Graph-Based Motion Artifacts Detection Method from Head Computed Tomography Images

Computed tomography (CT) images play an important role due to effectiveness and accessibility, however, motion artifacts may obscure or simulate pathology and dramatically degrade the diagnosis accuracy. In recent years, convolutional neural networks (CNNs) have achieved state-of-the-art performance...

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Detalles Bibliográficos
Autores principales: Liu, Yiwen, Wen, Tao, Sun, Wei, Liu, Zhenyu, Song, Xiaoying, He, Xuan, Zhang, Shuo, Wu, Zhenning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371218/
https://www.ncbi.nlm.nih.gov/pubmed/35957222
http://dx.doi.org/10.3390/s22155666

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371218/
https://www.ncbi.nlm.nih.gov/pubmed/35957222
http://dx.doi.org/10.3390/s22155666

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