Regression forest-based automatic estimation of the articular margin plane for shoulder prosthesis planning

Medical Image Analysis

Volumn 31, Issue , 2016, Pages 88-97

  Tschannen, Michael ^a   Vlachopoulos, Lazaros ^a,b   Gerber, Christian ^b   Székely, Gábor ^a   Fürnstahl, Philipp ^b  

^a ETH ZURICH   (Switzerland)

^b BALGRIST UNIVERSITY HOSPITAL   (Switzerland)

Author keywords

Computer assisted preoperative planning; Humerus; Orthopedic surgery; Sheetness measure

Indexed keywords

ARTHROPLASTY; BONE; COMPUTERIZED TOMOGRAPHY; FORESTRY; ORTHOPEDICS; PROSTHETICS;

AUTOMATIC ESTIMATION; HUMERUS; LOCALIZATION ERRORS; ORTHOPEDIC SURGERY; PRE-OPERATIVE PLANNING; REGRESSION FORESTS; SHEETNESS MEASURE; SHOULDER ARTHROPLASTY;

MAPPING;

ANALYTICAL PARAMETERS; ARTICLE; ARTICULAR MARGIN PLANE; CADAVER; COMPARATIVE STUDY; COMPUTED TOMOGRAPHY SCANNER; COMPUTER ASSISTED TOMOGRAPHY; CORTICAL BONE; FORENSIC MEDICINE; HEALTH CARE PLANNING; HUMAN; HUMERUS HEAD; NORMAL DISTRIBUTION; PREOPERATIVE CARE; PRIORITY JOURNAL; REGRESSION FOREST; SHOULDER ARTHROPLASTY; SHOULDER PROSTHESIS; WHOLE BODY CT; ALGORITHM; AUTOMATED PATTERN RECOGNITION; BONE IMPLANT INTERFACE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED SURGERY; COMPUTER SIMULATION; DEVICES; DIAGNOSTIC IMAGING; HUMERAL HEAD; IMAGE ENHANCEMENT; MACHINE LEARNING; PROCEDURES; PROSTHETIC FITTING; REGRESSION ANALYSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SHOULDER; SHOULDER REPLACEMENT; STATISTICAL MODEL; SURGERY; X-RAY COMPUTED TOMOGRAPHY;

ALGORITHMS; ARTHROPLASTY, REPLACEMENT, SHOULDER; BONE-IMPLANT INTERFACE; COMPUTER SIMULATION; HUMANS; HUMERAL HEAD; MACHINE LEARNING; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PROSTHESIS FITTING; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SHOULDER JOINT; SHOULDER PROSTHESIS; SURGERY, COMPUTER-ASSISTED; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84961223792     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2016.02.008     Document Type: Article

References (45)

1. Bicknell R.T., DeLude J.A., Kedgley A.E., Ferreira L.M., Dunning C.E., King G.J., Faber K.J., Johnson J.A., Drosdowech D.S. Early experience with computer-assisted shoulder hemiarthroplasty for fractures of the proximal humerus: development of a novel technique and an in vitro comparison with traditional methods. J. Shoulder Elbow Surg. 2007, 16:S117-S125. American Shoulder and Elbow Surgeons ... [et al.].
2. Bohsali K.I., Wirth M.A., Rockwood C.A. Complications of total shoulder arthroplasty. J. Bone Joint Surg. Am. 2006, 88:2279-2292.
3. Boileau P., Bicknell R., Mazzoleni N., Walch G., Urien J. CT scan method accurately assesses humeral head retroversion. Clin. Orthop. Relat. Res. 2008, 466:661-669.
4. Boileau P., Krishnan S., Tinsi L., Walch G., Coste J., Mole D. Tuberosity malposition and migration: reasons for poor outcomes after hemiarthroplasty for displaced fractures of the proximal humerus. J. Shoulder Elbow Surg. 2002, 11:401-412.
5. Boileau P., Walch G. The three-dimensional geometry of the proximal humerus. Implications for surgical technique and prosthetic design. J. Bone Joint Surg. Br. 1997, 79:857-865.
6. Breiman L. Random forests. Mach. Learn. 2001, 45:5-32.
7. Casciaro M.E., Craiem D. Towards automatic measurement of anteversion and neck-shaft angles in human femurs using CT images. Comput. Methods Biomech. Biomed. Eng. 2014, 17:128-136.
8. Chen C., Zheng G. Fully automatic segmentation of AP pelvis x-rays via random forest regression and hierarchical sparse shape composition. Computer Analysis of Images and Patterns 2013, 335-343. Springer.
9. Criminisi A., Shotton J. Decision Forests for Computer Vision and Medical Image Analysis 2013, Springer.
10. Criminisi A., Shotton J., Criminisi A., Shotton J. Regression forests. Decision Forests for Computer Vision and Medical Image Analysis 2013, 47-58. Springer, London.
11. Criminisi A., Shotton J., Robertson D., Konukoglu E. Regression forests for efficient anatomy detection and localization in CT studies. Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging 2011, 106-117. Springer.
12. Day J.S., Lau E., Ong K.L., Williams G.R., Ramsey M.L., Kurtz S.M. Prevalence and projections of total shoulder and elbow arthroplasty in the United States to 2015. J. Shoulder Elbow Surg. 2010, 19:1115-1120.
13. DeLude J.A., Bicknell R.T., MacKenzie G.A., Ferreira L.M., Dunning C.E., King G.J., Johnson J.A., Drosdowech D.S. An anthropometric study of the bilateral anatomy of the humerus. J. Shoulder Elbow Surg. 2007, 16:477-483.
14. Descoteaux M., Audette M., Chinzei K., Siddiqi K. Bone enhancement filtering: application to sinus bone segmentation and simulation of pituitary surgery. Comput. Aided Surg. 2006, 11:247-255.
15. Dollár P., Welinder P., Perona P. Cascaded pose regression. 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010, 1078-1085. IEEE.
16. Donner R., Menze B.H., Bischof H., Langs G. Global localization of 3D anatomical structures by pre-filtered Hough forests and discrete optimization. Med. Image Anal. 2013, 17:1304-1314.
17. Ebner T., Stern D., Donner R., Bischof H., Urschler M. Towards automatic bone age estimation from MRI: localization of 3D anatomical landmarks. Medical Image Computing and Computer-Assisted Intervention-MICCAI 2014 2014, 421-428. Springer.
18. Edwards T.B., Gartsman G.M., O'Connor D.P., Sarin V.K. Safety and utility of computer-aided shoulder arthroplasty. J. Shoulder Elbow Surg. 2008, 17:503-508. American Shoulder and Elbow Surgeons ... [et al.].
19. Ehrhardt J., Handels H., Strathmann B., Malina T., Plötz W., Pöppl S.J. Atlas-based recognition of anatomical structures and landmarks to support the virtual three-dimensional planning of hip operations. Medical Image Computing and Computer-Assisted Intervention-MICCAI 2003 2003, 17-24. Springer.
20. Fanelli G., Gall J., Van Gool L. Real time head pose estimation with random regression forests. 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2011, 617-624. IEEE.
21. Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J.-C., Pujol S., Bauer C., Jennings D., Fennessy F., Sonka M. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn. Reson. Imaging 2012, 30:1323-1341.
22. Fucentese S.F., Costouros J.G., Kuhnel S.P., Gerber C. Total shoulder arthroplasty with an uncemented soft-metal-backed glenoid component. J. Shoulder Elbow Surg. 2010, 19:624-631.
23. Fürnstahl P., Fuchs T., Schweizer A., Nagy L., Székely G., Harders M. Automatic and robust forearm segmentation using graph cuts. 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2008 2008, 77-80.
24. Fürnstahl P., Székely G., Gerber C., Hodler J., Snedeker J.G., Harders M. Computer assisted reconstruction of complex proximal humerus fractures for preoperative planning. Med. Image Anal. 2012, 16:704-720.
25. Gao Y., Shen D. Context-aware anatomical landmark detection: application to deformable model initialization in prostate CT images. Machine Learning in Medical Imaging 2014, 165-173. Springer.
26. Gass T., Székely G., Goksel O. Simultaneous segmentation and multiresolution nonrigid atlas registration. IEEE Trans. Image Process. 2014, 23:2931-2943.
27. Glocker B., Feulner J., Criminisi A., Haynor D.R., Konukoglu E. Automatic localization and identification of vertebrae in arbitrary field-of-view CT scans. Medical Image Computing and Computer-Assisted Intervention-MICCAI 2012 2012, 590-598. Springer.
28. Han D., Gao Y., Wu G., Yap P.-T., Shen D. Robust anatomical landmark detection with application to MR brain image registration. Comput. Med. Imaging Graphics 2015, 46(3):277-290.
29. Hertel R., Knothe U., Ballmer F.T. Geometry of the proximal humerus and implications for prosthetic design. J. Shoulder Elbow Surg. 2002, 11:331-338.
30. Huffman G.R., Itamura J.M., McGarry M.H., Duong L., Gililland J., Tibone J.E., Lee T.Q. Neer award 2006: biomechanical assessment of inferior tuberosity placement during hemiarthroplasty for four-part proximal humeral fractures. J. Shoulder Elbow Surg. 2008, 17:189-196.
31. Iannotti J., Baker J., Rodriguez E., Brems J., Ricchetti E., Mesiha M., Bryan J. Three-dimensional preoperative planning software and a novel information transfer technology improve glenoid component positioning. J. Bone Joint Surg. Am. 2014, 96:e71.
32. Iannotti J.P., Gabriel J.P., Schneck S.L., Evans B.G., Misra S. The normal glenohumeral relationships. An anatomical study of one hundred and forty shoulders. J. Bone Joint Surg. Am. 1992, 74:491-500.
33. Johnson J.W., Thostenson J.D., Suva L.J., Hasan S.A. Relationship of bicipital groove rotation with humeral head retroversion. J. Bone Joint Surg. 2013, 95:719-724.
34. Kelm M.B., Wels M., Kevin Zhou S., Seifert S., Suehling M., Zheng Y., Comaniciu D. Spine detection in CT and MR using iterated marginal space learning. Med. Image Anal. 2013, 17:1283-1292.
35. Kircher J., Wiedemann M., Magosch P., Lichtenberg S., Habermeyer P. Improved accuracy of glenoid positioning in total shoulder arthroplasty with intraoperative navigation: a prospective-randomized clinical study. J. Shoulder Elbow Surg. 2009, 18:515-520.
36. Lindner C., Thiagarajah S., Wilkinson J.M., Consortium T., Wallis G., Cootes T. Fully automatic segmentation of the proximal femur using random forest regression voting. IEEE Trans. Med. Imaging 2013, 32:1462-1472.
37. Nguyen D., Ferreira L.M., Brownhill J.R., King G.J., Drosdowech D.S., Faber K.J., Johnson J.A. Improved accuracy of computer assisted glenoid implantation in total shoulder arthroplasty: an in-vitro randomized controlled trial. J. Shoulder Elbow Surg. 2009, 18:907-914.
38. Ponce B.A., Oladeji L.O., Rogers M.E., Menendez M.E. Comparative analysis of anatomic and reverse total shoulder arthroplasty: in-hospital outcomes and costs. J. Shoulder Elbow Surg. 2015, 24:460-467.
39. Ruppertshofen H., Lorenz C., Schmidt S., Beyerlein P., Salah Z., Rose G., Schramm H. Discriminative Generalized Hough transform for localization of joints in the lower extremities. Comput. Sci. Res. Dev. 2011, 26:97-105.
40. Schneider P., Eberly D.H. Geometric Tools for Computer Graphics 2002, Morgan Kaufmann.
41. Shotton J., Girshick R., Fitzgibbon A., Sharp T., Cook M., Finocchio M., Moore R., Kohli P., Criminisi A., Kipman A. Efficient human pose estimation from single depth images. Decision Forests for Computer Vision and Medical Image Analysis 2013, 175-192. Springer.
42. Smith K., Carleton A., Lepetit V. Fast ray features for learning irregular shapes. 2009 IEEE 12th International Conference on Computer Vision 2009, 397-404.
43. van der Glas M, Vos F.M., Botha C.P., Vossepoel A.M. Determination of position and radius of ball joints. Medical Imaging 2002 2002, 1571-1577. International Society for Optics and Photonics.
44. Viola P., Jones M.J. Robust real-time face detection. Int. J. Comput. Vision 2004, 57:137-154.
45. Vlachopoulos L., Dünner C., Gass T., Graf M., Goksel O., Gerber C., Székely G., Fürnstahl P. Computer algorithms for three-dimensional measurement of humeral anatomy: analysis of 140 paired humeri. J. Shoulder Elbow Surg. 2016, 25(2):e38-e48.