An Iterative Mixed Pixel Classification for Brain Tissues and White Matter Hyperintensity in Magnetic Resonance Imaging-Reference-Cited by-同舟云学术

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An Iterative Mixed Pixel Classification for Brain Tissues and White Matter Hyperintensity in Magnetic Resonance Imaging

Published:2019 Issue: Volume:7 Page:124674-124687
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Chen Chi-Chang Clayton,Chai Jyh-Wen,Chen Hung-Chieh,Wang Hsin Che,Chang Yung-Chieh,Wu Yi-Ying,Chen Wen-Hsien,Chen Hsian-Min^ORCID,Lee San-Kan,Chang Chein-I

Funder

Taichung Veterans General Hospital

Ministry of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8600701/08779620.pdf?arnumber=8779620

Cited by 13 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. Enhanced Detection of White Matter Hyperintensities via Deep Learning-Enabled MR Imaging Segmentation;Traitement du Signal;2024-02-29

2. Detection of White Matter Hyperintensities in Magnetic Resonance Imaging by Hyperspectral Subpixel Detection;IEEE Access;2024

3. Constrained Energy Minimization (CEM) for Hyperspectral Target Detection: Theory and Generalizations;IEEE Transactions on Geoscience and Remote Sensing;2024

4. Real-time GB pattern convolution neural network-based brain image classification;AIP Conference Proceedings;2024

5. An AI-based segmentation and analysis pipeline for high-field MR monitoring of cerebral organoids;Scientific Reports;2023-12-01

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