The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence
This study aimed at evaluating the precision of the segmented tooth model (STM) that was produced by the artificial intelligence (AI) program (CephX®) with an intraoral scan (IOS) and insignia outcomes. Methods. 10 patients with Cl I malocclusion (mild-to-moderate crowding) who underwent nonextracti...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2023/5933003 |
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| author | Ammar Sh. Al-Ubaydi Dheaa Al-Groosh |
| author_facet | Ammar Sh. Al-Ubaydi Dheaa Al-Groosh |
| author_sort | Ammar Sh. Al-Ubaydi |
| collection | DOAJ |
| description | This study aimed at evaluating the precision of the segmented tooth model (STM) that was produced by the artificial intelligence (AI) program (CephX®) with an intraoral scan (IOS) and insignia outcomes. Methods. 10 patients with Cl I malocclusion (mild-to-moderate crowding) who underwent nonextraction orthodontic therapy with the Insignia™ system had IOS and CBCT scans taken before treatment. AI was used to produce a total of 280 STMs; each tooth will be measured from three aspects (apexo-occlusal, mesiodistal, and labiolingual) for DICOM and STL formats. Also, root volume measurements for each tooth generated by using the CephX® software and Insignia™ system were compared. The software used for these measurements was the OnDemand3D program used for the multiplanar reconstruction for DICOM format and Geomagic® Control X™ used for STL format. Statistics. An intraclass correlation (ICC) analysis was used to check the agreement between the volume measurement of the segmented teeth generated by using the CephX® and Insignia™ system. Also, it was used to check the agreement between the STL (IOS), STL (CephX®), and DICOM tooth models. In addition, it was used to determine the intraexaminer repeatability by remeasuring five randomly selected individuals two weeks after the initial measurement. After confirmation of the data normality using the Shapiro–Wilk test, the right and left tooth models and the differences between the DICOM, CephX® (STL), and IOS (STL) tooth models were compared using a paired t-test. The STL (IOS), STL (CephX®), and DICOM tooth models were compared utilizing the ANOVA test. p<0.05 was set as the statistical significance level. Result. Overall data showed good agreement with ICC. The measurements of the various tooth types on the right and left sides did not differ significantly. Also, there was no significant difference between the three groups. Conclusions. The automatic AI approach (CephX®) may be advised in the clinical practice for patients with mild crowding and no teeth restorations due to its speed and effectiveness. |
| format | Article |
| id | doaj-art-7596bc6d71c346a58c16d4c9fea8c84a |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-7596bc6d71c346a58c16d4c9fea8c84a2025-02-03T06:48:32ZengWileyThe Scientific World Journal1537-744X2023-01-01202310.1155/2023/5933003The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial IntelligenceAmmar Sh. Al-Ubaydi0Dheaa Al-Groosh1College of DentistryOrthodontic DepartmentThis study aimed at evaluating the precision of the segmented tooth model (STM) that was produced by the artificial intelligence (AI) program (CephX®) with an intraoral scan (IOS) and insignia outcomes. Methods. 10 patients with Cl I malocclusion (mild-to-moderate crowding) who underwent nonextraction orthodontic therapy with the Insignia™ system had IOS and CBCT scans taken before treatment. AI was used to produce a total of 280 STMs; each tooth will be measured from three aspects (apexo-occlusal, mesiodistal, and labiolingual) for DICOM and STL formats. Also, root volume measurements for each tooth generated by using the CephX® software and Insignia™ system were compared. The software used for these measurements was the OnDemand3D program used for the multiplanar reconstruction for DICOM format and Geomagic® Control X™ used for STL format. Statistics. An intraclass correlation (ICC) analysis was used to check the agreement between the volume measurement of the segmented teeth generated by using the CephX® and Insignia™ system. Also, it was used to check the agreement between the STL (IOS), STL (CephX®), and DICOM tooth models. In addition, it was used to determine the intraexaminer repeatability by remeasuring five randomly selected individuals two weeks after the initial measurement. After confirmation of the data normality using the Shapiro–Wilk test, the right and left tooth models and the differences between the DICOM, CephX® (STL), and IOS (STL) tooth models were compared using a paired t-test. The STL (IOS), STL (CephX®), and DICOM tooth models were compared utilizing the ANOVA test. p<0.05 was set as the statistical significance level. Result. Overall data showed good agreement with ICC. The measurements of the various tooth types on the right and left sides did not differ significantly. Also, there was no significant difference between the three groups. Conclusions. The automatic AI approach (CephX®) may be advised in the clinical practice for patients with mild crowding and no teeth restorations due to its speed and effectiveness.http://dx.doi.org/10.1155/2023/5933003 |
| spellingShingle | Ammar Sh. Al-Ubaydi Dheaa Al-Groosh The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence The Scientific World Journal |
| title | The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence |
| title_full | The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence |
| title_fullStr | The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence |
| title_full_unstemmed | The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence |
| title_short | The Validity and Reliability of Automatic Tooth Segmentation Generated Using Artificial Intelligence |
| title_sort | validity and reliability of automatic tooth segmentation generated using artificial intelligence |
| url | http://dx.doi.org/10.1155/2023/5933003 |
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