Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography
In this study, an integrated deep learning framework was developed for classifying the periodontitis stages of each individual tooth using dental panoramic radiographs. Based on actual patient panoramic radiographs data, the bone loss by periodontitis and cementoenamel junction boundaries were detec...
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MDPI AG
2022-08-01
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| Online Access: | https://www.mdpi.com/2076-3417/12/17/8500 |
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| author | Ho Sun Shon Vungsovanreach Kong Jae Sung Park Wooyeong Jang Eun Jong Cha Sang-Yup Kim Eun-Young Lee Tae-Geon Kang Kyung Ah Kim |
| author_facet | Ho Sun Shon Vungsovanreach Kong Jae Sung Park Wooyeong Jang Eun Jong Cha Sang-Yup Kim Eun-Young Lee Tae-Geon Kang Kyung Ah Kim |
| author_sort | Ho Sun Shon |
| collection | DOAJ |
| description | In this study, an integrated deep learning framework was developed for classifying the periodontitis stages of each individual tooth using dental panoramic radiographs. Based on actual patient panoramic radiographs data, the bone loss by periodontitis and cementoenamel junction boundaries were detected, while the tooth number and tooth length were identified using data from AIHub, an open database platform. The two factors were integrated to classify and to evaluate the periodontitis staging on dental panoramic radiography. Periodontitis is classified into four stages based on the criteria of the radiographic bone level, as suggested at the relevant international conference in 2017. For the integrated deep learning framework developed in this study, the classification performance was evaluated by comparing the results of dental specialists, which indicated that the integrated framework had an accuracy of 0.929, with a recall and precision of 0.807 and 0.724, respectively, in average across all four stages. The novel framework was thus shown to exhibit a relatively high level of performance, and the findings in this study are expected to assist dental specialists with detecting the periodontitis stage and subsequent effective treatment. A systematic application will be developed in the future, to provide ancillary data for diagnosis and basic data for the treatment and prevention of periodontal disease. |
| first_indexed | 2024-03-10T03:05:02Z |
| format | Article |
| id | doaj.art-cb38c6cfe2cd4cf28b5b0cf27a8d9780 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T03:05:02Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-cb38c6cfe2cd4cf28b5b0cf27a8d97802023-11-23T12:40:38ZengMDPI AGApplied Sciences2076-34172022-08-011217850010.3390/app12178500Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic RadiographyHo Sun Shon0Vungsovanreach Kong1Jae Sung Park2Wooyeong Jang3Eun Jong Cha4Sang-Yup Kim5Eun-Young Lee6Tae-Geon Kang7Kyung Ah Kim8Medical Research Institute, School of Medicine, Chungbuk National University, Cheongju 28644, KoreaDepartment of Big Data, Chungbuk National University, Cheongju 28644, KoreaDepartment of Biomedical Engineering, School of Medicine, Chungbuk National University, Cheongju 28644, KoreaDepartment of Biomedical Engineering, School of Medicine, Chungbuk National University, Cheongju 28644, KoreaDepartment of Biomedical Engineering, School of Medicine, Chungbuk National University, Cheongju 28644, KoreaDepartment of Oral & Maxillofacial Surgery, Hankook General Hospital, Cheongju 28713, KoreaDepartment of Oral & Maxillofacial Surgery, Hankook General Hospital, Cheongju 28713, KoreaInstitute for Trauma Research, College of Medicine, Korea University, Seoul 02841, KoreaDepartment of Biomedical Engineering, School of Medicine, Chungbuk National University, Cheongju 28644, KoreaIn this study, an integrated deep learning framework was developed for classifying the periodontitis stages of each individual tooth using dental panoramic radiographs. Based on actual patient panoramic radiographs data, the bone loss by periodontitis and cementoenamel junction boundaries were detected, while the tooth number and tooth length were identified using data from AIHub, an open database platform. The two factors were integrated to classify and to evaluate the periodontitis staging on dental panoramic radiography. Periodontitis is classified into four stages based on the criteria of the radiographic bone level, as suggested at the relevant international conference in 2017. For the integrated deep learning framework developed in this study, the classification performance was evaluated by comparing the results of dental specialists, which indicated that the integrated framework had an accuracy of 0.929, with a recall and precision of 0.807 and 0.724, respectively, in average across all four stages. The novel framework was thus shown to exhibit a relatively high level of performance, and the findings in this study are expected to assist dental specialists with detecting the periodontitis stage and subsequent effective treatment. A systematic application will be developed in the future, to provide ancillary data for diagnosis and basic data for the treatment and prevention of periodontal disease.https://www.mdpi.com/2076-3417/12/17/8500periodontitisdeep learningradiographic bone loss |
| spellingShingle | Ho Sun Shon Vungsovanreach Kong Jae Sung Park Wooyeong Jang Eun Jong Cha Sang-Yup Kim Eun-Young Lee Tae-Geon Kang Kyung Ah Kim Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography Applied Sciences periodontitis deep learning radiographic bone loss |
| title | Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography |
| title_full | Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography |
| title_fullStr | Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography |
| title_full_unstemmed | Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography |
| title_short | Deep Learning Model for Classifying Periodontitis Stages on Dental Panoramic Radiography |
| title_sort | deep learning model for classifying periodontitis stages on dental panoramic radiography |
| topic | periodontitis deep learning radiographic bone loss |
| url | https://www.mdpi.com/2076-3417/12/17/8500 |
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