{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T07:51:00Z","timestamp":1769845860874,"version":"3.49.0"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2017,8,14]],"date-time":"2017-08-14T00:00:00Z","timestamp":1502668800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2017,9]]},"DOI":"10.1007\/s10916-017-0773-9","type":"journal-article","created":{"date-parts":[[2017,8,14]],"date-time":"2017-08-14T10:10:11Z","timestamp":1502705411000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images"],"prefix":"10.1007","volume":"41","author":[{"given":"Ramin","family":"Nateghi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2108-5958","authenticated-orcid":false,"given":"Habibollah","family":"Danyali","sequence":"additional","affiliation":[]},{"given":"Mohammad Sadegh","family":"Helfroush","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,8,14]]},"reference":[{"key":"773_CR1","doi-asserted-by":"crossref","unstructured":"Frierson, J H. F., Interobserver reproducibility of the Nottingham modification of the bloom and richardson histologic grading scheme for infiltrating ductal carcinoma. Am. J. Clin. Pathol. 195\u2013198, 1995","DOI":"10.1093\/ajcp\/103.2.195"},{"key":"773_CR2","doi-asserted-by":"crossref","unstructured":"He, L., Long, L.R, Antani, S. and Thoma, G.R., Histology image analysis for carcinoma detection and grading. Comput. Methods Prog. Biomed. 538\u2013556, 2012.","DOI":"10.1016\/j.cmpb.2011.12.007"},{"key":"773_CR3","doi-asserted-by":"crossref","unstructured":"Ciresan., D. C. Mitosis detection in breast cancer histology images with deep neural networks, in: MICCAI 2013. Springer, 411\u2013418, 2013.","DOI":"10.1007\/978-3-642-40763-5_51"},{"key":"773_CR4","doi-asserted-by":"crossref","unstructured":"Nateghi, R., Danyali, H., Helfroush, M. S. and Tashk, A., Intelligent cad system for automatic detection of mitosis cells from breast cancer histology slide images based on teaching- learning based optimization, Comput. Biol. J, 2014.","DOI":"10.1155\/2014\/970898"},{"key":"773_CR5","unstructured":"Khan, A.M. El-Daly H. and Rajpoot., N. M. A gamma-gaussian mixture model for detection of mitosis cells in breast cancer histopathology images. In: Pattern Recognition (ICPR), 2012, 21st International Conference on. IEEE, 149\u2013152, 2012."},{"key":"773_CR6","unstructured":"Sommer, C. Fiaschi, L. Hamprecht F. A. and Gerlich., D. W. Learning-based mitosis cell detection in histopathological images. In: Pattern Recognition (ICPR), International Conference on. IEEE, 2306\u20132309, 2012."},{"key":"773_CR7","doi-asserted-by":"crossref","unstructured":"Irshad, H., Jalali, S., Roux, L., Racoceanu, D., Hwee, L. J., Le Naour, G., and Capron, F., Automated mitosis detection using texture, sift features and HMAX biologically inspired approach. J. pathol. Inf., 2013.","DOI":"10.4103\/2153-3539.109870"},{"key":"773_CR8","doi-asserted-by":"crossref","unstructured":"Paul A. and Mukherjee., D. P. Mitosis detection for invasive breast cancer grading in histopathological images. Image Processing. IEEE Transaction on, 4041\u20134054, 2015.","DOI":"10.1109\/TIP.2015.2460455"},{"key":"773_CR9","doi-asserted-by":"crossref","unstructured":"Tashk, A., Helfroush. M. S., Danyali, H. and Akbarzadeh Jahromi, M., Automatic detection of breast cancer mitosis cells based on the combination of textural, statistical and innovative mathematical features. Appl. Math. Model., 6165\u20136182, 2015.","DOI":"10.1016\/j.apm.2015.01.051"},{"key":"773_CR10","doi-asserted-by":"crossref","unstructured":"Chen, H. Dou, Q. Wang, X. Qin J. and Heng., P. Mitosis detection in breast cancer histology images via deep cascaded networks. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 1160\u20131166, 2016.","DOI":"10.1609\/aaai.v30i1.10140"},{"key":"773_CR11","doi-asserted-by":"crossref","unstructured":"Roullier, V., Lezoray, O., Ta, V.T., and Elmoataz, A., Multi-resolution graph-based analysis of histopathological whole slide images, Application to mitosis cell extraction and visualization. Comput. Med. Imaging Graph., 603\u2013615, 2011.","DOI":"10.1016\/j.compmedimag.2011.02.005"},{"key":"773_CR12","doi-asserted-by":"crossref","unstructured":"Tek, F. B., Mitosis detection using generic features and an ensemble of cascade adaboosts. J. Pathol. Inf., 2013.","DOI":"10.4103\/2153-3539.112697"},{"key":"773_CR13","doi-asserted-by":"crossref","unstructured":"Lu, C. and Mandal, M.., Towards automatic mitosis cells detection and segmentation in multi-spectral histopathological images. IEEE J. Biomed. and Health Inform., 594\u2013605, 2013.","DOI":"10.1109\/JBHI.2013.2277837"},{"key":"773_CR14","doi-asserted-by":"crossref","unstructured":"Irshad, H. Gouaillard, A. Roux L. and Racoceanu., D. Spectral band selection for mitosis detection in histopathology. In: Biomedical Imaging (ISBI), 11st International Symposium on. IEEE, 1279\u20131282, 2014.","DOI":"10.1109\/ISBI.2014.6868110"},{"key":"773_CR15","doi-asserted-by":"crossref","unstructured":"Irshad, H., Gouaillard, A., Roux, L. and Racoceanu, D., Multispectral band selection and spatial characterization, application to mitosis detection in breast cancer histopathology. Comput. Med. Imaging Graph, 390\u2013402, 2014.","DOI":"10.1016\/j.compmedimag.2014.04.003"},{"key":"773_CR16","doi-asserted-by":"crossref","unstructured":"Macenko, M. Niethammer, M. Marron, J. S. Borland, D. Woosley, JT Xiaojun, G. Schmitt C. and Thomas., NE. A method for normalizing histology slides for quantitative analysis. In: Biomedical Imaging (ISBI), International Symposium on. IEEE, 1107\u20131110, 2009.","DOI":"10.1109\/ISBI.2009.5193250"},{"key":"773_CR17","doi-asserted-by":"crossref","unstructured":"Khan, A. M. Rajpoot, N. Treanor, D. Magee., D. A nonlinear mapping approach to stain normalization in digital histopathology images using image-specific color deconvolution. Biomedical Engineering, IEEE Transactions on, 1729\u20131738, 2014.","DOI":"10.1109\/TBME.2014.2303294"},{"key":"773_CR18","doi-asserted-by":"crossref","unstructured":"Yang., X. Nuclei segmentation using marker-controlled watershed, tracking using mean-shift, and kalman filter in time-lapse microscopy. Circuits and Systems I, Regular Papers, IEEE Trans. on, 2405\u20132414, 2006.","DOI":"10.1109\/TCSI.2006.884469"},{"key":"773_CR19","doi-asserted-by":"crossref","unstructured":"Al-Kofahi., Y. Improved automatic detection and segmentation of cell nuclei in histopathology images. Biomedical Engineering, IEEE Transactions on, 841\u2013852, 2010.","DOI":"10.1109\/TBME.2009.2035102"},{"key":"773_CR20","doi-asserted-by":"crossref","unstructured":"Mukherjee, D. P. Ray, N. and Acton., S. T. Level set analysis for leukocyte detection and tracking. Image Processing, IEEE Transactions on, 562\u2013572, 2004.","DOI":"10.1109\/TIP.2003.819858"},{"key":"773_CR21","doi-asserted-by":"crossref","unstructured":"Plissiti, M. E. Nikou., C. Overlapping cell nuclei segmentation using a spatially adaptive active physical model. Image Processing, IEEE Transactions on, 4568\u20134580, 2012.","DOI":"10.1109\/TIP.2012.2206041"},{"key":"773_CR22","doi-asserted-by":"crossref","unstructured":"Otsu., N. A threshold selection method from gray-level histograms. Systems, Man and Cybernetics, IEEE Transaction on, 62\u201366, 1979.","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"773_CR23","doi-asserted-by":"crossref","unstructured":"Nagase, A. Takahashi M. and Nakano., M. Automatic calculation and visualization of nuclear density in whole slide images of hepatic histological sections. Bio-Med. Mater. Eng., 1335\u20131344, 2015.","DOI":"10.3233\/BME-151431"},{"key":"773_CR24","doi-asserted-by":"crossref","unstructured":"Karagiannidis G. K. and Lioumpas., A. S. An improved approximation for the Gaussian Q-function. IEEE Communications Letters, 644\u2013646, 2007.","DOI":"10.1109\/LCOMM.2007.070470"},{"key":"773_CR25","doi-asserted-by":"crossref","unstructured":"Haralick, R. M. Shanmygam K. and Dinstein., I. Textural features for image classification. Systems, Man and Cybernetics, IEEE Transaction on, 610\u2013621, 1973.","DOI":"10.1109\/TSMC.1973.4309314"},{"key":"773_CR26","doi-asserted-by":"crossref","unstructured":"Tang., X. Texture information in run-length matrices. Image Processing, IEEE Transactions on, 1602\u20131609, 1998.","DOI":"10.1109\/83.725367"},{"key":"773_CR27","doi-asserted-by":"crossref","unstructured":"Guo., Z. A complete modeling of local binary pattern operator for texture classification. Image Processing, IEEE Transactions on, 1657\u20131663, 2010.","DOI":"10.1109\/TIP.2010.2044957"},{"key":"773_CR28","doi-asserted-by":"crossref","unstructured":"Cortes, C. Vapnik., V. Support-vector networks. Machine Learning Springer, 273\u2013297, 1995.","DOI":"10.1007\/BF00994018"},{"key":"773_CR29","unstructured":"Available as on 10.06.2014. [Online]. Available, http:\/\/mitos-atypia-14.grand-challenge.org\/dataset\/"},{"key":"773_CR30","unstructured":"Available as on 5.02.2013. [Online]. Available: http:\/\/amida13.isi.uu.nl\/?q=node\/62"},{"key":"773_CR31","unstructured":"Available as on 8.01.2012. [Online]. Available: http:\/\/ludo17.free.fr\/mitos_2012\/dataset.html"},{"key":"773_CR32","doi-asserted-by":"crossref","unstructured":"Perona, P. and Malik, J.., Scale-space and edge detection using anisotropic diffusion. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 629\u2013639, 1990.","DOI":"10.1109\/34.56205"},{"key":"773_CR33","doi-asserted-by":"crossref","unstructured":"Xu., L. Image smoothing via l 0 gradient minimization. ACM Trans. Graph. 174, 2011.","DOI":"10.1145\/2070752.2024208"}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10916-017-0773-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-017-0773-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-017-0773-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T04:40:52Z","timestamp":1659328852000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10916-017-0773-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,14]]},"references-count":33,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2017,9]]}},"alternative-id":["773"],"URL":"https:\/\/doi.org\/10.1007\/s10916-017-0773-9","relation":{},"ISSN":["0148-5598","1573-689X"],"issn-type":[{"value":"0148-5598","type":"print"},{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,14]]},"article-number":"146"}}