{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:50:43Z","timestamp":1760151043244,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,7]],"date-time":"2022-02-07T00:00:00Z","timestamp":1644192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Cone-beam dental CT can provide high-precision 3D images of the teeth and surrounding bones. From the 3D CT images, 3D models, also called digital impressions, can be computed for CAD\/CAM-based fabrication of dental restorations or orthodontic devices. However, the cone-beam angle-dependent artifacts, mostly caused by the incompleteness of the projection data acquired in the circular cone-beam scan geometry, can induce significant errors in the 3D models. Using a micro-CT, we acquired CT projection data of plaster cast models at several different cone-beam angles, and we investigated the dependency of the model errors on the cone-beam angle in comparison with the reference models obtained from the optical scanning of the plaster models. For the 3D CT image reconstruction, we used the conventional Feldkamp algorithm and the combined half-scan image reconstruction algorithm to investigate the dependency of the model errors on the image reconstruction algorithm. We analyzed the mean of positive deviations and the mean of negative deviations of the surface points on the CT-image-derived 3D models from the reference model, and we compared them between the two image reconstruction algorithms. It has been found that the model error increases as the cone-beam angle increases in both algorithms. However, the model errors are smaller in the combined half-scan image reconstruction when the cone-beam angle is as large as 10 degrees.<\/jats:p>","DOI":"10.3390\/s22031253","type":"journal-article","created":{"date-parts":[[2022,2,7]],"date-time":"2022-02-07T20:36:42Z","timestamp":1644266202000},"page":"1253","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Cone-Beam Angle Dependency of 3D Models Computed from Cone-Beam CT Images"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8449-7282","authenticated-orcid":false,"given":"Myung Hye","family":"Cho","sequence":"first","affiliation":[{"name":"R&D Center, Ray, Seongnam-si 13494, Korea"},{"name":"Department of Biomedical Engineering, Kyung Hee University, Yongin-si 17104, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7192-2641","authenticated-orcid":false,"given":"Mohamed A. A.","family":"Hegazy","sequence":"additional","affiliation":[{"name":"R&D Center, Ray, Seongnam-si 13494, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min Hyoung","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Kyung Hee University, Yongin-si 17104, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7573-2079","authenticated-orcid":false,"given":"Soo Yeol","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Kyung Hee University, Yongin-si 17104, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1364\/JOSAA.1.000612","article-title":"Practical cone-beam algorithm","volume":"1","author":"Feldkamp","year":"1984","journal-title":"J. Opt. Soc. Am. 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