{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T08:20:13Z","timestamp":1790756413506,"version":"4.1.0"},"reference-count":20,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2017,2,17]],"date-time":"2017-02-17T00:00:00Z","timestamp":1487289600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"MEXT\/JSPS Grant-in-Aid for Scientific Research on Innovative Areas","award":["26108004"],"award-info":[{"award-number":["26108004"]}]},{"name":"MEXT\/JSPS Grant-in-Aid for Scientific Research","award":["25242051"],"award-info":[{"award-number":["25242051"]}]},{"name":"JST PRESTO","award":["20407"],"award-info":[{"award-number":["20407"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics Computer Surgery"],"published-print":{"date-parts":[[2017,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Computer\u2010assisted corrective osteotomy using a mirror image of the normal contralateral shape as reference is increasingly used. Instead, we propose to use the shape predicted by statistical learning to deal with cases demonstrating bilateral abnormality, such as bilateral trauma, congenital disease, and metabolic disease.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Computed tomography (CT) scans of 100 normal forearms were used in this study. The whole bone shape was predicted from its partial shape based on statistical learning of the other 99 bones. Accuracy was evaluated by average symmetric surface distance (ASD), and translational and rotational errors.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>ASDs for predicted shapes were 0.71\u20131.03\u00a0mm. Mean absolute translational and rotational errors were 0.48\u20131.76\u00a0mm and 0.99\u20136.08\u00b0, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Normal bone shape was predicted with an acceptable accuracy from its partial shape using statistical learning. Predicted shape can be an alternative to a mirror image, which may enable reduced radiation exposure and examination costs.<\/jats:p><\/jats:sec>","DOI":"10.1002\/rcs.1807","type":"journal-article","created":{"date-parts":[[2017,2,17]],"date-time":"2017-02-17T10:13:58Z","timestamp":1487326438000},"source":"Crossref","is-referenced-by-count":8,"title":["Prediction of forearm bone shape based on partial least squares regression from partial shape"],"prefix":"10.1002","volume":"13","author":[{"given":"Keiichiro","family":"Oura","sequence":"first","affiliation":[{"name":"Department of Orthopaedic Surgery Japan Community Health care Organization Osaka Hospital  Osaka Japan"},{"name":"Department of Orthopaedic Surgery Osaka University Graduate School of Medicine  Osaka Japan"},{"name":"Graduate School of Information Science Nara Institute of Science and Technology (NAIST)  Nara 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