{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T15:26:48Z","timestamp":1784215608840,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,1,25]],"date-time":"2019-01-25T00:00:00Z","timestamp":1548374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,1,25]]},"DOI":"10.1145\/3310986.3311010","type":"proceedings-article","created":{"date-parts":[[2019,4,30]],"date-time":"2019-04-30T12:12:51Z","timestamp":1556626371000},"page":"186-191","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Application of Computer Vision and Deep Learning in Breast Cancer Assisted Diagnosis"],"prefix":"10.1145","author":[{"given":"Gu","family":"Yunchao","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineer, Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Jiayao","sequence":"additional","affiliation":[{"name":"Xianyang Rainbow Middle School, Xianyang, Shaanxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,1,25]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"GLOBOCAN 2008","author":"Ferlay J.","year":"2010","unstructured":"Ferlay J. GLOBOCAN 2008 , cancer incidence and mortality worldwide: IARC Cancer-Base No. 10{J}. http:\/\/globocan. iarc. fr , 2010 . Ferlay J. GLOBOCAN 2008, cancer incidence and mortality worldwide: IARC Cancer-Base No. 10{J}. http:\/\/globocan. iarc. fr, 2010."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.188.2.8327668"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp1606181"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2005.1561621"},{"issue":"1","key":"e_1_3_2_1_5_1","first-page":"129","article-title":"Locally adaptive wavelet domain Bayesian processor for denoising medical ultrasound images using Speckle modelling based on Rayleigh distribution{J}. Vision, Image and Signal Processing","volume":"152","author":"Gupta","year":"2005","unstructured":"Gupta , Chauhan, R.C, Locally adaptive wavelet domain Bayesian processor for denoising medical ultrasound images using Speckle modelling based on Rayleigh distribution{J}. Vision, Image and Signal Processing , IEE Proceedings - , 2005 , 152 ( 1 ): 129 -- 135 . Gupta, Chauhan, R.C, et al. Locally adaptive wavelet domain Bayesian processor for denoising medical ultrasound images using Speckle modelling based on Rayleigh distribution{J}. Vision, Image and Signal Processing, IEE Proceedings -, 2005, 152(1):129--135.","journal-title":"IEE Proceedings -"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0041-624X(03)00105-7"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2002.808364"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2005.1504017"},{"issue":"4","key":"e_1_3_2_1_9_1","first-page":"70","article-title":"Diagnosis Model Based Neutral -network in Galactophore Cancer Cell Identification {J}","volume":"26","author":"Liu Q.S.","year":"2003","unstructured":"Liu Q.S. , He L.Q . Diagnosis Model Based Neutral -network in Galactophore Cancer Cell Identification {J} . Journal of Chongqing University , 2003 , 26 ( 4 ): 70 -- 72 . Liu Q.S., He L.Q. Diagnosis Model Based Neutral -network in Galactophore Cancer Cell Identification {J}. Journal of Chongqing University, 2003, 26(4):70--72.","journal-title":"Journal of Chongqing University"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2001.974915"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2001.974915"},{"key":"e_1_3_2_1_12_1","first-page":"343","article-title":"Enter Health Information Technology: Expanding Theories of the Doctor-Patient Relationship for the Twenty-First Century Health Care Delivery System{M}.{S.l.}","volume":"2011","author":"Wright E. R","unstructured":"Wright E. R . Enter Health Information Technology: Expanding Theories of the Doctor-Patient Relationship for the Twenty-First Century Health Care Delivery System{M}.{S.l.} : Springer New York , 2011 : 343 -- 359 . Wright E. R. Enter Health Information Technology: Expanding Theories of the Doctor-Patient Relationship for the Twenty-First Century Health Care Delivery System{M}.{S.l.}:Springer New York, 2011: 343--359.","journal-title":"Springer New York"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"e_1_3_2_1_14_1","volume-title":"IEEE International Symposium on Circuits and Systems {C}. {S.l.}: {s.n.}","author":"Dahl J. V.","unstructured":"Dahl J. V. , Koch K. C. , Kleinhans E. , Convolutional networks and applications in vision{A} . IEEE International Symposium on Circuits and Systems {C}. {S.l.}: {s.n.} , 2011:253--256. Dahl J. V., Koch K. C., Kleinhans E., et al. Convolutional networks and applications in vision{A}. IEEE International Symposium on Circuits and Systems {C}. {S.l.}: {s.n.}, 2011:253--256."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1962.sp006837"},{"key":"e_1_3_2_1_16_1","unstructured":"Jaderberg M. Simonyan K. Zisserman A. etal Spatial Transformer Networks{J}. 2015:2017--2025.   Jaderberg M. Simonyan K. Zisserman A. et al. Spatial Transformer Networks{J}. 2015:2017--2025."},{"key":"e_1_3_2_1_17_1","volume-title":"CoRR","author":"Worrall D. E.","year":"2016","unstructured":"Worrall D. E. , Garbin S. J. , Turmukhambetov D. , Harmonic Networks : Deep Translation and Rotation Equivariance{J} . CoRR , 2016 , abs\/1612.04642. http:\/\/arxiv.org\/abs\/1612.04642. Worrall D. E., Garbin S. J., Turmukhambetov D., et al. Harmonic Networks: Deep Translation and Rotation Equivariance{J}. CoRR, 2016, abs\/1612.04642. http:\/\/arxiv.org\/abs\/1612.04642."},{"key":"e_1_3_2_1_18_1","volume-title":"CoRR, 2018","author":"Ruderman A.","year":"1804","unstructured":"Ruderman A. , Rabinowitz N. C. , Morcos A. S. , Learned Deformation Stability in Convolutional Neural Networks{J} . CoRR, 2018 , abs\/ 1804 .04438. http:\/\/arxiv.org\/abs\/1804.04438. Ruderman A., Rabinowitz N. C., Morcos A. S., et al. Learned Deformation Stability in Convolutional Neural Networks{J}. CoRR, 2018, abs\/1804.04438. http:\/\/arxiv.org\/abs\/1804.04438."},{"key":"e_1_3_2_1_19_1","volume-title":"Rectified linear units improve restricted boltzmann machines{A}.International Conference on International Conference on Machine Learning{C}. {S.l.}:{s.n.}","author":"Nair V.","year":"2010","unstructured":"Nair V. , Hinton G. E. Rectified linear units improve restricted boltzmann machines{A}.International Conference on International Conference on Machine Learning{C}. {S.l.}:{s.n.} , 2010 :807--814. Nair V., Hinton G. E. Rectified linear units improve restricted boltzmann machines{A}.International Conference on International Conference on Machine Learning{C}. {S.l.}:{s.n.}, 2010:807--814."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.476112"},{"key":"e_1_3_2_1_22_1","volume-title":"Going deeper with convolutions{A}. {S.l.}: {s.n.}","author":"Szegedy C.","year":"2014","unstructured":"Szegedy C. , Liu W. , Jia Y. , Going deeper with convolutions{A}. {S.l.}: {s.n.} , 2014 :1--9. Szegedy C., Liu W., Jia Y., et al. Going deeper with convolutions{A}. {S.l.}: {s.n.}, 2014:1--9."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-016-9914-9"},{"key":"e_1_3_2_1_25_1","volume-title":"Densely Connected Convolutional Networks {J}","author":"Huang G.","year":"2016","unstructured":"Huang G. , Liu Z. , Maaten L. , Densely Connected Convolutional Networks {J} . 2016 . Huang G., Liu Z., Maaten L., et al. Densely Connected Convolutional Networks {J}. 2016."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Wang X. Peng Y. Lu L. etal ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases{A}. Computer Vision and Pattern Recognition {C}. {S.l.}: {s.n.} 2017:3462--3471.  Wang X. Peng Y. Lu L. et al. ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases{A}. Computer Vision and Pattern Recognition {C}. {S.l.}: {s.n.} 2017:3462--3471.","DOI":"10.1109\/CVPR.2017.369"},{"key":"e_1_3_2_1_27_1","volume-title":"CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning{J}","author":"Rajpurkar P.","year":"2017","unstructured":"Rajpurkar P. , Irvin J. , Zhu K. , CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning{J} . 2017 . Rajpurkar P., Irvin J., Zhu K., et al. CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning{J}. 2017."},{"key":"e_1_3_2_1_28_1","volume-title":"Information Processing in Medical Imaging: Conference{C}. {S.l.}: {s.n.}","author":"Yan Z.","unstructured":"Yan Z. , Zhan Y. , Peng Z. , Bodypart Recognition Using Multi-stage Deep Learning{A} . Information Processing in Medical Imaging: Conference{C}. {S.l.}: {s.n.} , 2015:449. Yan Z., Zhan Y., Peng Z., et al. Bodypart Recognition Using Multi-stage Deep Learning{A}. Information Processing in Medical Imaging: Conference{C}. {S.l.}: {s.n.}, 2015:449."},{"key":"e_1_3_2_1_29_1","volume-title":"IEEE International Symposium on Biomedical Imaging{C}. {S.l.}: {s.n.}","author":"Roth H. R.","unstructured":"Roth H. R. , Lee C. T. , Shin H. C. , Anatomy-specific classification of medical images using deep convolutional nets{A} . IEEE International Symposium on Biomedical Imaging{C}. {S.l.}: {s.n.} , 2015:101--104. Roth H. R., Lee C. T., Shin H. C., et al. Anatomy-specific classification of medical images using deep convolutional nets{A}. IEEE International Symposium on Biomedical Imaging{C}. {S.l.}: {s.n.}, 2015:101--104."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528120"},{"key":"e_1_3_2_1_31_1","volume-title":"CoRR","author":"Goodfellow I. J.","year":"2014","unstructured":"Goodfellow I. J. , Pouget-Abadie J. , Mirza M. , Generative Adversarial Networks {J} . CoRR , 2014 , abs\/1406.2661. http:\/\/arxiv.org\/abs\/1406.2661. Goodfellow I. J., Pouget-Abadie J., Mirza M., et al. Generative Adversarial Networks {J}. CoRR, 2014, abs\/1406.2661. http:\/\/arxiv.org\/abs\/1406.2661."},{"key":"e_1_3_2_1_32_1","volume-title":"Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment{C}..{S.l.}","author":"Hu Y.","year":"2017","unstructured":"Hu Y. , Gibson E. , Lee L.-L. , Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks {M} ., Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment{C}..{S.l.} : Springer , 2017 : 105--115. Hu Y., Gibson E., Lee L.-L., et al. Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks {M}., Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment{C}..{S.l.}: Springer, 2017:105--115."}],"event":{"name":"ICMLSC 2019: 2019 the 3rd International Conference on Machine Learning and Soft Computing","location":"Da Lat Viet Nam","acronym":"ICMLSC 2019"},"container-title":["Proceedings of the 3rd International Conference on Machine Learning and Soft Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3310986.3311010","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3310986.3311010","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T19:08:01Z","timestamp":1750273681000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3310986.3311010"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,25]]},"references-count":32,"alternative-id":["10.1145\/3310986.3311010","10.1145\/3310986"],"URL":"https:\/\/doi.org\/10.1145\/3310986.3311010","relation":{},"subject":[],"published":{"date-parts":[[2019,1,25]]},"assertion":[{"value":"2019-01-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}