[1] Liu S T, Yin F L. The basic principle and its new advances of image segmentation methods based on graph cuts[J]. Acta Automatica Sinica, 38, 911-922(2012).

[2] Zhu Z L, Dong J B, Li M L et al. Generalized fuzzy C-means for image segmentation based on adaptive weighted image patch[J]. Laser & Optoelectronics Progress, 57, 241006(2020).

[3] Liu Y, Chen S L, Feng G F et al. Automatic segmentation of images with low depth of field based on graph cuts[J]. Acta Automatica Sinica, 41, 1471-1481(2015).

[4] Tan G H, Hou J, Han Y P et al. Low-parameter real-time image segmentation algorithm based on convolutional neural network[J]. Laser & Optoelectronics Progress, 56, 091003(2019).

[5] Zheng T Y, Tang C, Lei Z K. Multi-scale retinal vessel segmentation based on fully convolutional neural network[J]. Acta Optica Sinica, 39, 0211002(2019).

[6] Zhang F, Wu Y, Xiao Z T et al. Nanoparticle segmentation based on U-Net convolutional neural network[J]. Laser & Optoelectronics Progress, 56, 061005(2019).

[7] Rother C, Kolmogorov V, Blake A. GrabCut: interactive foreground extraction using iterated graph cuts[J]. ACM Transactions on Graphics, 23, 309-314(2004).

[8] Boykov Y, Jolly M P. Interactive organ segmentation using graph cuts[M]. //Delp S L, DiGoia A M, Jaramaz B, et al. Medical Image Computing and Computer-Assisted Intervention-MICCAI 2000. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer, 1935, 276-286(2000).

[9] Boykov Y Y, Jolly M P. Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. [C]//Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, July 7-14, 2001, Vancouver, BC, Canada. New York: IEEE, 105-112(2001).

[10] Xu Q P, Guo M, Wang Y R. Fast image segmentation algorithm based on multiscale analysis and graph cuts[J]. Application Research of Computers, 26, 3989-3991(2009).

[11] Zhou L F, He J N. Improved image segmentation algorithm based on GrabCut[J]. Journal of Computer Applications, 33, 49-52(2013).

[12] Hu Z L, Guo M. Fast segmentation in color image based on SLIC and GrabCut[J]. Computer Engineering and Applications, 52, 186-190, 270(2016).

[13] Ren D Y, Jia Z H, Yang J et al. A practical GrabCut color image segmentation based on Bayes classification and simple linear iterative clustering[J]. IEEE Access, 5, 18480-18487(2017).

[14] Chen X, He Z S, Li Y H. Improved color image segmentation of GrabCut algorithm based on SLICO[J]. Application Research of Computers, 32, 3191-3195(2015).

[15] Liu H, Shi X L, Qi K Y et al. Automatic image segmentation combined Grabcut and depth information[J]. Journal of Chinese Computer Systems, 39, 2309-2313(2018).

[16] Kong X, Ma X K. Improvement of GrabCut image segmentation algorithm based on non-normalized histogram[J]. Application Research of Computers, 37, 1549-1552(2020).

[17] Specht D F. Probabilistic neural networks[J]. Neural Networks, 3, 109-118(1990).

[18] Taha A A, Hanbury A. Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool[J]. BMC Med Imaging, 15, 29(2015).

[19] Tang M. GorelickL, Veksler O, et al. GrabCut in one cut. [C]//2013 IEEE International Conference on Computer Vision, December 1-8, 2013, Sydney, NSW, Australia. New York: IEEE, 1769-1776(2013).

[20] Wei Y K, Fan P, Zeng G. Application of improved GrabCut method in tongue diagnosis system[J]. Transducer and Microsystem Technologies, 33, 157-160(2014).