M-CSAFN: Multi-Color Space Adaptive Fusion Network for Automated Port-Wine Stains Segmentation-Reference-Cited by-同舟云学术

M-CSAFN: Multi-Color Space Adaptive Fusion Network for Automated Port-Wine Stains Segmentation

Published:2023-08 Issue:8 Volume:27 Page:3924-3935
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Mu Jinrong¹^ORCID,Lin Yucong²^ORCID,Meng Xianqi¹^ORCID,Fan Jingfan¹^ORCID,Ai Danni¹^ORCID,Chen Defu³^ORCID,Qiu Haixia⁴,Yang Jian¹^ORCID,Gu Ying⁴

Affiliation:

1. Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, China

2. Institute of Engineering Medicine, Beijing Institute of Technology, Beijing, China

3. School of Medical Technology, Beijing Institute of Technology, Beijing, China

4. Department of Laser Medicine, the First Medical Centre, Chinese PLA General Hospital, Beijing, China

Funder

National Science Foundation Program of China

CAMS Innovation Fund for Medical Sciences

Big Data Research Support Fund of Chinese PLA General Hospital

Science and Technology Innovation Talent Program of Beijing Institute of Technology

National Key R&D Program of Zhejiang Province

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10210140/10049643.pdf?arnumber=10049643

Reference51 articles.

1. Calibration of a three-dimensional photodynamic therapy illumination system and its segmentation assessment for port-wine stains

2. A Medical Manipulator System with Lasers in Photodynamic Therapy of Port Wine Stains

3. AI in Medical Imaging Informatics: Current Challenges and Future Directions

4. Eight ways machine learning is assisting medicine

5. Automated Skin Lesion Segmentation Via an Adaptive Dual Attention Module

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