{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T12:20:37Z","timestamp":1770898837203,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030111656","type":"print"},{"value":"9783030111663","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-11166-3_3","type":"book-chapter","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T00:00:38Z","timestamp":1546992038000},"page":"22-34","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Fully Automatic Planning of Total Shoulder Arthroplasty Without Segmentation: A Deep Learning Based Approach"],"prefix":"10.1007","author":[{"given":"Paul","family":"Kulyk","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lazaros","family":"Vlachopoulos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philipp","family":"F\u00fcrnstahl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoyan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,1,9]]},"reference":[{"issue":"24","key":"3_CR1","doi-asserted-by":"publisher","first-page":"2249","DOI":"10.2106\/JBJS.J.01994","volume":"93","author":"S Kim","year":"2011","unstructured":"Kim, S., Wise, B., Zhang, Y., Szabo, R.: Increasing incidence of shoulder arthroplasty in the United States. J. Bone Joint Surg. Am. 93(24), 2249\u20132254 (2011). https:\/\/doi.org\/10.2106\/JBJS.J.01994","journal-title":"J. Bone Joint Surg. Am."},{"issue":"6","key":"3_CR2","doi-asserted-by":"publisher","first-page":"427","DOI":"10.5435\/JAAOS-D-15-00682","volume":"25","author":"J Keener","year":"2017","unstructured":"Keener, J., Chalmers, P., Yamaguchi, K.: The humeral implant in shoulder arthroplasty. J. Am. Acad. Orthop. Surg. 25(6), 427\u2013438 (2017). https:\/\/doi.org\/10.5435\/JAAOS-D-15-00682","journal-title":"J. Am. Acad. Orthop. Surg."},{"key":"3_CR3","volume-title":"Shoulder Arthroplasty","author":"T Edwards","year":"2019","unstructured":"Edwards, T., Morris, B., Gartsman, G.: Shoulder Arthroplasty, 2nd edn. Elsevier, Amsterdam (2019)","edition":"2"},{"key":"3_CR4","volume-title":"Arthritis & Arthroplasty: The Shoulder","year":"2009","unstructured":"Dines, D., Laurencin, C., Williams, G. (eds.): Arthritis & Arthroplasty: The Shoulder. Saunders\/Elsevier, Philadelphia (2009)"},{"issue":"Suppl 1","key":"3_CR5","doi-asserted-by":"publisher","first-page":"S99","DOI":"10.1016\/j.jse.2004.09.025","volume":"14","author":"M Pearl","year":"2005","unstructured":"Pearl, M.: Proximal humeral anatomy in shoulder arthroplasty: implications for prosthetic design and surgical technique. J. Shoulder Elbow Surg. 14(Suppl 1), S99\u2013S104 (2005). https:\/\/doi.org\/10.1016\/j.jse.2004.09.025","journal-title":"J. Shoulder Elbow Surg."},{"issue":"4","key":"3_CR6","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1016\/j.jse.2006.09.016","volume":"16","author":"J DeLude","year":"2007","unstructured":"DeLude, J., et al.: An anthropometric study of the bilateral anatomy of the humerus. J. Shoulder Elbow Surg. 16(4), 477\u2013483 (2007). https:\/\/doi.org\/10.1016\/j.jse.2006.09.016","journal-title":"J. Shoulder Elbow Surg."},{"issue":"8","key":"3_CR7","doi-asserted-by":"publisher","first-page":"719","DOI":"10.2106\/JBJS.J.00085","volume":"95","author":"J Johnson","year":"2013","unstructured":"Johnson, J., Thostenson, J., Suva, L., Hasan, S.: Relationship of bicipital groove rotation with humeral head retroversion: a three-dimensional computed tomographic analysis. J. Bone Joint Surg. Am. 95(8), 719\u2013724 (2013). https:\/\/doi.org\/10.2106\/JBJS.J.00085","journal-title":"J. Bone Joint Surg. Am."},{"issue":"2","key":"3_CR8","doi-asserted-by":"publisher","first-page":"e38","DOI":"10.1016\/j.jse.2015.07.027","volume":"25","author":"L Vlachopoulos","year":"2016","unstructured":"Vlachopoulos, L., et al.: Computer algorithms for three-dimensional measurement of humeral anatomy: analysis of 140 paired humeri. J. Shoulder Elbow Surg. 25(2), e38\u2013e48 (2016). https:\/\/doi.org\/10.1016\/j.jse.2015.07.027","journal-title":"J. Shoulder Elbow Surg."},{"key":"3_CR9","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.media.2016.02.008","volume":"31","author":"M Tschannen","year":"2016","unstructured":"Tschannen, M., Vlachopoulos, L., Gerber, C., Sz\u00e9kely, G., F\u00fcrnstahl, P.: Regression forest-based automatic estimation of the articular margin plane for shoulder prosthesis planning. Med. Image Anal. 31, 88\u201397 (2016). https:\/\/doi.org\/10.1016\/j.media.2016.02.008","journal-title":"Med. Image Anal."},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Janssens, R., Zeng, G., Zheng, G.: Fully automatic segmentation of lumbar vertebrae from CT images using cascaded 3D fully convolutional networks. arXiv:1712.01509 (2017). http:\/\/arxiv.org\/abs\/1712.01509","DOI":"10.1109\/ISBI.2018.8363715"},{"key":"3_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1007\/978-3-319-46723-8_27","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"C Payer","year":"2016","unstructured":"Payer, C., \u0160tern, D., Bischof, H., Urschler, M.: Regressing heatmaps for multiple landmark localization using CNNs. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 230\u2013238. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46723-8_27"},{"key":"3_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1007\/978-3-319-66185-8_81","volume-title":"Medical Image Computing and Computer Assisted Intervention","author":"J Zhang","year":"2017","unstructured":"Zhang, J., et al.: Joint craniomaxillofacial bone segmentation and landmark digitization by context-guided fully convolutional networks. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10434, pp. 720\u2013728. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66185-8_81"},{"issue":"1","key":"3_CR13","doi-asserted-by":"publisher","first-page":"57","DOI":"10.2106\/JBJS.16.01122","volume":"100","author":"P Boileau","year":"2018","unstructured":"Boileau, P., Cheval, D., Gauci, M., Holzer, N., Chaoui, J., Walch, G.: Automated three-dimensional measurement of glenoid version and inclination in arthritic shoulders. J. Bone Joint Surg. Am. 100(1), 57\u201365 (2018). https:\/\/doi.org\/10.2106\/JBJS.16.01122","journal-title":"J. Bone Joint Surg. Am."},{"issue":"6","key":"3_CR14","doi-asserted-by":"publisher","first-page":"907","DOI":"10.1016\/j.jse.2009.02.022","volume":"18","author":"D Nguyen","year":"2009","unstructured":"Nguyen, D., et al.: Improved accuracy of computer assisted glenoid implantation in total shoulder arthroplasty: an in-vitro randomized controlled trial. J. Shoulder Elbow Surg. 18(6), 907\u2013914 (2009). https:\/\/doi.org\/10.1016\/j.jse.2009.02.022","journal-title":"J. Shoulder Elbow Surg."},{"issue":"8","key":"3_CR15","doi-asserted-by":"publisher","first-page":"1477","DOI":"10.1016\/j.jse.2017.01.006","volume":"26","author":"B Werner","year":"2017","unstructured":"Werner, B., Hudek, R., Burkhart, K., Gohlke, F.: The influence of three-dimensional planning on decision-making in total shoulder arthroplasty. J. Shoulder Elbow Surg. 26(8), 1477\u20131483 (2017). https:\/\/doi.org\/10.1016\/j.jse.2017.01.006","journal-title":"J. Shoulder Elbow Surg."},{"key":"3_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1007\/978-3-319-24574-4_81","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2014 MICCAI 2015","author":"A Suzani","year":"2015","unstructured":"Suzani, A., Seitel, A., Liu, Y., Fels, S., Rohling, R.N., Abolmaesumi, P.: Fast automatic vertebrae detection and localization in pathological CT scans - a deep learning approach. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 678\u2013686. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_81"},{"key":"3_CR17","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. arXiv:1412.6980 (2014). http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"3_CR18","unstructured":"Abadi, M., et al.: TensorFlow: a system for large-scale machine learning. arXiv:1605.08695 (2016). http:\/\/arxiv.org\/abs\/1605.08695"}],"container-title":["Lecture Notes in Computer Science","Computational Methods and Clinical Applications in Musculoskeletal Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-11166-3_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T01:01:58Z","timestamp":1704675718000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-11166-3_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030111656","9783030111663"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-11166-3_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"9 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MSKI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Computational Methods and Clinical Applications in Musculoskeletal Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mski2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mski2018.wordpress.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}