{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T17:05:33Z","timestamp":1726247133455},"publisher-location":"Wiesbaden","reference-count":11,"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_66","type":"book-chapter","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T08:05:12Z","timestamp":1708329912000},"page":"232-236","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Addressing the Bias of the Dice Coefficient"],"prefix":"10.1007","author":[{"given":"Fenja","family":"Falta","sequence":"first","affiliation":[]},{"given":"Mattias P.","family":"Heinrich","sequence":"additional","affiliation":[]},{"given":"Marian","family":"Himstedt","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"key":"66_CR1","doi-asserted-by":"crossref","unstructured":"Reichl T, Luo X, Menzel M, Hautmann H, Mori K, Navab N. Hybrid electromagnetic and image-based tracking of endoscopes with guaranteed smooth output. \u0132CARS. 2013;8:955\u2013 65.","DOI":"10.1007\/s11548-013-0835-5"},{"key":"66_CR2","doi-asserted-by":"crossref","unstructured":"Falta F, Hansen L, Himstedt M, Heinrich MP. Learning an airway atlas from lung CT using semantic inter-patient deformable registration. Proc BVM. 2022:75\u201380.","DOI":"10.1007\/978-3-658-36932-3_15"},{"key":"66_CR3","doi-asserted-by":"crossref","unstructured":"Chauhan NS, Sood D, Takkar P, Dhadwal DS, Kapila R. Quantitative assessment of airway and parenchymal components of chronic obstructive pulmonary disease using thin-section helical computed tomography. Pol J Radiol. 2019;84:54\u201360.","DOI":"10.5114\/pjr.2019.82737"},{"key":"66_CR4","doi-asserted-by":"crossref","unstructured":"Zhang M, Wu Y, Zhang H, Qin Y, Zheng H, Tang W et al. Multi-site, multi-domain airway tree modeling. Med Image Anal. 2023;90:102957.","DOI":"10.1016\/j.media.2023.102957"},{"key":"66_CR5","doi-asserted-by":"crossref","unstructured":"Isensee F, Jaeger PF, Kohl SA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.Nat Methods. 2021;(2):203\u2013 11.","DOI":"10.1038\/s41592-020-01008-z"},{"key":"66_CR6","doi-asserted-by":"crossref","unstructured":"Tan Z, Feng J, Zhou J. SGNet: structure-aware graph-based network for airway semantic segmentation. Proc MICCAI. 2021:153\u201363.","DOI":"10.1007\/978-3-030-87193-2_15"},{"key":"66_CR7","unstructured":"Paetzold JC, Shit S, Ezhov I, Tetteh G, Ert\u00fcrk A, Munich HZ et al. clDice\u2014A novel connectivity-preserving loss function for vessel segmentation. Medical Imaging Meets NeurIPS 2019 Workshop. 2019."},{"key":"66_CR8","doi-asserted-by":"crossref","unstructured":"Mishra D, Chaudhury S, Sarkar M, Soin AS. Ultrasound image segmentation: a deeply supervised network with attention to boundaries. IEEE Trans Biomed Eng. 2018;66(6):1637\u2013 48.","DOI":"10.1109\/TBME.2018.2877577"},{"key":"66_CR9","unstructured":"Eisenmann M, Reinke A, Weru V, Tizabi MD, Isensee F, Adler TJ et al. Why is the winner the best? Proc IEEE CVPR. 2023:19955\u201366."},{"key":"66_CR10","doi-asserted-by":"crossref","unstructured":"Armato III SG, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP et al. The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys. 2011;38(2):915\u201331.","DOI":"10.1118\/1.3528204"},{"key":"66_CR11","doi-asserted-by":"crossref","unstructured":"Wasserthal J, Breit HC, Meyer MT, Pradella M, Hinck D, Sauter AWet al. Totalsegmentator: robust segmentation of 104 anatomic structures in ct images. Radiol Artif Intell. 2023;5(5).","DOI":"10.1148\/ryai.230024"}],"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_66","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T08:07:06Z","timestamp":1708330026000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-658-44037-4_66"}},"subtitle":["Semantic Segmentation of Peripheral Airways in Lung CT"],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783658440367","9783658440374"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-658-44037-4_66","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"}}]}}