Development and evaluation of a deep learning segmentation model for assessing non-surgical endodontic treatment outcomes on periapical radiographs: A retrospective study.
This study aimed to evaluate the performance of a deep learning-based segmentation model for predicting outcomes of non-surgical endodontic treatment. Preoperative and 3-year postoperative periapical radiographic images of each tooth from routine root canal treatments performed by endodontists from...
Những tác giả chính: | Dennis Dennis, Siriwan Suebnukarn, Sothana Vicharueang, Wasit Limprasert |
---|---|
Định dạng: | Bài viết |
Ngôn ngữ: | English |
Được phát hành: |
Public Library of Science (PLoS)
2024-01-01
|
Loạt: | PLoS ONE |
Truy cập trực tuyến: | https://doi.org/10.1371/journal.pone.0310925 |
Những quyển sách tương tự
-
AI-based analysis of oral lesions using novel deep convolutional neural networks for early detection of oral cancer.
Bằng: Kritsasith Warin, et al.
Được phát hành: (2022-01-01) -
Maxillofacial fracture detection and classification in computed tomography images using convolutional neural network-based models
Bằng: Kritsasith Warin, et al.
Được phát hành: (2023-03-01) -
Histopathologic Evaluation of Periapical Radiolucencies Clinico-Radiographically Diagnosed as Endodontic Lesions: A Retrospective Analysis
Bằng: Saede Atarbashi-Moghadam, et al.
Được phát hành: (2024-03-01) -
RADIOGRAPHIC EVALUATION OF PERIAPICAL STATUS AND FREQUENCY OF ENDODONTIC TREATMENT IN A TURKISH POPULATION:A RETROSPECTIVE STUDY*
Bằng: Melek TAŞSÖKER, et al.
Được phát hành: (2016-04-01) -
Automatic Feature Segmentation in Dental Periapical Radiographs
Bằng: Tugba Ari, et al.
Được phát hành: (2022-12-01)