{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:39:37Z","timestamp":1769906377055,"version":"3.49.0"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030667849","type":"print"},{"value":"9783030667856","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","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":[[2021]]},"DOI":"10.1007\/978-3-030-66785-6_16","type":"book-chapter","created":{"date-parts":[[2021,1,23]],"date-time":"2021-01-23T15:03:07Z","timestamp":1611414187000},"page":"137-147","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["The Generation of Virtual Immunohistochemical Staining Images Based on an Improved Cycle-GAN"],"prefix":"10.1007","author":[{"given":"Shuting","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiping","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tian","family":"Guan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yonghong","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,24]]},"reference":[{"issue":"8","key":"16_CR1","doi-asserted-by":"publisher","first-page":"1057","DOI":"10.1016\/j.humpath.2009.04.006","volume":"40","author":"RS Weinstein","year":"2009","unstructured":"Weinstein, R.S., et al.: Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future. Human Pathol. 40(8), 1057\u20131069 (2009)","journal-title":"Human Pathol."},{"issue":"4","key":"16_CR2","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1177\/1066896907302124","volume":"15","author":"CT Soares","year":"2007","unstructured":"Soares, C.T., Frederigue-Junior, U., de Luca, L.A.: Anatomopathological analysis of sentinel and nonsentinel lymph nodes in breast cancer: hematoxylin-eosin versus immunohistochemistry. Int. J. Surg. Pathol. 15(4), 358\u2013368 (2007)","journal-title":"Int. J. Surg. Pathol."},{"issue":"1","key":"16_CR3","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1023\/A:1021727608133","volume":"48","author":"RA Sheikh","year":"2003","unstructured":"Sheikh, R.A., et al.: Correlation of Ki-67, p53, and Adnab-9 immunohistochemical staining and ploidy with clinical and histopathologic features of severely dysplastic colorectal adenomas. Dig. Dis. Sci. 48(1), 223\u2013229 (2003). https:\/\/doi.org\/10.1023\/A:1021727608133","journal-title":"Dig. Dis. Sci."},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Wang, Y., Sun, L.L., Jin, Q.: Enhanced diagnosis of pneumothorax with an improved real-time augmentation for imbalanced chest x-rays data based on DCNN. In: IEEE\/ACM Transactions on Computational Biology and Bioinformatics (2019)","DOI":"10.1109\/TCBB.2019.2911947"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"133111","DOI":"10.1109\/ACCESS.2019.2941154","volume":"7","author":"Z Tang","year":"2019","unstructured":"Tang, Z., et al.: An augmentation strategy for medical image processing based on statistical shape model and 3D thin plate spline for deep learning. IEEE Access 7, 133111\u2013133121 (2019)","journal-title":"IEEE Access"},{"issue":"7","key":"16_CR6","doi-asserted-by":"publisher","first-page":"075019","DOI":"10.1088\/1361-6560\/ab0606","volume":"64","author":"J Yang","year":"2019","unstructured":"Yang, J., et al.: Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain 18F-FDG PET. Phys. Med. Biol. 64(7), 075019 (2019)","journal-title":"Phys. Med. Biol."},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.ejmp.2018.09.005","volume":"54","author":"Z Tang","year":"2018","unstructured":"Tang, Z., Wang, M., Song, Z.: Rotationally resliced 3D prostate segmentation of MR images using Bhattacharyya similarity and active band theory. Physica Med. 54, 56\u201365 (2018)","journal-title":"Physica Med."},{"key":"16_CR8","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.neucom.2019.10.092","volume":"380","author":"B Zhang","year":"2020","unstructured":"Zhang, B., et al.: Cerebrovascular segmentation from TOF-MRA using model-and data-driven method via sparse labels. Neurocomputing 380, 162\u2013179 (2020)","journal-title":"Neurocomputing"},{"key":"16_CR9","first-page":"2672","volume":"27","author":"I Goodfellow","year":"2014","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. Adv. Neural. Inf. Process. Syst. 27, 2672\u20132680 (2014)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"16_CR10","unstructured":"Mirza, M., Osindero, S.: Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784 (2014)"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Isola, P., et al.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"16_CR12","doi-asserted-by":"crossref","unstructured":"Zhu, J.-Y., et al.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision. (2017)","DOI":"10.1109\/ICCV.2017.244"},{"issue":"4","key":"16_CR13","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"16_CR14","unstructured":"Liu, L., et al.: Understanding the Difficulty of Training Transformers. arXiv preprint arXiv:2004.08249 (2020)"},{"key":"16_CR15","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"16_CR16","unstructured":"Wang, Z., Simoncelli, E.P., Bovik, A.C.: Multiscale structural similarity for image quality assessment. In: The Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, vol. 2. IEEE (2003)"},{"key":"16_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1007\/978-3-642-24712-5_9","volume-title":"Communications and Multimedia Security","author":"L Weng","year":"2011","unstructured":"Weng, L., Preneel, B.: A secure perceptual hash algorithm for image content authentication. In: De Decker, B., Lapon, J., Naessens, V., Uhl, A. (eds.) CMS 2011. LNCS, vol. 7025, pp. 108\u2013121. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-24712-5_9"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Machine Learning and Intelligent Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-66785-6_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T12:35:57Z","timestamp":1619267757000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-66785-6_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030667849","9783030667856"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-66785-6_16","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"value":"1867-8211","type":"print"},{"value":"1867-822X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"24 January 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MLICOM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning and Intelligent Communications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mlicom2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mlicom.eai-conferences.org\/2020\/","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":"Confyplus.eai.eu","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"133","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":"55","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":"41% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was held virtually due to COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}