Localization of Craniomaxillofacial Landmarks on CBCT Images Using 3D Mask R-CNN and Local Dependency Learning-Reference-Cited by-同舟云学术

Localization of Craniomaxillofacial Landmarks on CBCT Images Using 3D Mask R-CNN and Local Dependency Learning

Published:2022-10 Issue:10 Volume:41 Page:2856-2866
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Lang Yankun¹^ORCID,Lian Chunfeng¹^ORCID,Xiao Deqiang¹^ORCID,Deng Hannah²^ORCID,Thung Kim-Han¹^ORCID,Yuan Peng²,Gateno Jaime²,Kuang Tianshu²,Alfi David M.²,Wang Li¹^ORCID,Shen Dinggang¹,Xia James J.²^ORCID,Yap Pew-Thian¹^ORCID

Affiliation:

1. Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

2. Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital, Houston, TX, USA

Funder

National Institutes of Health/National Institute of Dental and Craniofacial Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/9906463/09772618.pdf?arnumber=9772618

Reference45 articles.

1. Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting

2. Fully automated quantitative cephalometry using convolutional neural networks

3. Deep Residual Learning for Image Recognition

4. Integrating spatial configuration into heatmap regression based CNNs for landmark localization

5. Joint Segmentation and Landmark Localization of Fetal Femur in Ultrasound Volumes

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