Research graph
References from Using deep learning to segment impacted molar teeth from panoramic radiographs. Local targets link to admitted publications; unresolved targets remain external evidence.
Factors affecting interpretation of dental radiographs
10.1259/dmfr.20220279 · 2023 · External reference
Automatic segmentation of inferior alveolar canal with ambiguity classification in panoramic images using deep learning
2023 · External reference
Deep learning systems for detecting and classifying the presence of impacted supernumerary teeth in the maxillary incisor region on panoramic radiographs
10.1016/j.oooo.2020.04.813 · 2020 · External reference
Deep learning based detection tool for impacted mandibular third molar teeth
10.3390/diagnostics12040942 · 2022 · External reference
Teeth segmentation in panoramic dental X-ray using mask regional convolutional neural network
10.3390/app13137947 · 2023 · External reference
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist
10.1038/s41591-020-1041-y · 2020 · External reference
Convolutional neural networks: an overview and application in radiology
10.1007/s13244-018-0639-9 · 2018 · External reference
Human gender prediction based on deep transfer learning from panoramic radiograph images
2022 · External reference
Estimating age and sex from dental panoramic radiographs using neural networks and vision–language models
10.3390/oral5010003 · 2025 · External reference
How much can clip benefit vision-and-language tasks?
2021 · External reference
U-net: convolutional networks for biomedical image segmentation
2015 · External reference
One-stage methods of computer vision Object detection to classify carious lesions from smartphone imaging
10.3390/oral3020016 · 2023 · External reference
Unresolved reference
2020 · External reference
The efficacy of supervised learning and semi-supervised learning in diagnosis of impacted third molar on panoramic radiographs through artificial intelligence model
10.1259/dmfr.20230030 · 2023 · External reference
Automation and deep (machine) learning in temporomandibular joint disorder radiomics: A systematic review
10.1111/joor.13440 · 2023 · External reference
Overfitting and undercomputing in machine learning
10.1145/212094.212114 · 1995 · External reference
Understanding occlusion and temporomandibular joint function using deep learning and predictive modeling
10.1002/cre2.70028 · 2024 · External reference
ResNet-50 vs VGG-19 vs training from scratch: a comparative analysis of the segmentation and classification of Pneumonia from chest X-ray images
10.1016/j.gltp.2021.08.027 · 2021 · External reference
PSP net-based automatic segmentation network model for prostate magnetic resonance imaging
10.1016/j.cmpb.2021.106211 · 2021 · External reference
Medical image recognition and segmentation of pathological slices of gastric cancer based on Deeplab v3+ neural network
10.1016/j.cmpb.2021.106210 · 2021 · External reference
Unified focal loss: generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation
10.1016/j.compmedimag.2021.102026 · 2022 · External reference
