Optics and Precision Engineering, Volume. 31, Issue 7, 1074(2023)

Pneumonia aided diagnosis model based on dense dual-stream focused network

Tao ZHOU1,3, Xinyu YE1,3、*, Huiling LU2, Yuncan LIU1,3, and Xiaoyu CHANG1,3
Author Affiliations
  • 1College of Computer Science and Engineering, North Minzu University, Yinchuan75002, China
  • 2College of Science, Ningxia Medical University, Yinchuan750003, China
  • 3Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission, North Minzu University, Yinchuan750021, China
  • show less
    References(24)

    [1] EZHILAN M, SURESH I, NESAKUMAR N. SARS-CoV, MERS-CoV and SARS-CoV-2: a diagnostic challenge[J]. Measurement: Journal of the International Measurement Confederation, 168, 108335(2021).

    [2] Centers for Disease Control and Prevention[EB/OL]. https://www.cdc.gov/pneumonia/prevention.html(2020).

    [3] TOĞAÇAR M, ERGEN B, CÖMERT Z. COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches[J]. Computers in Biology and Medicine, 121, 103805(2020).

    [4] [4] 4周涛, 霍兵强, 陆惠玲, 等. 融合多尺度图像的密集神经网络肺部肿瘤识别算法[J]. 光学 精密工程, 2021, 29(7): 1695-1708. doi: 10.37188/OPE.20212907.1695ZHOUT, HUOB Q, LUH L, et al. Lung tumor image recognition algorithm with densenet fusion multi-scale images[J]. Opt. Precision Eng., 2021, 29(7): 1695-1708.(in Chinese). doi: 10.37188/OPE.20212907.1695

    [5] JAIN R. Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning[J]. Measurement, 165, 108046(2020).

    [7] ÇALLl E, SOGANCIOGLU E, VAN GINNEKEN B et al. Deep learning for chest X-ray analysis: a survey[J]. Medical Image Analysis, 72, 102125(2021).

    [8] CHEN B Z. DualCheXNet: dual asymmetric feature learning for thoracic disease classification in chest X-rays[J]. Biomedical Signal Processing and Control, 53, 101554(2019).

    [9] LI H, ZHUANG S S, LI D A et al. Benign and malignant classification of mammogram images based on deep learning[J]. Biomedical Signal Processing and Control, 51, 347-354(2019).

    [10] CHEN B L, ZHAO T S, LIU J H et al. Multipath feature recalibration DenseNet for image classification[J]. International Journal of Machine Learning and Cybernetics, 12, 651-660(2021).

    [11] [11] 11陈筱, 朱向冰, 吴昌凡, 等. 基于迁移学习与特征融合的眼底图像分类[J]. 光学 精密工程, 2021, 29(2): 388-399. doi: 10.37188/OPE.20212902.0388CHENX, ZHUX B, WUCH F, et al. Research on fundus image classification based on transfer learning and feature fusion[J]. Opt. Precision Eng., 2021, 29(2): 388-399.(in Chinese). doi: 10.37188/OPE.20212902.0388

    [12] LIU Y J, HAO P Y, ZHANG P et al. Dense convolutional binary-tree networks for lung nodule classification[J]. IEEE Access, 6, 49080-49088(2018).

    [13] PRIYA K V. A federated approach for detecting the chest diseases using DenseNet for multi-label classification[J]. Complex & Intelligent Systems, 8, 3121-3129(2022).

    [15] [15] 15景海钊, 史江林, 邱梦哲, 等. 基于密集残差块生成对抗网络的空间目标图像超分辨率重建[J]. 光学 精密工程, 2022, 30(17): 2155-2165. doi: 10.37188/OPE.20223017.2155JINGH ZH, SHIJ L, QIUM ZH, et al. Super-resolution reconstruction method for space target images based on dense residual block-based GAN[J]. Opt. Precision Eng., 2022, 30(17): 2155-2165.(in Chinese). doi: 10.37188/OPE.20223017.2155

    [16] KERMANY D S, ZHANG K, GOLDBAUM M. Labeled optical coherence tomography (OCT) and chest X-ray images for classification[J]. Mendeley data(2018).

    [17] GIEŁCZYK A, MARCINIAK A, TARCZEWSKA M et al. Pre-processing methods in chest X-ray image classification[J]. PLoS One, 17(2022).

    [18] RADOSAVOVIC I, KOSARAJU R P, GIRSHICK R et al. Designing network design spaces[C], 10425-10433(2020).

    [20] ELARABY M E. A novel Gray-Scale spatial exploitation learning Net for COVID-19 by crawling Internet resources[J]. Biomedical Signal Processing and Control, 73, 103441(2022).

    [21] CHETOUI M, AKHLOUFI M A. Explainable vision transformers and radiomics for COVID-19 detection in chest X-rays[J]. Journal of Clinical Medicine, 11, 3013(2022).

    [22] BALASUBRAMANIAN K, ANANTHAMOORTHY N P, RAMYA K. An end-end deep learning framework for lung infection recognition using attention-based features and cross average pooling[J]. International Journal for Multiscale Computational Engineering, 20, 67-82(2022).

    [23] KHAN I A. CoroNet: a deep neural network for detection and diagnosis of COVID-19 from chest X-ray images[J]. Computer Methods and Programs in Biomedicine, 196, 105581(2020).

    [24] OUCHICHA C, AMMOR O, MEKNASSI M. CVDNet: a novel deep learning architecture for detection of coronavirus (Covid-19) from chest X-ray images[J]. Chaos, Solitons, and Fractals, 140, 110245(2020).

    Tools

    Get Citation

    Copy Citation Text

    Tao ZHOU, Xinyu YE, Huiling LU, Yuncan LIU, Xiaoyu CHANG. Pneumonia aided diagnosis model based on dense dual-stream focused network[J]. Optics and Precision Engineering, 2023, 31(7): 1074

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Information Sciences

    Received: Sep. 28, 2020

    Accepted: --

    Published Online: Apr. 28, 2023

    The Author Email: Xinyu YE (3303626778@qq.com)

    DOI:10.37188/OPE.20233107.1074

    Topics