NPCNet: Jointly Segment Primary Nasopharyngeal Carcinoma Tumors and Metastatic Lymph Nodes in MR Images-Reference-Cited by-同舟云学术

NPCNet: Jointly Segment Primary Nasopharyngeal Carcinoma Tumors and Metastatic Lymph Nodes in MR Images

Published:2022-07 Issue:7 Volume:41 Page:1639-1650
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Li Yang¹^ORCID,Dan Tingting¹^ORCID,Li Haojiang²,Chen Jiazhou¹^ORCID,Peng Hong¹,Liu Lizhi²,Cai Hongmin¹^ORCID

Affiliation:

1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

2. Department of Radiology, the State Key Laboratory of Oncology in South China, the Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, the Collaborative Innovation Center for Cancer Medicine, and the Sun Yat-sen University Cancer Center, Sun Yat-sen University, Guangzhou, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Fund for the Central Universities

Key-Area Research and Development of Guangdong Province

China Postdoctoral Science Foundation

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/ielx7/42/9811094/09684475.pdf?arnumber=9684475

Reference42 articles.

1. Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

2. FocalMix: Semi-Supervised Learning for 3D Medical Image Detection

3. BASNet: Boundary-Aware Salient Object Detection

4. RefineNet: Multi-path refinement networks for high-resolution semantic segmentation;lin;Proc IEEE Conf Comput Vis Pattern Recognit (CVPR),2017

5. Attention U-Net: Learning where to look for the pancreas;oktay;arXiv 1804 03999,2018

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Domain knowledge-driven encoder–decoder for nasopharyngeal carcinoma segmentation;Expert Systems with Applications;2024-12

2. Unfolding Explainable AI for Brain Tumor Segmentation;Neurocomputing;2024-09

3. A novel fully automatic segmentation and counting system for metastatic lymph nodes on multimodal magnetic resonance imaging: Evaluation and prognostic implications in nasopharyngeal carcinoma;Radiotherapy and Oncology;2024-08

4. Boundary-Aware Gradient Operator Network for Medical Image Segmentation;IEEE Journal of Biomedical and Health Informatics;2024-08

5. Semi-supervised segmentation for primary nasopharyngeal carcinoma tumors using local-region constraint and mixed feature-level consistency;Engineering Applications of Artificial Intelligence;2024-07