[1] [1] Liu H, Cao H C, Song E M, et al. Bone marrow cells detection: a technique for the microscopic image analysis［J］. Journal of Medical Systems, 2019, 43(4): 82.

[2] [2] Cao H C, Liu H, Song E M. A novel algorithm for segmentation of leukocytes in peripheral blood［J］. Biomedical Signal Processing and Control, 2018, 45(8): 10-21.

[3] [3] Mohammadi E, Orooji M. An unsupervised and supervised combined approach for white blood cells segmentation［C］//Proceedings of the 25th National and the 3rd International Iranian Conference on Biomedical Engineering. Los Alamitos: IEEE Computer Society Press, 2018: 209-214.

[4] [4] Partha Pratim Banik, Rappy Saha, Ki-Doo Kim. An automatic nucleus segmentation and CNN model based classification method of white blood cell［J］. Expert Systems With Applications, 2020, 149(4): 113211.

[5] [5] Andrea Acevedo, Santiago Alférez, Anna Merino, et al.Recognition of peripheral blood cell images using convolutional neural networks［J］. Computer Methods and Programs in Biomedicine, 2019, 180(10): 105020.

[6] [6] Zhang X Q, Zhao S G. Blood cell image classification based on image segmentation preprocessing and CapsNet network model［J］. Journal of Medical Imaging and Health Informatics, 2019, 9(1): 159-166.

[7] [7] Jingru Yi, Pengxiang Wu, Menglin Jiang, et al. Attentive neural cell instance segmentation［J］. Medical Image Analysis, 2019, 55(7): 228-240.

[8] [8] WU Shuang. Research of white blood cells recognition based on SVM［J］. Electronic Desigh Engineering, 2010, 18(12): 124-126.

[9] [9] Zar Nawab Khan Swati, Qinghua Zhao, Muhammad Kabir, et al. ?Brain tumor classification for MR images using transfer learning and fine-tuning［J］. Computerized Medical Imaging and Graphics, 2019, 75(7): 34-36.

[10] [10] Khan S U, Islam N, Jan Z, et al. A novel deep learning based framework for the detection and classification of breast cancer using transfer learning［J］. Pattern Recognition Letters, 2019, 125(7): 1-6.

[11] [11] Hegde Roopa B, Prasad Keerthana, Hebbar Harishchandra, et al.Feature extraction using traditional image processing and convolutional neural network methods to classify white blood cells: A study［J］. Australasian Physical & Engineering Sciences in Medicine, 2019, 42(2): 627-638.

[13] [13] Liqun Lin, Weixing Wang. A robust leukocyte recognition method based on multi-scale regional growth and mean-shift clustering［J］. Journal of Algorithms & Computational Technology, 2018, 12(3): 174830181877083.

[14] [14] Mohamed H, Omar R, Saeed N, et al. Automated detection of blood leukocytes cancer diseases［C］//2018 First International Workshop on Deep and Representation Learning (IWDRL). IEEE, 2018: 48-54.

[15] [15] Kang Chao, Wu Chengmao, Fan Jiulun.? Lorenz curve-based entropy thresholding on circular histogram［J］. ?IEEE Access, 2020, 8(1): 17025-17038.

[16] [16] Gomez-GilP, Ramirez-Cortes M, Gonzalez-Bernal J, et al. A Feature Extraction Method Based on Morphological Operators for Automatic Classification of Leukocytes［C］// Seventh Mexican International Conference on Artificial Intelligence. IEEE Computer Society, 2008.

[17] [17] Yapin Wang, Yiping Cao. A Leukocyte image fast scanning based on max-min distance clustering［J］. Journal of Innovative Optical Health Sciences, 2016, 9(6): 1650022.

[18] [18] Yu W, Xu J J, Liu Y Y, et al. No-reference quality evaluation for gamut mapping images based on natural scene statistics［J］. Laser & Optoelectronics Progress, 2020, 57(14): 141006.

[19] [19] Dongyao Jia, Zhengyi Li, Chuanwang Zhang. Detection of cervical cancer cells based on strong feature CNN-SVM network［J］. Neurocomputing, 2020, 411(10): 112-127.