{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:21:46Z","timestamp":1758273706242},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030393427"},{"type":"electronic","value":"9783030393434"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-39343-4_19","type":"book-chapter","created":{"date-parts":[[2020,1,23]],"date-time":"2020-01-23T11:03:29Z","timestamp":1579777409000},"page":"220-227","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deep Vectorization Convolutional Neural Networks for Denoising in Mammogram Using Enhanced Image"],"prefix":"10.1007","author":[{"given":"Varakorn","family":"Kidsumran","sequence":"first","affiliation":[]},{"given":"Yalin","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,1,24]]},"reference":[{"key":"19_CR1","unstructured":"WHO Homepage. http:\/\/www.who.int\/cancer\/detection\/breastcancer\/en\/index1.html . Accessed 27 June 2018"},{"key":"19_CR2","unstructured":"Diagnosisdelayed Homepage. http:\/\/www.diagnosisdelayed.com\/breast-cancer-misdiagnosis ,. Accessed 27 June 2018"},{"issue":"3","key":"19_CR3","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1109\/TMI.2003.809632","volume":"22","author":"P Heinlein","year":"2003","unstructured":"Heinlein, P., Drexl, J., Schneider, W.: Integrated wavelets for enhancement of micro calcifications in digital mammography. IEEE Trans. Med. Imaging 22(3), 402\u2013413 (2003)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"19_CR4","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1142\/S0219691310003754","volume":"8","author":"A Mencattini","year":"2010","unstructured":"Mencattini, A., Rabottino, G., Salmeri, M., Sciunzi, B., Lojacono, R.: Denoising and enhancement of mammmographic images under the assumption of heteroscedastic additive noise by an optimal subband thresholding. Int. J. Wavelets Multiresolut. Inf. Process. 8, 713\u2013741 (2010)","journal-title":"Int. J. Wavelets Multiresolut. Inf. Process."},{"key":"19_CR5","first-page":"180","volume":"1","author":"MS Elsherif","year":"2001","unstructured":"Elsherif, M.S., Elsayad, A.: Wavelet packet denoising for mammogram enhancement. Circuits Syst. 1, 180\u2013183 (2001)","journal-title":"Circuits Syst."},{"issue":"4","key":"19_CR6","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1007\/s10278-012-9555-6","volume":"26","author":"Eri Matsuyama","year":"2012","unstructured":"Matsuyama, E., Tsai, D.Y., Lee, Y., Tsurumaki, M.: A modified undecimated discrete wavelet transform based approach to mammographic image denoising. J. Digit. Imaging 26, 748\u2013758 (2013)","journal-title":"Journal of Digital Imaging"},{"issue":"2","key":"19_CR7","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1109\/TIP.2006.887733","volume":"16","author":"JL Starck","year":"2007","unstructured":"Starck, J.L., Fadili, J., Murtagh, F.: The undecimated wavelet decomposition and its reconstruction. IEEE Trans. Image Process. 16(2), 297\u2013309 (2007)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR8","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1137\/040616024","volume":"4","author":"A Buades","year":"2005","unstructured":"Buades, A., Coll, B., Morel, J.M.: A review of image denoising algorithms, with a new one. Multiscale Model. Simul. 4, 490\u2013530 (2005)","journal-title":"Multiscale Model. Simul."},{"key":"19_CR9","doi-asserted-by":"publisher","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Trans. Image Process. 16, 2080\u20132095 (2007)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR10","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1007\/s10851-016-0647-7","volume":"56","author":"EM Eksioglu","year":"2016","unstructured":"Eksioglu, E.M.: Decoupled algorithm for MRI reconstruction using nonlocal block matching model: BM3D-MRI. J. Math. Imaging Vis. 56, 430\u2013440 (2016)","journal-title":"J. Math. Imaging Vis."},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Gu, S., Zhang, L., Zuo, W., Feng, X.: Weighted nuclear norm minimization with application to image denoising. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2862\u20132869 (2014)","DOI":"10.1109\/CVPR.2014.366"},{"key":"19_CR12","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1109\/TIP.2007.891064","volume":"16","author":"F Luisier","year":"2007","unstructured":"Luisier, F., Blu, T., Unser, M.: A new SURE approach to image denoising: interscale orthonormal wavelet thresholding. IEEE Trans. Image Process. 16, 593\u2013606 (2007)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR13","doi-asserted-by":"publisher","first-page":"1532","DOI":"10.1109\/83.862633","volume":"9","author":"SG Chang","year":"2000","unstructured":"Chang, S.G., Yu, B., Vetterli, M.: Adaptive wavelet thresholding for image denoising and compression. IEEE Trans. Image Process. 9, 1532\u20131546 (2000)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR14","doi-asserted-by":"publisher","first-page":"1338","DOI":"10.1109\/TIP.2003.818640","volume":"12","author":"J Portilla","year":"2003","unstructured":"Portilla, J., Strela, V., Wainwright, M.J., Simoncelli, E.P.: Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Trans. Image Process. 12, 1338\u20131351 (2003)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR15","doi-asserted-by":"publisher","first-page":"2778","DOI":"10.1109\/TIP.2007.906002","volume":"16","author":"T Blu","year":"2007","unstructured":"Blu, T., Luisier, F.: The SURE-LET approach to image denoising. IEEE Trans. Image Process. 16, 2778\u20132786 (2007)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR16","unstructured":"Matsuyama, E.: SURE-LET image denoising with directional LOTS. In: Picture Coding Symposium, pp. 232\u2013239 (2012)"},{"key":"19_CR17","unstructured":"Wang, J., Wang, Y., Li, Y., Liu, J.: Improved median filtering denoising algorithm and analysis. In: International Conference on Information Science and Control Engineering (IET) (2012)"},{"key":"19_CR18","doi-asserted-by":"crossref","unstructured":"Bhateja, V., Rastogi, K., Verma, A., Malhotra, C.: A non-iterative adaptive median filter for image denoising. In: International Conference on Signal Processing and Integrated Networks (SPIN), pp. 113\u2013118 (2014)","DOI":"10.1109\/SPIN.2014.6776932"},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Wu, S., Chen, H., Xu, X., Long, H., Jiang, W., Xu, D.: An improved median filter algorithm based on VC in image denoising. In: 10th International Conference on Computational Intelligence and Security (CIS), pp. 193\u2013196 (2014)","DOI":"10.1109\/CIS.2014.91"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, X., Cheng, S., Ding, H., Wu, H., Gong, N., Cheng, R.: Ultrasound medical image denoising based on multi-direction median filter. In: 8th International Conference on Information Technology in Medicine and Education (ITME), pp. 835\u2013839 (2016)","DOI":"10.1109\/ITME.2016.0194"},{"key":"19_CR21","unstructured":"Burger, H.C., Schuler, C.J., Harmeling, S.: Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds. arXiv:1211.1544 (2012)"},{"key":"19_CR22","unstructured":"Burger, H.C., Schuler, C.J., Harmeling, S.: Image denoising with multi-layer perceptrons, part 2: training trade-offs and analysis of their mechanisms. arXiv:1211.1552 . (2012)"},{"key":"19_CR23","unstructured":"Jain, V., Seung, S.: Natural image denoising with convolutional networks. In: Advances Neural Information Processing Systems, pp. 769\u2013776 (2009)"},{"key":"19_CR24","unstructured":"Xie, J., Xu, L., Chen, E.: Image denoising and inpainting with deep neural networks. In: Advances Neural Information Processing Systems, pp. 341\u2013349 (2012)"},{"key":"19_CR25","unstructured":"Agostinelli, F., Anderson, M.R., Lee, H.: Adaptive multi-column deep neural networks with application to robust image denoising. In: Advances in Neural Information Processing Systems, vol. 26, pp. 1493\u20131501 (2013)"},{"key":"19_CR26","doi-asserted-by":"crossref","unstructured":"Gondara, L.: Medical image denoising using convolutional denoising autoencoders. In: IEEE 16th International Conference on Data Mining Workshops (ICDMW), pp. 241\u2013246 (2016)","DOI":"10.1109\/ICDMW.2016.0041"},{"key":"19_CR27","doi-asserted-by":"crossref","unstructured":"Ren, J., Xu, L.: On vectorization of deep convolutional neural networks for vision tasks. In: AAAI, pp. 1840\u20131846 (2015)","DOI":"10.1609\/aaai.v29i1.9488"},{"key":"19_CR28","unstructured":"Suckling, J., et al.: The mammographic image analysis society digital mammogram exerpta media. In: International Congress Sersis, vol. 1069, pp. 375\u2013378 (1994)"}],"container-title":["Communications in Computer and Information Science","Medical Image Understanding and Analysis"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-39343-4_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T15:22:19Z","timestamp":1665588139000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-39343-4_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030393427","9783030393434"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-39343-4_19","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"24 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MIUA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Annual Conference on Medical Image Understanding and Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Liverpool","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miua2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/miua2019.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"ocs","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"70","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"61% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}