[1] Coudray N, Ocampo P S, Sakellaropoulos T et al. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning[J]. Nature Medicine, 24, 1559-1567(2018). http://www.nature.com/articles/s41591-018-0177-5/

[2] Guo L L, Li Y N. Histopathological image classification algorithm based on product of experts[J]. Laser & Optoelectronics Progress, 55, 021008(2018).

[3] Veta M, Pluim J P W, van Diest P J et al. Breast cancer histopathology image analysis: a review[J]. IEEE Transactions on Biomedical Engineering, 61, 1400-1411(2014).

[4] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).

[5] Fang L, Wang C, Li S et al. Attention to lesion: lesion-aware convolutional neural network for retinal optical coherence tomography image classification[J]. IEEE Transactions on Medical Imaging, 38, 1959-1970(2019). http://ieeexplore.ieee.org/document/8637959/references

[6] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017). http://users.ics.aalto.fi/perellm1/thesis/summaries_html/node64.html

[7] Zhou F Y, Jin L P, Dong J. Review of convolutional neural network[J]. Chinese Journal of Computers, 40, 1229-1251(2017).

[8] Liu J P, Yang Y Z, Chen M Y et al. Image dehazing algorithm based on convolutional neural network and dynamic ambient light[J]. Acta Optica Sinica, 39, 1110002(2019).

[9] Murtaza G, Shuib L, Abdul Wahab A W et al. Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges[J]. Artificial Intelligence Review, 53, 1655-1720(2020).

[10] Naik S, Doyle S, Agner S et al. Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology[C]. //2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, May 14-17, 2008, Paris, France, 284-287(2008).

[11] Spanhol F A, Oliveira L S, Petitjean C et al. A dataset for breast cancer histopathological image classification[J]. IEEE Transactions on Biomedical Engineering, 63, 1455-1462(2016). http://europepmc.org/abstract/med/26540668

[12] Spanhol F A, Oliveira L S, Petitjean C et al. Breast cancer histopathological image classification using convolutional neural networks[C]. //2016 International Joint Conference on Neural Networks (IJCNN), July 24-29, 2016, Vancouver, BC, Canada., 2560-2567(2016).

[13] Bayramoglu N, Kannala J, Heikkilä J. Deep learning for magnification independent breast cancer histopathology image classification[C]. //2016 23rd International Conference on Pattern Recognition (ICPR), December 4--8, 2016, Cancun, Mexico., 2440-2445(2016).

[14] Araújo T, Aresta G, Castro E et al. Classification of breast cancer histology images using convolutional neural networks[J]. PLoS One, 12, e0177544(2017). http://pubmedcentralcanada.ca/pmcc/articles/PMC5453426/?report=reader&lang=fr

[15] Wei B Z, Han Z Y, He X Y et al. Deep learning model based breast cancer histopathological image classification[C]. //2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), April 28-30, 2017, Chengdu, China., 348-353(2017).

[16] Ehteshami Bejnordi B, Veta M, Johannes van Diest P et al. Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer[J]. JAMA, 318, 2199-2210(2017).

[17] Meng T, Liu Y H, Zhang K Y. Algorithm for pathological image diagnosis based on boosting convolutional neural network[J]. Laser & Optoelectronics Progress, 56, 081001(2019).

[18] Li H, Zhang L M, Jiang M R et al. Multi-focus image fusion algorithm based on supervised learning for fully convolutional neural networks[J]. Laser & Optoelectronics Progress, 57, 081015(2020).

[19] Deng L. Deep learning: methods and applications[J]. Foundations and Trends© in Signal Processing, 7, 197-387(2014).

[20] Pan S J, Yang Q. A survey on transfer learning[J]. IEEE Transactions on Knowledge and Data Engineering, 22, 1345-1359(2010). http://smartsearch.nstl.gov.cn/paper_detail.html?id=378c34ad7135c2707c673b9ac765c137

[21] Shin H C, Roth H R, Gao M C et al. Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning[J]. IEEE Transactions on Medical Imaging, 35, 1285-1298(2016). http://pubmedcentralcanada.ca/pmcc/articles/PMC4890616/

[22] Alom M Z, Yakopcic C, Nasrin M S et al. Breast cancer classification from histopathological images with inception recurrent residual convolutional neural network[J]. Journal of Digital Imaging, 32, 605-617(2019). http://link.springer.com/article/10.1007/s10278-019-00182-7