Cargando…
Optimized Deconvolutional Algorithm-based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction
To apply deconvolution algorithm in computer tomography (CT) perfusion imaging of acute cerebral infarction (ACI), a convolutional neural network (CNN) algorithm was optimized first. RIU-Net was applied to segment CT image, and then equipped with SE module to enhance the feature extraction ability....
Autores principales: | Chen, Xiaoxia, Bai, Xiao, Shu, Xin, He, Xucheng, Zhao, Jinjing, Guo, Xiaodong, Wang, Guisheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192278/ https://www.ncbi.nlm.nih.gov/pubmed/35800236 http://dx.doi.org/10.1155/2022/8728468 |
Ejemplares similares
-
Adoption of computerized tomography perfusion imaging in the diagnosis of acute cerebral infarct under optimized deconvolution algorithm
por: Fang, Bo, et al.
Publicado: (2021) -
Appearance of cerebral infarct fogging on CT perfusion
por: Braileanu, Maria, et al.
Publicado: (2019) -
Comparison of different deconvolution algorithms for voxel-wise quantitative MR perfusion assessment
por: Nooralipour, Niloufar Zarinabad, et al.
Publicado: (2011) -
An Optimal Subspace Deconvolution Algorithm for Robust and High-Resolution Beamforming
por: Su, Xiruo, et al.
Publicado: (2022) -
Accuracy of CT cerebral perfusion in predicting infarct in the emergency department: lesion characterization on CT perfusion based on commercially available software
por: Ho, Chang Y., et al.
Publicado: (2013)