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Recently, an automatic single\u2010plane fluoroscopic method utilizing machine learning has been developed to facilitate a quick and simple process for measuring TKR kinematics. This study aimed to validate the new automatic single\u2010plane technique using biplanar radiostereometric analysis (RSA) as the gold standard. Twenty\u2010four knees were imaged at various angles of flexion in a dedicated RSA lab and 113 image pairs were obtained. Only the lateral RSA images were used for the automatic single\u2010plane technique to simulate single\u2010plane fluoroscopy. Two networks helped automate the kinematics measurement process, one segmented implant components and the other generated an initial pose estimate for the optimization algorithm. Kinematics obtained via the automatic single plane and manual biplane techniques were compared using root\u2010mean\u2010square error and Bland\u2013Altman plots. Two observers measured the kinematics using the automated technique and results were compared with assess reproducibility. Root\u2010mean\u2010square errors were 0.8\u2009mm\u00a0for anterior\u2013posterior translation, 0.5\u2009mm\u00a0for superior\u2013inferior translation, 2.6\u2009mm for medial\u2013lateral translation, 1.0\u00b0 for flexion\u2013extension, 1.2\u00b0 for abduction\u2013adduction, and 1.7\u00b0 for internal\u2013external rotation. Reproducibility, reported as root\u2010mean\u2010square errors between operator measurements, was submillimeter for in\u2010plane translations and below 2\u00b0 for all rotations. Clinical Significance: The advantages of the automated single plane technique should aid in the kinematic measurement process and help researchers and clinicians perform TKR kinematic analyses.<\/jats:p>","DOI":"10.1002\/jor.25518","type":"journal-article","created":{"date-parts":[[2023,1,24]],"date-time":"2023-01-24T09:39:56Z","timestamp":1674553196000},"page":"1767-1773","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Validation of a machine learning technique for segmentation and pose estimation in single plane fluoroscopy"],"prefix":"10.1002","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8923-8338","authenticated-orcid":false,"given":"Jordan S.","family":"Broberg","sequence":"first","affiliation":[{"name":"Department of Medical Biophysics, Schulich School of Medicine and Dentistry Western University London Canada"},{"name":"Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine and Dentistry Western University London Canada"},{"name":"Surgical Innovation Program Lawson Health Research Institute  London Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joanna","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Medical Biophysics, Schulich School of Medicine and Dentistry Western University London Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"Jensen","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering University of Florida Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0404-6826","authenticated-orcid":false,"given":"Scott A.","family":"Banks","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering University of Florida Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3911-3171","authenticated-orcid":false,"given":"Matthew G.","family":"Teeter","sequence":"additional","affiliation":[{"name":"Department of Medical Biophysics, Schulich School of Medicine and Dentistry Western University London Canada"},{"name":"Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine and Dentistry Western University London Canada"},{"name":"Surgical Innovation Program Lawson Health Research Institute  London Canada"},{"name":"Division of Orthopedic Surgery, Department of Surgery, Schulich School of Medicine and Dentistry Western University and London Health Sciences Centre London Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,2]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.blo.0000092986.12414.b5"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.blo.0000148777.98244.84"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.arth.2017.09.035"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00167-018-4842-5"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11999-008-0440-z"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.arth.2019.05.037"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1097\/00003086-199610000-00015"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1097\/00003086-199112000-00036"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.arth.2017.09.064"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.5435\/JAAOS-D-16-00628"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2016.03.006"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/10.495283"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.385980"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.811310"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2773398"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2003.820027"},{"key":"e_1_2_7_18_1","series-title":"In: Medical Image Computing and Computer\u2010Assisted Intervention\u2014MICCAI 2015.\u00a0","volume-title":"U\u2010Net: Convolutional Networks for Biomedical Image Segmentation.\u00a0","author":"Ronneberger O"},{"key":"e_1_2_7_19_1","unstructured":"KrizhevskyA SutskeverI HintonGE. 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