지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.12
- 수록면
- 632 - 638 (7page)
- DOI
- 10.4283/JMAG.2020.25.4.632
이용수
초록· 키워드
오류제보하기
Recently, deep learning (DL) based semantic segmentation approach has been widely applied in medical image analysis. The semantic segmentation approach based DL technique was employed in the diagnosis of dental conditions with digital panoramic radiography (DRP). The purpose of this study is to investigate the accuracy of the semantic segmentation of Deeplab v3+ in the diagnosis of 5 different dental disease - apical, abrasion, caries, impaction, perio. DPR database (512×748-pixel, including 86 panoramic radiography) was used for semantic segmentation (DeepLab v3+). To validate the performance, the confusion matrix (maximum 97 %) was estimated. In addition, significant classification and semantic segmentation results were assessed. From the result of this study, the DL model could be a useful tool for the dentist to identify dental diseases as a clinical aid software.
목차
1. Introduction
2. Materials and Methods
3. Results and Discussion
4. Conclusion
References
참고문헌 (19)
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