• Laser & Optoelectronics Progress
  • Vol. 56, Issue 6, 061005 (2019)
Fang Zhang1、2, Yue Wu1, Zhitao Xiao1、2、*, Lei Geng1、2, Jun Wu1、2, Yanbei Liu1、2, and Wen Wang1、2
Author Affiliations
  • 1 School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China
  • 2 Tianjin Key Laboratory of Optoelectronic Detection Technology and System, Tianjin 300387, China
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    DOI: 10.3788/LOP56.061005 Cite this Article Set citation alerts
    Fang Zhang, Yue Wu, Zhitao Xiao, Lei Geng, Jun Wu, Yanbei Liu, Wen Wang. Nanoparticle Segmentation Based on U-Net Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2019, 56(6): 061005 Copy Citation Text show less
    References

    [1] Pan L C, Ge B Z, Zhang F G. Laser particle size measurement based on annular sample cell[J]. Acta Optica Sinica, 37, 1029001(2017).

    [2] He F L, Guo Y C, Gao C. Improved PCNN method for human target infrared image segmentation under complex environments[J]. Acta Optica Sinica, 37, 0215003(2017).

    [3] Fang J X. Study based on the variational level set methods for image segmentation[D]. Shanghai: Shanghai Jiao Tong University, 20-28(2012).

    [4] Liu X B. The study on the segmentation of circle-like particle images[D]. Changsha: Hunan University(2006).

    [5] Ni K, Wu Y Q, Geng S. Segmentation of metallographic image based on improved CV model integrated with local fitting term[J]. Acta Optica Sinica, 38, 0411009(2018).

    [6] Li C M, Kao C Y, Gore J C et al. Minimization of region-scalable fitting energy for image segmentation[J]. IEEE Transactions on Image Processing, 17, 1940-1949(2008). http://www.ncbi.nlm.nih.gov/pubmed/18784040/

    [7] Zhang B, Ni K Z, Wang L J et al. New algorithm of detecting optical surface imperfection based on background correction and image segmentation[J]. Acta Optica Sinica, 36, 0911004(2016).

    [8] Wang Y, Chen J, Wang G. Particle seed images segmentation method based on the improved fuzzy C-means clustering algorithm[J]. Journal of North University of China(Natural Science Edition), 39, 177-182(2018).

    [9] Lü J C, Wang L P, Zhang Q Q. Research on the background segmentation method based on nano-particles images[J]. Journal of Baicheng Normal University, 31, 1-6(2017).

    [10] Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 640-651(2017). http://www.ncbi.nlm.nih.gov/pubmed/27244717/

    [11] Badrinarayanan V, Kendall A, Cipolla R. SegNet: a deep convolutional encoder-decoder architecture for image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 2481-2495(2017). http://arxiv.org/abs/1511.00561v3

    [12] Bansal A, Chen X L, Russell B, by the pixels, for the pixels[EB/OL] et al. -02-27)[2018-11-23]. https:∥arxiv., org/abs/1702, 06506(2017).

    [13] Ronneberger O, Fischer P, Brox T. U-Net: Convolutional networks for biomedical image segmentation. [C]∥International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2015), October 5-9, Munich, Germany. Switzerland: Springer, 234-241(2015).

    [14] Xiao Z T, Yuan Q, Zhang F et al. The oriented partial differential equation based on the discontinuities measure for electronic speckle pattern interferometry[J]. Journal of Electronics & Information Technology, 36, 2600-2606(2014).

    [15] Weickert J, Scharr H. A scheme for coherence-enhancing diffusion filtering with optimized rotation invariance[J]. Journal of Visual Communication and Image Representation, 13, 103-118(2002). http://dl.acm.org/citation.cfm?id=2796818

    [16] Zhang Y G, Yi B S, Wu C Y et al. Low-dose CT image denoising method based on convolutional neural network[J]. Acta Optica Sinica, 38, 0410003(2018).

    [17] Gao W, Zhou Z H. Dropout Rademacher complexity of deep neural networks[J]. Science China Information Sciences, 59, 072104(2016). http://link.springer.com/article/10.1007/s11432-015-5470-z

    Fang Zhang, Yue Wu, Zhitao Xiao, Lei Geng, Jun Wu, Yanbei Liu, Wen Wang. Nanoparticle Segmentation Based on U-Net Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2019, 56(6): 061005
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