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Longitudinal Assessment of COVID-19 Using a Deep Learning-based Quantitative CT Pipeline: Illustration of Two Cases.

作者信息

Cao Yukun, Xu Zhanwei, Feng Jianjiang, Jin Cheng, Han Xiaoyu, Wu Hanping, Shi Heshui

机构信息

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China (Y.C., X.H., H.S.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (Y.C., X.H., H.S.); Department of Automation, Tsinghua University, Beijing, China (Z.X., J.F., C.J.); and Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, Mich (H.W.).

出版信息

Radiol Cardiothorac Imaging. 2020 Mar 23;2(2):e200082. doi: 10.1148/ryct.2020200082. eCollection 2020 Apr.

DOI:10.1148/ryct.2020200082
PMID:33778563
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7233432/
Abstract
摘要

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本文引用的文献

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Imaging Profile of the COVID-19 Infection: Radiologic Findings and Literature Review.新型冠状病毒肺炎感染的影像学表现：放射学发现与文献综述
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2
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.中国武汉地区 2019 年新型冠状病毒感染患者的临床特征。
Lancet. 2020 Feb 15;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5. Epub 2020 Jan 24.
3
A Novel Coronavirus from Patients with Pneumonia in China, 2019.
Fully feature fusion based neural network for COVID-19 lesion segmentation in CT images.
基于全特征融合的神经网络用于CT图像中新冠肺炎病变分割
Biomed Signal Process Control. 2023 Sep;86:104939. doi: 10.1016/j.bspc.2023.104939. Epub 2023 Apr 10.
4
Preliminary Stages for COVID-19 Detection Using Image Processing.利用图像处理技术进行新冠病毒检测的前期阶段
Diagnostics (Basel). 2022 Dec 15;12(12):3171. doi: 10.3390/diagnostics12123171.
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Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.校准袋式深度学习在图像语义分割中的应用：以 COVID-19 胸片图像为例。
PLoS One. 2022 Nov 16;17(11):e0276250. doi: 10.1371/journal.pone.0276250. eCollection 2022.
6
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Contrast Media Mol Imaging. 2022 Oct 12;2022:1306664. doi: 10.1155/2022/1306664. eCollection 2022.
7
A teacher-student framework with Fourier Transform augmentation for COVID-19 infection segmentation in CT images.一种用于CT图像中新冠病毒感染分割的带有傅里叶变换增强的师生框架。
Biomed Signal Process Control. 2023 Jan;79:104250. doi: 10.1016/j.bspc.2022.104250. Epub 2022 Sep 26.
8
Machine learning techniques for CT imaging diagnosis of novel coronavirus pneumonia: a review.用于新型冠状病毒肺炎CT成像诊断的机器学习技术：综述
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