{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:47:19Z","timestamp":1771703239139,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2018,7,27]],"date-time":"2018-07-27T00:00:00Z","timestamp":1532649600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Natural&nbsp;Science&nbsp;Foundation&nbsp;of&nbsp;Hunan&nbsp;Province,&nbsp;China","award":["No.&nbsp;14JJ2008"],"award-info":[{"award-number":["No.&nbsp;14JJ2008"]}]},{"name":"National&nbsp;Natural&nbsp;Science&nbsp;Foundation&nbsp;of&nbsp;China","award":["No.&nbsp;61602522,&nbsp;No.&nbsp;61573380,&nbsp;No.&nbsp;61672542"],"award-info":[{"award-number":["No.&nbsp;61602522,&nbsp;No.&nbsp;61573380,&nbsp;No.&nbsp;61672542"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s10916-018-1014-6","type":"journal-article","created":{"date-parts":[[2018,7,27]],"date-time":"2018-07-27T02:52:34Z","timestamp":1532659954000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["An End-to-End System for Automatic Urinary Particle Recognition with Convolutional Neural Network"],"prefix":"10.1007","volume":"42","author":[{"given":"Yixiong","family":"Liang","sequence":"first","affiliation":[]},{"given":"Rui","family":"Kang","sequence":"additional","affiliation":[]},{"given":"Chunyan","family":"Lian","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Mao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,27]]},"reference":[{"issue":"2","key":"1014_CR1","doi-asserted-by":"publisher","first-page":"104","DOI":"10.3109\/03091902.2013.863394","volume":"38","author":"MD Almadhoun","year":"2014","unstructured":"Almadhoun, M. D., and El-Halees, A., Automated recognition of urinary microscopic solid particles.Journal of medical engineering & technology 38(2):104\u2013110, 2014.","journal-title":"Journal of medical engineering & technology"},{"issue":"2","key":"1014_CR2","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/s10916-014-0007-3","volume":"38","author":"D Avci","year":"2014","unstructured":"Avci, D., Leblebicioglu, M. K., Poyraz, M., and Dogantekin, E., A new method based on adaptive discrete wavelet entropy energy and neural network classifier (ADWEENN) for recognition of urine cells from microscopic images independent of rotation and scaling. Journal of medical systems 38(2):7, 2014.","journal-title":"Journal of medical systems"},{"key":"1014_CR3","unstructured":"Bell, S., Lawrence Zitnick, C., Bala, K., and Girshick, R.: Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2874\u20132883, 2016."},{"issue":"1","key":"1014_CR4","first-page":"47","volume":"57","author":"YU Budak","year":"2011","unstructured":"Budak, Y. U., and Huysal, K., Comparison of three automated systems for urine chemistry and sediment analysis in routine laboratory practice. Clinical laboratory 57(1):47, 2011.","journal-title":"Clinical laboratory"},{"key":"1014_CR5","doi-asserted-by":"crossref","unstructured":"Cai, Z., Fan, Q., Feris, R. S., and Vasconcelos, N.: A unified multi-scale deep convolutional neural network for fast object detection. European conference on computer vision, pp. 354\u2013370. Springer, 2016.","DOI":"10.1007\/978-3-319-46493-0_22"},{"issue":"1","key":"1014_CR6","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.cca.2007.05.012","volume":"384","author":"TI Chien","year":"2007","unstructured":"Chien, T. I., Kao, J. T., Liu, H. L., Lin, P. C., Hong, J. S., Hsieh, H. P., and Chien, M. J., Urine sediment examination: a comparison of automated urinalysis systems and manual microscopy. Clinica Chimica Acta 384(1):28\u201334, 2007.","journal-title":"Clinica Chimica Acta"},{"key":"1014_CR7","unstructured":"Girshick, R.: Fast r-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440\u20131448, 2015."},{"key":"1014_CR8","unstructured":"Girshick, R., Donahue, J., Darrell, T., and Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 580\u2013587, 2014."},{"issue":"1","key":"1014_CR9","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1109\/MSP.2017.2749125","volume":"35","author":"J Han","year":"2018","unstructured":"Han, J., Zhang, D., Cheng, G., Liu, N., and Xu, D., Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Processing Magazine 35(1):84\u2013100, 2018.","journal-title":"IEEE Signal Processing Magazine"},{"key":"1014_CR10","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R.: Mask r-CNN. In: IEEE International conference on computer vision (ICCV), pp. 2980\u20132988. IEEE, 2017."},{"key":"1014_CR11","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J.: Spatial pyramid pooling in deep convolutional networks for visual recognition. In: European conference on computer vision, pp. 346\u2013361. Springer , 2014."},{"key":"1014_CR12","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 , 2016."},{"key":"1014_CR13","unstructured":"Hoang Ngan Le, T., Zheng, Y., Zhu, C., Luu, K., and Savvides, M.: Multiple scale faster-RCNN approach to driver\u2019s cell-phone usage and hands on steering wheel detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 46\u201353, 2016."},{"key":"1014_CR14","doi-asserted-by":"crossref","unstructured":"Huang, J., Rathod, V., Sun, C., Zhu, M., Korattikara, A., Fathi, A., Fischer, I., Wojna, Z., Song, Y., Guadarrama, S., et al., Speed\/accuracy trade-offs for modern convolutional object detectors. In: IEEE CVPR, Vol. 4, 2017.","DOI":"10.1109\/CVPR.2017.351"},{"key":"1014_CR15","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.plabm.2016.03.002","volume":"5","author":"FD \u0130nce","year":"2016","unstructured":"\u0130nce, F. D., Ellida\u0121, H. Y., Koseo\u0121lu, M., S\u0307ims\u0307ek, N., Yal\u010b\u0131n, H., and Zengin, M.O., The comparison of automated urine analyzers with manual microscopic examination for urinalysis automated urine analyzers and manual urinalysis. Practical Laboratory Medicine 5:14\u201320, 2016.","journal-title":"Practical Laboratory Medicine"},{"key":"1014_CR16","unstructured":"Kim, K. H., Hong, S., Roh, B., Cheon, Y., and Park, M.: Pvanet: Deep but lightweight neural networks for real-time object detection. arXiv:\n                    abs\/1608.08021\n                    \n                  , 2016"},{"key":"1014_CR17","unstructured":"Kong, T., Yao, A., Chen, Y., and Sun, F.: Hypernet: towards accurate region proposal generation and joint object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 845\u2013853, 2016."},{"key":"1014_CR18","doi-asserted-by":"crossref","unstructured":"Kouri, T., Fogazzi, G., Gant, V., Hallander, H., Hofmann, W., and Guder, W.: European urinalysis guidelines. Scandinavian Journal of Clinical and Laboratory Investigation-Supplement 60(231), 2000","DOI":"10.1080\/00365513.2000.12056993"},{"key":"1014_CR19","unstructured":"Li, C., Tang, Y. Y., Luo, H., and Zheng, X.: Join gabor and scattering transform for urine sediment particle texture analysis. In: 2nd international conference on Cybernetics (CYBCONF), 2015 IEEE, pp. 410\u2013415. IEEE, 2015."},{"key":"1014_CR20","unstructured":"Li, Y., and He, K.: Sun, J., others: r-FCN: Object detection via region-based fully convolutional networks. In: Advances in neural information processing systems, pp. 379\u2013387, 2016."},{"issue":"9","key":"1014_CR21","doi-asserted-by":"publisher","first-page":"11,429","DOI":"10.1016\/j.eswa.2009.03.049","volume":"36","author":"Y Liang","year":"2009","unstructured":"Liang, Y., Fang, B., Qian, J., Chen, L., Li, C., and Liu, Y., False positive reduction in urinary particle recognition. Expert Systems with Applications 36(9):11,429\u201311,438, 2009.","journal-title":"Expert Systems with Applications"},{"key":"1014_CR22","unstructured":"Lin, T. Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., and Belongie, S.: Feature pyramid networks for object detection. In: CVPR, Vol. 1, p. 4, 2017."},{"key":"1014_CR23","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C. Y., and Berg, A. C.: SSD: Single shot multibox detector. In: European conference on computer vision, pp. 21\u201337. Springer, 2016."},{"key":"1014_CR24","unstructured":"Long, J., Shelhamer, E., and Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440, 2015."},{"issue":"1","key":"1014_CR25","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.patrec.2006.06.010","volume":"28","author":"M Ranzato","year":"2007","unstructured":"Ranzato, M., Taylor, P., House, J., Flagan, R., LeCun, Y., and Perona, P., Automatic recognition of biological particles in microscopic images. Pattern recognition letters 28(1):31\u201339, 2007.","journal-title":"Pattern recognition letters"},{"key":"1014_CR26","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A.: You only look once: Unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788, 2016."},{"key":"1014_CR27","unstructured":"Redmon, J., and Farhadi, A.: Yolo9000: better, faster, stronger. In: 2017 IEEE Conference on computer vision and pattern recognition (CVPR), pp. 6517\u20136525. IEEE, 2017."},{"key":"1014_CR28","unstructured":"Redmon, J., and Farhadi, A., 2018"},{"key":"1014_CR29","unstructured":"Ren, S., He, K., Girshick, R., and Sun, J.: Faster R-CNN: Towards real-time object detection with region proposal networks. In: Advances in neural information processing systems, pp. 91\u201399, 2015."},{"issue":"3","key":"1014_CR30","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al., Imagenet large scale visual recognition challenge. International Journal of Computer Vision 115(3):211\u2013252, 2015.","journal-title":"International Journal of Computer Vision"},{"issue":"5","key":"1014_CR31","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/34.589215","volume":"19","author":"C Schmid","year":"1997","unstructured":"Schmid, C., and Mohr, R., Local grayvalue invariants for image retrieval. IEEE transactions on pattern analysis and machine intelligence 19(5):530\u2013535, 1997.","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"1014_CR32","unstructured":"Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., and LeCun, Y.: Overfeat: Integrated recognition, localization and detection using convolutional networks. arXiv:\n                    1312.6229\n                    \n                  , 2013"},{"key":"1014_CR33","unstructured":"Shen, M. l., and Zhang, R.: Urine sediment recognition method based on svm and adaboost. In: International conference on Computational intelligence and software engineering, 2009. ciSE 2009, pp. 1\u20134. IEEE, 2009."},{"key":"1014_CR34","unstructured":"Shrivastava, A., Gupta, A., and Girshick, R.: Training region-based object detectors with online hard example mining. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 761\u2013769, 2016."},{"key":"1014_CR35","unstructured":"Simonyan, K., and Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:\n                    1409.1556\n                    \n                  , 2014"},{"issue":"2","key":"1014_CR36","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/s11263-013-0620-5","volume":"104","author":"JR Uijlings","year":"2013","unstructured":"Uijlings, J. R., Van De Sande, K. E., Gevers, T., and Smeulders, A. W., Selective search for object recognition. International journal of computer vision 104(2):154\u2013171, 2013.","journal-title":"International journal of computer vision"},{"key":"1014_CR37","unstructured":"Zeiler, M. D., and Fergus, R.: Visualizing and understanding convolutional networks. In: European conference on computer vision, pp. 818\u2013833. Springer, 2014."},{"key":"1014_CR38","unstructured":"Zhang, L., Lin, L., Liang, X., and He, K.: Is Faster r-CNN doing well for pedestrian detection?. In: European conference on computer vision, pp. 443\u2013457. Springer, 2016."},{"key":"1014_CR39","unstructured":"Zhang, S., Wen, L., Bian, X., Lei, Z., and Li, S. Z.: Single-shot refinement neural network for object detection. In: IEEE CVPR, 2018."},{"key":"1014_CR40","unstructured":"Zhou, Y., and Zhou, H.: Automatic classification and recognition of particles in urinary sediment images. In: Computer, informatics, cybernetics and applications, pp. 1071\u20131078. Springer, 2012."},{"key":"1014_CR41","unstructured":"Zitnick, C. L., and Doll\u00e1r, P.: Edge boxes: Locating object proposals from edges. In: European conference on computer vision, pp. 391\u2013405. Springer, 2014."}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10916-018-1014-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-018-1014-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-018-1014-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T19:25:13Z","timestamp":1564169113000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10916-018-1014-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,27]]},"references-count":41,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["1014"],"URL":"https:\/\/doi.org\/10.1007\/s10916-018-1014-6","relation":{},"ISSN":["0148-5598","1573-689X"],"issn-type":[{"value":"0148-5598","type":"print"},{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,27]]},"assertion":[{"value":"2 July 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 July 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of interests"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Ethical Approval"}}],"article-number":"165"}}