Optics and Precision Engineering, Volume. 31, Issue 6, 936(2023)

Bone scintigraphic classification method based on ACGAN and transfer learning

Hong YU1、*, Renze LUO1, Chunmeng CHEN2, Xiang TANG3, and Renquan LUO1
Author Affiliations
  • 1College of Electrical Engineering and Information,Southwest Petroleum University, Chengdu60500, China
  • 2Department of Nuclear Medicine, The No. People’s Hospital of Yibin, Yibin644000, China
  • 3College of Computer Science, Southwest Petroleum University, Chengdu610500, China
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    References(23)

    [1] FENG J X, JIANG J. Deep learning-based chest CT image features in diagnosis of lung cancer[J]. Computational and Mathematical Methods in Medicine, 2022, 4153211(2022).

    [2] [2] 2张永平, 兰朋训, 周兆霞. MRI和骨显像诊断骨转移瘤的临床价值分析[J]. 医学影像学杂志, 2017, 27(10): 2040-2042.ZHANGY P, LANP X, ZHOUZH X. Clinical value of MRI and bone scintigraphy in the diagnosis of bone metastases[J]. Journal of Medical Imaging, 2017, 27(10): 2040-2042.(in Chinese)

    [3] MADSEN M T. Recent advances in SPECT imaging[J]. Journal of Nuclear Medicine: Official Publication, 48, 661-673(2007).

    [4] SADIK M, HAMADEH I, NORDBLOM P et al. Computer-assisted interpretation of planar whole-body bone scans[J]. J Nucl Med, 49, 1958-1965(2008).

    [5] ASLANTAS A, DANDIL E, SAǦLAM S et al. CADBOSS: a computer-aided diagnosis system for whole-body bone scintigraphy scans[J]. Journal of Cancer Research and Therapeutics, 12, 787-792(2016).

    [6] ANTONINA M. Object-oriented classification approach for bone metastasis mapping from whole-body bone scintigraphy[J]. Physica Medica, 84, 141-148(2021).

    [7] ELFARRA F G, CALIN M A, PARASCA S V. Computer-aided detection of bone metastasis in bone scintigraphy images using parallelepiped classification method[J]. Annals of Nuclear Medicine, 33, 866-874(2019).

    [8] WANG Z Y, WEN X T, LU Y H et al. Exploiting machine learning for predicting skeletal-related events in cancer patients with bone metastases[J]. Oncotarget, 7, 12612-12622(2016).

    [9] LU L M, ZHANG C L, CAO K et al. A multichannel CNN-GRU model for human activity recognition[J]. IEEE Access, 10, 66797-66810(2022).

    [10] ZHENG Z W, LIU L X, CHEN X Y et al. Construction of Bisection Model of SPECT Bone Scan Image Based on VGGNet[C], 150-154(2021).

    [11] PAPANDRIANOS N, PAPAGEORGIOU E, ANAGNOSTIS A et al. Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application[J]. PLoS One, 15(2020).

    [12] NTAKOLIA C, DIAMANTIS D E, PAPANDRIANOS N et al. A lightweight convolutional neural network architecture applied for bone metastasis classification in nuclear medicine: a case study on prostate cancer patients[J]. Healthcare, 8, 493(2020).

    [13] LIN Q, CAO C G, LI T T et al. dSPIC: a deep SPECT image classification network for automated multi-disease, multi-lesion diagnosis[J]. BMC Medical Imaging, 21, 122(2021).

    [14] ABDOLLAHI B, TOMITA N, HASSANPOUR S. Data augmentation in training deep learning models for medical image analysis[J]. Intelligent Systems Reference Library, 167-180(2020).

    [15] PADMAVATHI KORA. Transfer learning techniques for medical image analysis: a review[J]. Biocybernetics and Biomedical Engineering, 42, 79-107(2022).

    [16] TEHSEEN ZIA. VANT-GAN: adversarial learning for discrepancy-based visual attribution in medical imaging[J]. Pattern Recognition Letters, 156, 112-118(2022).

    [17] WU C M, ZENG Z. A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing[J]. PLoS One, 16(2021).

    [18] RONNEBERGER O, FISCHER P, BROX T. U-net: convolutional networks for biomedical image segmentation[J]. Lecture Notes in Computer Science, 234-241(2015).

    [19] HOU Q B, ZHOU D Q, FENG J S. Coordinate Attention for Efficient Mobile Network Design[C], 13708-13717(2021).

    [20] XU J, WANG J, XU X et al. Image recognition for different developmental stages of rice by RAdam deep convolutional neural networks[J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 37, 143-150(2021).

    [21] HOWARD A, SANDLER M, CHEN B et al. Searching for MobileNetV3[C], 1314-1324.

    [22] LIU K, YU S T, LIU S D. An improved InceptionV3 network for obscured ship classification in remote sensing images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 4738-4747(2020).

    [23] TAN M, LE Q V. EfficientNet: Rethinking Model Scaling for Convolution Neural Networks[C], 6105-6114(2019).

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    Hong YU, Renze LUO, Chunmeng CHEN, Xiang TANG, Renquan LUO. Bone scintigraphic classification method based on ACGAN and transfer learning[J]. Optics and Precision Engineering, 2023, 31(6): 936

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    Paper Information

    Category: Information Sciences

    Received: Jul. 19, 2022

    Accepted: --

    Published Online: Apr. 4, 2023

    The Author Email: Hong YU (790622472@qq.com)

    DOI:10.37188/OPE.20233106.0936

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