Graph-based Regional Feature Enhancing for Abdominal Multi-Organ Segmentation in CT-Reference-Cited by-同舟云学术

Graph-based Regional Feature Enhancing for Abdominal Multi-Organ Segmentation in CT

Published:2022-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)
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Author:

Yang Zefan¹,Wang Yi¹

Affiliation:

1. Health Science Center, School of Biomedical Engineering, Shenzhen University,National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging,Shenzhen,China

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Natural Science Foundation of Shenzhen University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9866947/9866899/09867126.pdf?arnumber=9867126

Reference24 articles.

1. Automated design of deep learning methods for biomedical image segmentation;isensee;ArXiv Preprint,2019

2. Automatic Multi-Organ Segmentation on Abdominal CT With Dense V-Networks

3. Residual Dense Network for Image Super-Resolution

4. Block Level Skip Connections Across Cascaded V-Net for Multi-Organ Segmentation

5. AutoPath: Image-Specific Inference for 3D Segmentation

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