Brain gray matter nuclei segmentation on quantitative susceptibility mapping using dual-branch convolutional neural network-Reference-Cited by-同舟云学术

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Brain gray matter nuclei segmentation on quantitative susceptibility mapping using dual-branch convolutional neural network

Published:2022-03 Issue: Volume:125 Page:102255
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Chai Chao,Qiao Pengchong,Zhao Bin,Wang Huiying,Liu Guohua,Wu Hong,Shen Wen,Cao Chen,Ye Xinchen,Liu Zhiyang,Xia Shuang

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference42 articles.

1. Association between increased magnetic susceptibility of deep gray matter nuclei and decreased motor function in healthy adults;Li;Neuroimage,2015

2. Increased iron deposition of deep cerebral gray matter structures in hemodialysis patients: A longitudinal study using quantitative susceptibility mapping;Chai;Journal of Magnetic Resonance Imaging,2019

3. Imaging beta amyloid aggregation and iron accumulation in alzheimer’s disease using quantitative susceptibility mapping mri;Gong;NeuroImage,2019

4. Different iron deposition patterns in early- and middle-late-onset Parkinson’s disease;Xuan;Parkinsonism and Related Disorders,2017

5. Altered brain iron content and deposition rate in Huntington’s disease as indicated by quantitative susceptibility MRI;Chen;Journal of Neuroscience Research,2019

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3. Design of Medical Spectral Image Segmentation Algorithm Based on Artificial Neural Network;2023 2nd International Conference on 3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME);2023-06

4. Deep learning with multiresolution handcrafted features for brain MRI segmentation;Artificial Intelligence in Medicine;2022-09

5. CAU-Net: A Deep Learning Method for Deep Gray Matter Nuclei Segmentation;Frontiers in Neuroscience;2022-06-02

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