Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs
The cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound im...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-06-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/13/5850 |
| _version_ | 1797528934265389056 |
|---|---|
| author | Kim-Cuong T. Nguyen Yuening Yan Neelambar R. Kaipatur Paul W. Major Edmond H. Lou Kumaradevan Punithakumar Lawrence H. Le |
| author_facet | Kim-Cuong T. Nguyen Yuening Yan Neelambar R. Kaipatur Paul W. Major Edmond H. Lou Kumaradevan Punithakumar Lawrence H. Le |
| author_sort | Kim-Cuong T. Nguyen |
| collection | DOAJ |
| description | The cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound images, based on the curvature change of the junction outlining the upper edge of the enamel and cementum at the cementum–enamel intersection. The technique consists of image preprocessing steps for image enhancement, segmentation, and edge detection to locate the boundary of the enamel and cementum. The effects of the image preprocessing and the sizes of the bounding boxes enclosing the CEJ were studied. For validation, the algorithm was applied to 120 images acquired from human volunteers. The mean difference of the best performance between the proposed method and the two raters’ measurements was an average of 0.25 mm with reliability ≥ 0.98. The proposed method has the potential to assist dental professionals in CEJ identification on ultrasonographs to provide better patient care. |
| first_indexed | 2024-03-10T10:06:25Z |
| format | Article |
| id | doaj.art-4024bf2278ea4b2ea42d578648519864 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T10:06:25Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4024bf2278ea4b2ea42d5786485198642023-11-22T01:28:33ZengMDPI AGApplied Sciences2076-34172021-06-011113585010.3390/app11135850Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral UltrasonographsKim-Cuong T. Nguyen0Yuening Yan1Neelambar R. Kaipatur2Paul W. Major3Edmond H. Lou4Kumaradevan Punithakumar5Lawrence H. Le6Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 2B7, CanadaInstitute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QQ, UKSchool of Dentistry, University of Alberta, Edmonton, AB T6G 1C9, CanadaSchool of Dentistry, University of Alberta, Edmonton, AB T6G 1C9, CanadaDepartment of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 2B7, CanadaDepartment of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 2B7, CanadaDepartment of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 2B7, CanadaThe cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound images, based on the curvature change of the junction outlining the upper edge of the enamel and cementum at the cementum–enamel intersection. The technique consists of image preprocessing steps for image enhancement, segmentation, and edge detection to locate the boundary of the enamel and cementum. The effects of the image preprocessing and the sizes of the bounding boxes enclosing the CEJ were studied. For validation, the algorithm was applied to 120 images acquired from human volunteers. The mean difference of the best performance between the proposed method and the two raters’ measurements was an average of 0.25 mm with reliability ≥ 0.98. The proposed method has the potential to assist dental professionals in CEJ identification on ultrasonographs to provide better patient care.https://www.mdpi.com/2076-3417/11/13/5850high-frequency ultrasoundlandmark detectiondento-periodontiumcemento-enamel junctionoral healthimage processing |
| spellingShingle | Kim-Cuong T. Nguyen Yuening Yan Neelambar R. Kaipatur Paul W. Major Edmond H. Lou Kumaradevan Punithakumar Lawrence H. Le Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs Applied Sciences high-frequency ultrasound landmark detection dento-periodontium cemento-enamel junction oral health image processing |
| title | Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs |
| title_full | Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs |
| title_fullStr | Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs |
| title_full_unstemmed | Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs |
| title_short | Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs |
| title_sort | computer assisted detection of cemento enamel junction in intraoral ultrasonographs |
| topic | high-frequency ultrasound landmark detection dento-periodontium cemento-enamel junction oral health image processing |
| url | https://www.mdpi.com/2076-3417/11/13/5850 |
| work_keys_str_mv | AT kimcuongtnguyen computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs AT yueningyan computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs AT neelambarrkaipatur computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs AT paulwmajor computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs AT edmondhlou computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs AT kumaradevanpunithakumar computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs AT lawrencehle computerassisteddetectionofcementoenameljunctioninintraoralultrasonographs |