[1]
S. Mirjalili, and A. Lewis, "The whale optimization algorithm", Adv. Eng. Softw., vol. 95, pp. 51-67, 2016. [http://dx.doi.org/10.1016/j.advengsoft.2016.01.008].
[2]
J. Kennedy, “Particle swarm optimization”, Encycloped. Mach. learn., Springer: MA, USA, 2011, pp. 760-766. [DOI: https://doi.org/10.1007/978-0-387-30164-8_630]
[3]
J.C. Bansal, H. Sharma, S.S. Jadon, and M. Clerc, "Spider monkey optimization algorithm for numerical optimization", Memetic Comput., vol. 6, no. 1, pp. 31-47, 2014.
[4]
R.R. Chhikara, P. Sharma, and L. Singh, "A hybrid feature selection approach based on improved PSO and filter approaches for image steganalysis", Int. J. Mach. Learn. Cybern., vol. 7, pp. 1195-1206, 2016. [http://dx.doi.org/10.1007/s13042-015-0448-0].
[5]
F.G. Mohammadi, and M.S. Abadeh, "Image steganalysis using a bee colony based feature selection algorithm", Eng. Appl. Artif. Intell., vol. 31, pp. 35-43, 2014. [http://dx.doi.org/10.1016/j.engappai.2013.09.016].
[6]
E. Rashedi, H. Nezamabadi-Pour, and S. Saryazdi, "GSA: a gravitational search algorithm", Inf. Sci., vol. 179, pp. 2232-2248, 2009. [http://dx.doi.org/10.1016/j.ins.2009.03.004].
[7]
E. Emary, H.M. Zawbaa, C. Grosan, and A.E. Hassenian, Feature subset selection approach by gray-wolf optimization., Afro-Euro. Conf. for Industrial Advancem, pp. 1-13. 2015 [http://dx.doi.org/10.1007/978-3-319-13572-4_1]
[8]
K. Hussain, M.N.M. Salleh, S. Cheng, and Y. Shi, "Metaheuristic research: a comprehensive survey", Artif. Intell. Rev., pp. 1-43, 2018.
[9]
M. Saraswat, K. Arya, and H. Sharma, "Leukocyte segmentation in tissue images using differential evolution algorithm", Swarm Evol. Comput., vol. 11, pp. 46-54, 2013. [http://dx.doi.org/10.1016/j.swevo.2013.02.003].
[10]
G. Kaur, and S. Arora, "Chaotic whale optimization algorithm", J. Computat. Des. Eng, vol. 5, pp. 275-284, 2018.
[11]
H.S. Alamri, Y.A. Alsariera, and K.Z. Zamli, "Opposition-based whale optimization algorithm", Adv. Sci. Lett., vol. 24, no. 10, pp. 7461-7464, 2018. [http://dx.doi.org/10.1166/asl.2018.12959].
[12]
H. Mittal, and M. Saraswat, "An optimum multi-level image thresholding segmentation using non-local means 2d histogram and exponential k best gravitational search algorithm", Eng. Appl. Artif. Intell., vol. 71, pp. 226-235, 2018. [http://dx.doi.org/10.1016/j.engappai.2018.03.001].
[13]
R. Pal, and M. Saraswat, Data clustering using enhanced biogeography-based optimization2017, Tenth International Conference on Contemporary Computing (IC3), Noida, India 2017, pp. 1-6. [http://dx.doi.org/10.1109/IC3.2017.8284305]
[14]
M.N. Gurcan, L.E. Boucheron, A. Can, A. Madabhushi, N.M. Rajpoot, and B. Yener, "Histopathological image analysis: a review", IEEE Rev. Biomed. Eng., vol. 2, pp. 147-171, 2009. [http://dx.doi.org/10.1109/RBME.2009.2034865]. [PMID: 20671804].
[15]
H. Mittal, and M. Saraswat, "Classification of histopathological images through bag-of-visual-words and gravitational search algorithm", In: International Conference Soft Computing for Problem Solving, Springer: Singapore 2017, pp. 231-241. [http://dx.doi.org/10.1007/978-981-13-1595-4_18]
[16]
U. Srinivas, H.S. Mousavi, V. Monga, A. Hattel, and B. Jayarao, "Simultaneous sparsity model for histopathological image representation and classification", IEEE Trans. Med. Imaging, vol. 33, no. 5, pp. 1163-1179, 2014. [http://dx.doi.org/10.1109/TMI.2014.2306173]. [PMID: 24770920].
[17]
V. Monga, ADL data set, 2018. Available from: , http://signal.eepsu.edu/histimg2.htmlJan
[18]
N. Nayak, H. Chang, A. Borowsky, P. Spellman, and B. Parvin, Classification of tumor histopathology via sparse feature learning 2013, IEEE 10th International Symposium on Biomedical Imaging, San Francisco, CA, USA, pp. 410-413. 2013 [http://dx.doi.org/10.1109/ISBI.2013.6556499]
[19]
M. Saraswat, and K.V. Arya, "Feature selection and classification of leukocytes using random forest", Med. Biol. Eng. Comput., vol. 52, no. 12, pp. 1041-1052, 2014. [http://dx.doi.org/10.1007/s11517-014-1200-8]. [PMID: 25284218].
[20]
M. Saraswat, and K.V. Arya, "Automated microscopic image analysis for leukocytes identification: a survey", Micron, vol. 65, pp. 20-33, 2014. [http://dx.doi.org/10.1016/j.micron.2014.04.001]. [PMID: 25041828].
[21]
N. Orlov, L. Shamir, T. Macura, J. Johnston, D.M. Eckley, and I.G. Goldberg, "WND-CHARM: multi-purpose image classification using compound image transforms", Pattern Recognit. Lett., vol. 29, no. 11, pp. 1684-1693, 2008. [http://dx.doi.org/10.1016/j.patrec.2008.04.013]. [PMID: 18958301].
[22]
H.L. Tang, R. Hanka, and H.H-S. Ip, "Histological image retrieval based on semantic content analysis", IEEE Trans. Inf. Technol. Biomed., vol. 7, no. 1, pp. 26-36, 2003. [http://dx.doi.org/10.1109/TITB.2003.808500]. [PMID: 12670016].
[23]
G. Diaz, and E. Romero, "Histopathological image classification using stain component features on a plsa model", In: Iberoamerican Congress on Pattern Recognition., Springer, pp. 55-62. 2010 [http://dx.doi.org/10.1007/978-3-642-16687-7_12]
[24]
U. Srinivas, H. Mousavi, C. Jeon, V. Monga, A. Hattel, and B. Jayarao, SHIRC: A simultaneous sparsity model for histopathological image representation and classification2013, IEEE 10th International Symposium on Biomedical Imaging, San Francisco, CA, USA 2013, pp. 1118-1121. [http://dx.doi.org/10.1109/ISBI.2013.6556675]
[25]
M. Ghosh, D. Das, C. Chakraborty, and A.K. Ray, "Automated leukocyte recognition using fuzzy divergence", Micron, vol. 41, no. 7, pp. 840-846, 2010. [http://dx.doi.org/10.1016/j.micron.2010.04.017]. [PMID: 20554209].
[26]
T.H. Vu, H.S. Mousavi, V. Monga, G. Rao, and U.K. Rao, "Histopathological image classification using discriminative feature-oriented dictionary learning", IEEE Trans. Med. Imaging, vol. 35, no. 3, pp. 738-751, 2016. [http://dx.doi.org/10.1109/TMI.2015.2493530]. [PMID: 26513781].
[27]
A.A. Cruz-Roa, J.E.A. Ovalle, A. Madabhushi, and F.A.G. Osorio, "A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection", In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer , pp. 403-410. 2013 [http://dx.doi.org/10.1007/978-3-642-40763-5_50]
[28]
J. Xu, L. Xiang, Q. Liu, H. Gilmore, J. Wu, J. Tang, and A. Madabhushi, "Stacked sparse autoencoder (SSAE) for nuclei detection on breast cancer histopathology images", IEEE Trans. Med. Imaging, vol. 35, no. 1, pp. 119-130, 2016. [http://dx.doi.org/10.1109/TMI.2015.2458702]. [PMID: 26208307].
[29]
H. Chang, N. Nayak, P.T. Spellman, and B. Parvin, "Characterization of tissue histopathology via predictive sparse decomposition and spatial pyramid matching", In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, pp. 91-98. 2013. [http://dx.doi.org/10.1007/978-3-642-40763-5_12]
[30]
C. Malon, M. Miller, H.C. Burger, E. Cosatto, and H.P. Graf, "Identifying histological elements with convolutional neural networks", In: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology, ACM: Cergy-Pontoise, France, pp. 450-456. 2008. [http://dx.doi.org/10.1145/1456223.1456316]
[31]
L. Hou, D. Samaras, T.M. Kurc, Y. Gao, J.E. Davis, and J.H. Saltz, "Patch-based convolutional neural network for whole slide tissue image classification", In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA 2016, pp. 2424-2433. [http://dx.doi.org/10.1109/CVPR.2016.266]
[32]
Y. Zhou, H. Chang, K. Barner, P. Spellman, and B. Parvin, "Classification of histology sections via multispectral convolutional sparse coding", In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA 2014, pp. 3081-3088. [http://dx.doi.org/10.1109/CVPR.2014.394]
[33]
J. Arevalo, A. Cruz-Roa, V. Arias, E. Romero, and F.A. González, "An unsupervised feature learning framework for basal cell carcinoma image analysis", Artif. Intell. Med., vol. 64, no. 2, pp. 131-145, 2015. [http://dx.doi.org/10.1016/j.artmed.2015.04.004]. [PMID: 25976208].
[34]
J. Xu, X. Luo, G. Wang, H. Gilmore, and A. Madabhushi, "A deep convolutional neural network for segmenting and classifying epithelial and stromal regions in histopathological images", Neurocomputing, vol. 191, pp. 214-223, 2016. [http://dx.doi.org/10.1016/j.neucom.2016.01.034]. [PMID: 28154470].
[35]
J.C. Caicedo, A. Cruz, and F.A. Gonzalez, "Histopathology image classification using bag of features and kernel functions", In: Conference on Artificial Intelligence in Medicine in Europe, Springer, pp. 126-135. , 2009. [http://dx.doi.org/10.1007/978-3-642-02976-9_17]
[36]
M. Dholey, M. Maity, A. Sarkar, A. Giri, A. Sadhu, K. Chaudhury, S. Das, and J. Chatterjee, "Combining GMM-based hidden markov random field and bag-of-words trained classifier for lung cancer detection using pap-stained microscopic images", In: Advanced Computational and Communication Paradigms., Springer, pp. 695-705. 2018. [http://dx.doi.org/10.1007/978-981-10-8237-5_67]
[37]
S.H. Raza, R.M. Parry, Y. Sharma, Q. Chaudry, R.A. Moffitt, A. Young, and M.D. Wang, Automated classification of renal cell carcinoma subtypes using bag-of-features2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, pp. 6749-6752. 2010. [http://dx.doi.org/10.1109/IEMBS.2010.5626009]
[38]
S.H. Raza, R.M. Parry, R.A. Moffitt, A.N. Young, and M.D. Wang, "An analysis of scale and rotation invariance in the bag-of-features method for histopathological image classification", In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer: Berlin Heidelber, pp. 66-74. 2011. [http://dx.doi.org/10.1007/978-3-642-23626-6_9]
[39]
R. Hernandez-Garcia, J. Ramos-Cozar, N. Guil, E. Garcia-Reyes, and H. Sahli, "Improving bag-of-visual-words model using visual n-grams for human action classification", Expert Syst. Appl., vol. 92, pp. 182-191, 2018. [http://dx.doi.org/10.1016/j.eswa.2017.09.016].
[40]
A. Cruz-Roa, G. Diaz, E. Romero, and F. A. Gonzalez, "Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization", J. Pathol. Inform., vol. 2, . 2011. [http://dx.doi.org/10.4103/2153-3539.92031]
[41]
H. Bay, T. Tuytelaars, and L. van Gool, "Surf: Speeded up robust features", In: Leonardis A., Bischof H., and Pinz A., Eds., European Conf. Comp. Vis., Springer: Berlin, Heidelberg Vol. 3951, pp. 404-417. 2016
[42]
N. Dalal, and B. Triggs, "Histograms of oriented gradients for human detection", In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), San Diego, CA, USA, pp. 886-893. 2005. [http://dx.doi.org/10.1109/CVPR.2005.177]
[43]
A. Alahi, R. Ortiz, and P. Vandergheynst, "Freak: fast retina keypoint", In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA, pp. 510-517. 2012. [http://dx.doi.org/10.1109/CVPR.2012.6247715]
[44]
E. Rashedi, H. Nezamabadi-Pour, and S. Saryazdi, "GSA: a gravitational search algorithm", Inf. Sci., vol. 179, no. 13, pp. 2232-2248, 2009. [http://dx.doi.org/10.1016/j.ins.2009.03.004].
[45]
A.K. Qin, V.L. Huang, and P.N. Suganthan, "Differential evolution algorithm with strategy adaptation for global numerical optimization", IEEE Trans. Evol. Comput., vol. 13, no. 2, pp. 398-417, 2009. [http://dx.doi.org/10.1109/TEVC.2008.927706].
[46]
S. Mirjalili, "The ant lion optimizer", Adv. Eng. Softw., vol. 83, pp. 80-98, 2015. [http://dx.doi.org/10.1016/j.advengsoft.2015.01.010].
[47]
S. Mirjalili, "SCA: a sine cosine algorithm for solving optimization problems", Knowl. Base. Syst., vol. 96, pp. 120-133, 2016. [http://dx.doi.org/10.1016/j.knosys.2015.12.022].
[48]
S. Saremi, S. Mirjalili, and A. Lewis, "Grasshopper optimisation algorithm: theory and application", Adv. Eng. Softw., vol. 105, pp. 30-47, 2017. [http://dx.doi.org/10.1016/j.advengsoft.2017.01.004].
[49]
G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, "Visual categorization with bags of keypoints", In: Workshop on statistical learning in computer vision, ECCV , pp. 1-22. 2004
[50]
X. Yao, Y. Liu, and G. Lin, "Evolutionary programming made faster", IEEE Trans. Evol. Comput., vol. 3, no. 2, pp. 82-102, 1999. [http://dx.doi.org/10.1109/4235.771163].
[51]
"Blue histology, Available from:", http://www.lab.anhb.uwa.edu.au/ mb140/ [Accessed on 10 April 2017]
[52]
K. Sirinukunwattana, S.E. Ahmed Raza, Y-W. Tsang, D.R. Snead, I.A. Cree, and N.M. Rajpoot, "Locality sensitive deep learning for detection and classification of nuclei in routine colon cancer histology images", IEEE Trans. Med. Imaging, vol. 35, no. 5, pp. 1196-1206, 2016. [http://dx.doi.org/10.1109/TMI.2016.2525803]. [PMID: 26863654].
