{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,4]],"date-time":"2026-01-04T08:07:56Z","timestamp":1767514076959,"version":"3.40.5"},"publisher-location":"Wiesbaden","reference-count":13,"publisher":"Springer Fachmedien Wiesbaden","isbn-type":[{"type":"print","value":"9783658440367"},{"type":"electronic","value":"9783658440374"}],"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_91","type":"book-chapter","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T08:05:12Z","timestamp":1708329912000},"page":"356-361","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Accelerating Artificial Intelligence-based Whole Slide Image Analysis with an Optimized Preprocessing Pipeline"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8906-7644","authenticated-orcid":false,"given":"Fabian","family":"H\u00f6rst","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sajad H.","family":"Schaheer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5929-0271","authenticated-orcid":false,"given":"Giulia","family":"Baldini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5204-4713","authenticated-orcid":false,"given":"Fin H.","family":"Bahnsen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5225-1982","authenticated-orcid":false,"given":"Jan","family":"Egger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jens","family":"Kleesiek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"key":"91_CR1","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":"91_CR2","unstructured":"Dusenberry M, Hu F, Jindal N, Eriksson D. Deep-histopath. https : \/ \/ github . com \/ CODAIT\/deep-histopath. 2019."},{"key":"91_CR3","doi-asserted-by":"crossref","unstructured":"Levy JJ, Salas LA, Christensen BC, Sriharan A, Vaickus LJ. PathFlowAI: A high-throughput workflow for preprocessing, deep learning and interpretation in digital pathology. Pac Symp Biocomput. 2020;25:403\u201314.","DOI":"10.1101\/19003897"},{"key":"91_CR4","doi-asserted-by":"crossref","unstructured":"Berman AG, Orchard WR, Gehrung M, Markowetz F. SliDL: a toolbox for processing whole-slide images in deep learning. PLoS One. 2023;18(8):e0289499.","DOI":"10.1371\/journal.pone.0289499"},{"key":"91_CR5","unstructured":"Neuner C, Jabari S, Vilz S. WSI processing pipeline. https : \/ \/ github . com \/ FAU - DLM\/wsi_processing_pipeline. 2023."},{"key":"91_CR6","doi-asserted-by":"crossref","unstructured":"Marcolini A, Bussola N, Arbitrio E, Amgad M, Jurman G, Furlanello C. histolab: a Python library for reproducible digital pathology preprocessing with automated testing. SoftwareX. 2022;20(101237).","DOI":"10.1016\/j.softx.2022.101237"},{"key":"91_CR7","doi-asserted-by":"crossref","unstructured":"Pocock J, Graham S, Vu QD, Jahanifar M, Deshpande S, Hadjigeorghiou G et al. TIAToolbox as an end-to-end library for advanced tissue image analytics. Commun Med. 2022;2(1).","DOI":"10.1038\/s43856-022-00186-5"},{"key":"91_CR8","doi-asserted-by":"crossref","unstructured":"Goode A, Gilbert B, Harkes J, Jukic D, Satyanarayanan M. OpenSlide: A vendor-neutral software foundation for digital pathology. J Pathol Inform. 2013;4(1):27.","DOI":"10.4103\/2153-3539.119005"},{"key":"91_CR9","unstructured":"Bradski G. The opencv library. Dr. Dobb\u2019s Journal of Software Tools. 2000."},{"key":"91_CR10","doi-asserted-by":"crossref","unstructured":"van der Walt S, Sch\u00f6nberger JL, Nunez-Iglesias J, Boulogne F, Warner JD, Yager N et al. scikit-image: image processing in python. PeerJ. 2014;2:e453.","DOI":"10.7717\/peerj.453"},{"key":"91_CR11","doi-asserted-by":"crossref","unstructured":"Otsu N. A Threshold Selection Method from Gray-Level Histograms. IEEE Trans Syst Man Cybern. 1979;9(1):62\u20136.","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"91_CR12","doi-asserted-by":"crossref","unstructured":"Macenko M, Niethammer M, Marron JS, Borland D,Woosley JT, Guan X et al. A method for normalizing histology slides for quantitative analysis. Proc IEEE Int Symp Biomed Imaging. 2009:1107\u201310.","DOI":"10.1109\/ISBI.2009.5193250"},{"key":"91_CR13","unstructured":"NVIDIA. cuCIM. https:\/\/github.com\/rapidsai\/cucim. 2023."}],"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_91","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T08:08:56Z","timestamp":1708330136000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-658-44037-4_91"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783658440367","9783658440374"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-658-44037-4_91","relation":{},"ISSN":["1431-472X","2628-8958"],"issn-type":[{"type":"print","value":"1431-472X"},{"type":"electronic","value":"2628-8958"}],"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"}}]}}