Localization of Craniomaxillofacial Landmarks on CBCT Images Using 3D Mask R-CNN and Local Dependency Learning is a research paper published in IEEE Transactions on Medical Imaging (2022). On theSindex it has a DataRank of 0.571. It has been cited 44 times.
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Base Score Contribution
0.571
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Institutes of Health/National Institute of Dental and Craniofacial Research
Grant: R01 DE022676
National Institutes of Health/National Institute of Dental and Craniofacial Research
Grant: R01 DE027251
National Institutes of Health/National Institute of Dental and Craniofacial Research
Grant: R01 DE021863
National Institutes of Health
Grant: 5R01DE027251-04
Learning-Based Approach for Personalized Craniomaxillofacial Surgical Planning
National Institutes of Health
Grant: 2R01DE021863-06
Outcome-Driven Approach to Minimize the Risks of Facial Distortion Following CMF Surgery
National Institutes of Health
Grant: 5R01DE022676-03
A Novel Imaging Informatics Platform for Craniomaxillofacial Surgery
Influential Citations
2
Fields of Study
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Keywords
Additional file 1 of Automatic craniomaxillofacial landmarks detection in CT images of individuals with dentomaxillofacial deformities by a two-stage deep learning model
Additional file 1 of Automatic craniomaxillofacial landmarks detection in CT images of individuals with dentomaxillofacial deformities by a two-stage deep learning model