Citation: | ZHANG Xueyuan, XU Hongyan, DONG Yueming, LIU Danfeng, SUN Pengrui, YAN Rui, CUI Hongliang, LEI Hong, REN Fei. Fungal Microscopic Image Classification Based on Multi-scale Attention Mechanism[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(1): 139-147. DOI: 10.12290/xhyxzz.2022-0169 |
[1] |
Chen M, Xu Y, Hong N, et al. Epidemiology of fungal infections in China[J]. Front Med, 2018, 12: 58-75. DOI: 10.1007/s11684-017-0601-0
|
[2] |
Sanguinetti M, Posteraro B, Beigelman-Aubry C, et al. Diagnosis and treatment of invasive fungal infections: looking ahead[J]. J Antimicrob Chemother, 2019, 74: 27-37.
|
[3] |
何文军, 李曼, 李涛, 等. 基于血细胞形态识别的自动检测系统的研发[J]. 现代检验医学杂志, 2019, 34: 110-114. https://www.cnki.com.cn/Article/CJFDTOTAL-SXYN201902027.htm
He WJ, Li M, Li T, et al. Study on Automatic Detection System Base on Blood Cell Morphology Recognition[J]. Xiandai Jianyan Yixue Zazhi, 2019, 34: 110-114. https://www.cnki.com.cn/Article/CJFDTOTAL-SXYN201902027.htm
|
[4] |
赵颖, 李志荣, 赵建宏, 等. 河北地区临床实验室丝状真菌分离鉴定情况分析[J]. 中国真菌学杂志, 2020, 15: 206-212. DOI: 10.3969/j.issn.1673-3827.2020.04.004
Zhao Y, Li ZR, Zhao JH, et al. Analysis of filamentous fungi isolations from clinical laboratories in Hebei province[J]. Zhongguo Zhenjunxue Zazhi, 2020, 15: 206-212. DOI: 10.3969/j.issn.1673-3827.2020.04.004
|
[5] |
Tamiev D, Furman PE, Reuel NF. Automated classification of bacterial cell sub-populations with convolutional neural networks[J]. PLoS One, 2020, 15: e0241200. DOI: 10.1371/journal.pone.0241200
|
[6] |
Kulwa F, Li C, Zhang J, et al. A new pairwise deep learning feature for environmental microorganism image analysis[J]. Environ Sci Pollut Res Int, 2022. doi: 10.1007/s11356-022-18849-0.
|
[7] |
Zhang J, Li C, Kosov S, et al. LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation[J]. Pattern Recogn, 2021, 115: 107885. DOI: 10.1016/j.patcog.2021.107885
|
[8] |
Liang CM, Lai CC, Wang SH, et al. Environmental microorganism classification using optimized deep learning model[J]. Environ Sci Pollut Res Int, 2021, 28: 31920-31932. DOI: 10.1007/s11356-021-13010-9
|
[9] |
李卓识, 陈晓旭, 温长吉, 等. 基于机器学习的鹅膏属真菌形态特征分类模型研究[J]. 中国农机化学报, 2020, 41: 136-143. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJH202001026.htm
Li ZS, Chen XX, Wen CJ, et al. Study on classification model of morphological characteristics of amanita fungi based on machine learning[J]. Zhongguo Nongjihua Xuebao, 2020, 41: 136-143. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJH202001026.htm
|
[10] |
Tahir MW, Zaidi NA, Rao AA, et al. A fungus spores dataset and a convolutional neural network based approach for fungus detection[J]. IEEE Transact Nano Biosci, 2018, 17: 281-290.
|
[11] |
Zhang J, Lu S, Wang X, et al. Automatic identification of fungi in microscopic leucorrhea images[J]. J Opt Soc Am A Opt Image Sci Vis, 2017, 34: 1484-1489. DOI: 10.1364/JOSAA.34.001484
|
[12] |
周院. 基于深度学习的真菌图像分类算法研究[D]. 西安: 西安理工大学, 2019.
|
[13] |
郝如茜. 白带显微图像中霉菌自动识别及清洁度判定的研究[D]. 成都: 电子科技大学, 2017.
|
[14] |
Otsu N. A threshold selection method from gray-level histograms[J]. IEEE Transact Syst Man Cyb, 2007, 9: 62-66.
|
[15] |
Hao R, Wang X, Zhang J, et al. Automatic detection of fungi in microscopic leucorrhea images based on convolu-tional neural network and morphological method[C]. 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), 2019: 2491-2494.
|
[16] |
Sandler M, Howard A, Zhu M, et al. Mobilenetv2: Inverted residuals and linear bottlenecks[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018: 4510-4520.
|
[17] |
Deng J, Dong W, Socher R, et al. Imagenet: A large-scale hierarchical image database[C]. 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009: 248-255.
|
[18] |
Hu J, Shen L, Sun G. Squeeze-and-excitation networks[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018: 7132-7141.
|
[19] |
Yu F, Koltun V. Multi-Scale Context Aggregation by Dilated Convolutions[C]. International Conference on Learning Representations, 2016. https://doi.org/10.48550/arXiv.1511.07122.
|
[20] |
He K, Zhang X, Ren S, et al. Deep residual learning for image recognition[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016: 770-778.
|
[21] |
Huang G, Liu Z, Laurens V, et al. Densely connected convolutional networks[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017: 4700-4708.
|
[22] |
Szegedy C, Vanhoucke V, Ioffe S, et al. Rethinking the inception architecture for computer vision[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016: 2818-2826.
|
[23] |
Loshchilov I, Hutter F. SGDR: Stochastic Gradient Descent with Restarts[J]. ICLR 2017 Conference Paper, 2016. https://doi.org/10.48550/arXiv.1608.03983.
|
[24] |
Pan SJ, Qiang Y. A survey on transfer learning[J]. IEEE Transact Knowl Data En, 2010, 22: 1345-1359.
|
[25] |
Selvaraju RR, Cogswell M, Das A, et al. Grad-CAM: Visual explanations from deep networks via gradient-based localization[J]. Int J Comput Vision, 2020, 128: 336-359.
|
[26] |
Mital ME, Tobias RR, Villaruel H, et al. Transfer learning approach for the classification of conidial fungi (genus aspergillus) thru pre-trained deep learning models[C]. 2020 IEEE Region 10 Conference (Tencon), 2020: 1069-1074.
|
[27] |
Billones RK, Calilung EJ, Dadios EP, et al. Aspergillus species fungi identification using microscopic scale images[C]. 2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management(HNICEM), 2020. doi: 10.1109/HNICEM51456.2020.9400039.
|
[28] |
Zawadzki P. Deep learning approach to the classification of selected fungi and bacteria[C]. 2020 IEEE 21st International Conference on Computational Problems of Electrical Engineering (CPEE), 2020: 1-4.
|
[29] |
Zieliński B, Sroka-Oleksiak A, Rymarczyk D, et al. Deep learning approach to describe and classify fungi microscopic images[J]. PLoS One, 2020, 15: e0234806.
|
[1] | JIN Di, NIE Weihua, REN Liying, SHEN Le. Research Progress on the Influence of Perioperative Sleep Quality on Postoperative Pain[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(4): 897-903. DOI: 10.12290/xhyxzz.2023-0615 |
[2] | WEN Bei, ZHU He, XU Li, HUANG Yuguang. Association Between Coffee Consumption and Pain: A Cross-sectional Study Based on American National Health and Nutrition Examination Survey[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(2): 351-358. DOI: 10.12290/xhyxzz.2023-0553 |
[3] | ZHU He, WEN Bei, XU Li, HUANG Yuguang. Mechanism of Wnt5a on Keratinocyte Regulating MMP9 for CRPS-Ⅰ Peripheral Sensitization[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(2): 335-343. DOI: 10.12290/xhyxzz.2023-0551 |
[4] | CHEN Fei, ZHANG Yuguan, ZHU Bo. Prospects of Digital Medicine in Postoperative Pain Management in Children[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(2): 279-284. DOI: 10.12290/xhyxzz.2023-0429 |
[5] | LAI Honghao, WANG Zhe, LI Ying, TANG Wenjing, WANG Beibei, SUN Peidong, SUN Mingyao, HUANG Jiajie, XIAO Zhipan, LI Ying, ZHAO Chen, SHANG Hongcai, YANG Kehu, LIU Jie, GE Long. Multi-evidence Integration Methodology for Traditional Chinese Medicine: the MERGE Framework[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(1): 172-182. DOI: 10.12290/xhyxzz.2023-0083 |
[6] | Zhan Xiaoya, Zhao Xue, Cai Peng, Ma Lei, He Huan. Summary of the evidence for ambulatory blood pressure monitoring in adults[J]. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2024-0797 |
[7] | SU Renfeng, YU Xuan, SHI Qianling, LUO Xufei, SUN Yajia, LAN Hui, REN Mengjuan, WU Shouyuan, WANG Ping, WANG Ling, ZHAO Junxian, CHEN Yaolong. Current Situation and Progress of Evidence Synthesis Methodology[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(6): 1301-1309. DOI: 10.12290/xhyxzz.2023-0062 |
[8] | LIU Yuan, ZHAO Lin. Update and Interpretation of 2022 National Comprehensive Cancer Network Clinical Practice Guidelines for Gastric Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(6): 999-1004. DOI: 10.12290/xhyxzz.2022-0271 |
[9] | Xiao-qing LIU, Xiao-chuan SUN. Real-world Evidence[J]. Medical Journal of Peking Union Medical College Hospital, 2017, 8(4-5): 305-310. DOI: 10.3969/j.issn.1674-9081.2017.05.021 |