{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T00:29:58Z","timestamp":1776040198935,"version":"3.50.1"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030009458","type":"print"},{"value":"9783030009465","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-00946-5_8","type":"book-chapter","created":{"date-parts":[[2018,9,11]],"date-time":"2018-09-11T09:00:03Z","timestamp":1536656403000},"page":"73-80","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Domain Adaptation for Deviating Acquisition Protocols in CNN-Based Lesion Classification on Diffusion-Weighted MR Images"],"prefix":"10.1007","author":[{"given":"Jennifer","family":"Kamphenkel","sequence":"first","affiliation":[]},{"given":"Paul F.","family":"J\u00e4ger","sequence":"additional","affiliation":[]},{"given":"Sebastian","family":"Bickelhaupt","sequence":"additional","affiliation":[]},{"given":"Frederik Bernd","family":"Laun","sequence":"additional","affiliation":[]},{"given":"Wolfgang","family":"Lederer","sequence":"additional","affiliation":[]},{"given":"Heidi","family":"Daniel","sequence":"additional","affiliation":[]},{"given":"Tristan Anselm","family":"Kuder","sequence":"additional","affiliation":[]},{"given":"Stefan","family":"Delorme","sequence":"additional","affiliation":[]},{"given":"Heinz-Peter","family":"Schlemmer","sequence":"additional","affiliation":[]},{"given":"Franziska","family":"K\u00f6nig","sequence":"additional","affiliation":[]},{"given":"Klaus H.","family":"Maier-Hein","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,12]]},"reference":[{"issue":"24","key":"8_CR1","doi-asserted-by":"publisher","first-page":"2353","DOI":"10.1056\/NEJMsr1504363","volume":"372","author":"B Lauby-Secretan","year":"2015","unstructured":"Lauby-Secretan, B.: Breast-cancer screening-viewpoint of the IARC working group. New Engl. J. Med. 372(24), 2353\u20132358 (2015)","journal-title":"New Engl. J. Med."},{"issue":"11","key":"8_CR2","doi-asserted-by":"publisher","first-page":"e113240","DOI":"10.1371\/journal.pone.0113240","volume":"9","author":"D Wu","year":"2014","unstructured":"Wu, D.: Characterization of breast tumors using diffusion kurtosis imaging (DKI). PloS One 9(11), e113240 (2014)","journal-title":"PloS One"},{"issue":"1","key":"8_CR3","doi-asserted-by":"publisher","first-page":"4655","DOI":"10.1148\/radiol.15141625","volume":"277","author":"K Sun","year":"2015","unstructured":"Sun, K.: Breast cancer: diffusion kurtosis MR imaging diagnostic accuracy and correlation with clinical-pathologic factors. Radiology 277(1), 4655 (2015)","journal-title":"Radiology"},{"key":"8_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1007\/978-3-319-66182-7_76","volume-title":"Medical Image Computing and Computer Assisted Intervention - MICCAI 2017","author":"PF J\u00e4ger","year":"2017","unstructured":"J\u00e4ger, P.F., et al.: Revealing hidden potentials of the q-Space signal in breast cancer. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10433, pp. 664\u2013671. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66182-7_76"},{"key":"8_CR5","unstructured":"J\u00e4ger, P.F., et al.: Complementary value of end-to-end deep learning and radiomics in breast cancer classification on diffusion-weighted MR. In: ISMRM (2017)"},{"key":"8_CR6","first-page":"74","volume":"8","author":"M Ghodrati","year":"2014","unstructured":"Ghodrati, M., et al.: Feedforward object-vision models only tolerate small image variations compared to human. Front. Comput. Neurosci. 8, 74 (2014)","journal-title":"Front. Comput. Neurosci."},{"key":"8_CR7","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1007\/978-3-319-66179-7_48","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2212 MICCAI 2017","author":"Dong Nie","year":"2017","unstructured":"Nie, D., et al.: Medical image synthesis with context-aware generative adversarial networks. In: MICCAI, pp. 417\u2013425 (2017)"},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Isola, P., et al.: Image-to-image translation with conditional adversarial networks. In: IEEE Conference on CVPR, p. 5967 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"issue":"2","key":"8_CR9","first-page":"1278","volume":"32","author":"D Rezende","year":"2014","unstructured":"Rezende, D., Jimenez, S.M., Wierstra, D.: Stochastic backpropagation and approximate inference in deep generative models. ICML 32(2), 1278\u20131286 (2014)","journal-title":"ICML"},{"key":"8_CR10","unstructured":"Kingma, D., Welling, M.: Auto-encoding variational bayes. In: ICLR (2014)"},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Havaei, M., et al.: HeMIS: Hetero-modal image segmentation. In: MICCAI, pp. 469\u2013477 (2016)","DOI":"10.1007\/978-3-319-46723-8_54"},{"issue":"2","key":"8_CR12","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.ejrad.2006.08.033","volume":"61","author":"AC Balleyguier","year":"2007","unstructured":"Balleyguier, A.C., et al.: $$\\text{ BI-RADS }^{\\rm TM}$$ classification in mammography. Eur. J. Radiol. 61(2), 192\u2013194 (2007)","journal-title":"Eur. J. Radiol."},{"issue":"6","key":"8_CR13","doi-asserted-by":"publisher","first-page":"1432","DOI":"10.1002\/mrm.20508","volume":"53","author":"JH Jensen","year":"2005","unstructured":"Jensen, J.H., et al.: Diffusional kurtosis imaging: the quantification of nongaussian water diffusion by means of magnetic resonance imaging. Magn. Reson. Med. 53(6), 1432\u20131440 (2005)","journal-title":"Magn. Reson. Med."},{"issue":"3","key":"8_CR14","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1148\/radiol.2017170273","volume":"287","author":"S Bickelhaupt","year":"2018","unstructured":"Bickelhaupt, S., et al.: Radiomics based on adapted diffusion kurtosis imaging helps to clarify most mammographic findings suspicious for cancer. Radiology 287(3), 761\u2013770 (2018)","journal-title":"Radiology"},{"issue":"8","key":"8_CR15","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1097\/RLI.0000000000000155","volume":"50","author":"MC Roethke","year":"2015","unstructured":"Roethke, M.C., et al.: Evaluation of diffusion kurtosis imaging versus standard diffusion imaging for detection and grading of peripheral zone prostate cancer. Invest. Radiol. 50(8), 483\u2013489 (2015)","journal-title":"Invest. Radiol."}],"container-title":["Lecture Notes in Computer Science","Image Analysis for Moving Organ, Breast, and Thoracic Images"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00946-5_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T00:04:52Z","timestamp":1694390692000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00946-5_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030009458","9783030009465"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00946-5_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"12 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Breast Image Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bia2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cs.adelaide.edu.au\/~bia2018\/","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":"CMT3","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"18","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":"9","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":"50% - 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":"3.1","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":"n\/a","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)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}