{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T23:14:14Z","timestamp":1782861254626,"version":"3.54.5"},"publisher-location":"Wiesbaden","reference-count":7,"publisher":"Springer Fachmedien Wiesbaden","isbn-type":[{"value":"9783658440367","type":"print"},{"value":"9783658440374","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-658-44037-4_41","type":"book-chapter","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T08:05:12Z","timestamp":1708329912000},"page":"137-142","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Assessment of Scanner Domain Shifts in Deep Multiple Instance Learning"],"prefix":"10.1007","author":[{"given":"Jonathan","family":"Ganz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7629-0356","authenticated-orcid":false,"given":"Chlo\u00e9","family":"Puget","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0335-1194","authenticated-orcid":false,"given":"Jonas","family":"Ammeling","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4429-9529","authenticated-orcid":false,"given":"Eda","family":"Parlak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matti","family":"Kiupel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2402-9997","authenticated-orcid":false,"given":"Christof A.","family":"Bertram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7600-5869","authenticated-orcid":false,"given":"Katharina","family":"Breininger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6308-0568","authenticated-orcid":false,"given":"Robert","family":"Klopfleisch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5294-5247","authenticated-orcid":false,"given":"Marc","family":"Aubreville","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Aubreville M, Stathonikos N, Bertram CA, Klopfleisch R, Ter Hoeve N, Ciompi F et al. Mitosis domain generalization in histopathology images: the MIDOG challenge. Med Image Anal. 2023;84:102699.","DOI":"10.1016\/j.media.2022.102699"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Yagi Y. Color standardization and optimization in whole slide imaging. Diagnostic pathology. Vol. 6. Springer. 2011:1\u201312.","DOI":"10.1186\/1746-1596-6-S1-S15"},{"key":"41_CR3","unstructured":"Ilse M, Tomczak J, Welling M. Attention-based deep multiple instance learning. ICML. PMLR. 2018:2127\u201336."},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Lu MY, Williamson DF, Chen TY, Chen RJ, Barbieri M, Mahmood F. Data-efficient and weakly supervised computational pathology on whole-slide images. Nat Biomed Eng. 2021;5(6):555\u201370.","DOI":"10.1038\/s41551-020-00682-w"},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Puget C, Ganz J, Ostermaier J, Konrad T, Parlak E, Bertram CA et al. Deep Learning model predicts the c-Kit-11 mutational status of canine cutaneous mast cell tumors by HE stained histological slides. 2024.","DOI":"10.1016\/j.jcpa.2024.03.054"},{"key":"41_CR6","doi-asserted-by":"crossref","unstructured":"Webster JD, Yuzbasiyan-Gurkan V, Kaneene JB, Miller R, Resau JH, Kiupel M. The role of c-KIT in tumorigenesis: evaluation in canine cutaneous mast cell tumors. Neoplasia. 2006;8(2):104\u201311.","DOI":"10.1593\/neo.05622"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Zaffar I, Jaume G, Rajpoot N, Mahmood F. Embedding space augmentation for weakly supervised learning in whole-slide images. ISBI. IEEE. 2023:1\u20134.","DOI":"10.1109\/ISBI53787.2023.10230723"}],"container-title":["Informatik aktuell","Bildverarbeitung f\u00fcr die Medizin 2024"],"original-title":[],"language":"de","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-658-44037-4_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T20:10:59Z","timestamp":1731355859000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-658-44037-4_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783658440367","9783658440374"],"references-count":7,"URL":"https:\/\/doi.org\/10.1007\/978-3-658-44037-4_41","relation":{},"ISSN":["1431-472X","2628-8958"],"issn-type":[{"value":"1431-472X","type":"print"},{"value":"2628-8958","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"20 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BVM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"BVM Workshop","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Erlangen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Deutschland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 March 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 March 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bvm2024a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.bvm-workshop.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}