhevsky A, Sutskever I, Hinton GE (2012) ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems 25, Curran Associates, Inc., 2012, 1097–1105

    Google Scholar 

  105. Prasoon A, Petersen K, Igel C, Lauze F, Dam E, Nielsen M (2013) Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network. MICCAI 2013 16(Pt2): 246–253

    Google Scholar 

  106. Zeng G, Yang X, Li J, Yu L, Heng P-A, Zheng G (2017) 3D U-net with multi-level deep supervision: fully automatic segmentation of proximal femur in 3D MR images. MLMI@MICCAI 2017: 274–282

    Google Scholar 

  107. Li X, Dou Q, Chen H, Fu CW, Qi X, Belavý DL, Armbrecht G, Felsenberg D, Zheng G, Heng PA (2018) 3D multi-scale FCN with random modality voxel dropout learning for intervertebral disc localization and segmentation from multi-modality MR images. Med Image Anal 45:41–54

    Article  PubMed  Google Scholar 

  108. Janssens R, Zeng G, Zheng G (2017) Fully automatic segmentation of lumbar vertebrae from CT images using cascaded 3D fully convolutional networks. arXiv:1712.01509

    Google Scholar 

Download references

Acknowledgements

This chapter was modified from the paper published by our group in Frontiers in Surgery (Zheng and Nolte 2016; 2:66). The related contents were reused with the permission.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guoyan Zheng .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zheng, G., Nolte, LP. (2018). Computer-Aided Orthopaedic Surgery: State-of-the-Art and Future Perspectives. In: Zheng, G., Tian, W., Zhuang, X. (eds) Intelligent Orthopaedics. Advances in Experimental Medicine and Biology, vol 1093. Springer, Singapore. https://doi.org/10.1007/978-981-13-1396-7_1

Download citation

Publish with us

Policies and ethics