{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T18:11:40Z","timestamp":1772993500036,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030466398","type":"print"},{"value":"9783030466404","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-46640-4_9","type":"book-chapter","created":{"date-parts":[[2020,5,18]],"date-time":"2020-05-18T23:24:36Z","timestamp":1589844276000},"page":"89-97","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Optimization with Soft Dice Can Lead to a Volumetric Bias"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7206-2671","authenticated-orcid":false,"given":"Jeroen","family":"Bertels","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Robben","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dirk","family":"Vandermeulen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul","family":"Suetens","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,19]]},"reference":[{"key":"9_CR1","unstructured":"NEXIS - Next gEneration X-ray Imaging System. https:\/\/www.nexis-project.eu"},{"key":"9_CR2","unstructured":"Ischemic Stroke Lesion Segmentation (ISLES) challenge (2017). http:\/\/www.isles-challenge.org\/ISLES2017\/"},{"key":"9_CR3","unstructured":"Ischemic Stroke Lesion Segmentation (ISLES) challenge (2018). http:\/\/www.isles-challenge.org\/ISLES2017\/"},{"key":"9_CR4","unstructured":"Multimodal Brain Tumor Segmentation (BRATS) challenge (2018). https:\/\/www.med.upenn.edu\/sbia\/brats2018.html"},{"issue":"March","key":"9_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2017.117","volume":"4","author":"S Bakas","year":"2017","unstructured":"Bakas, S., et al.: Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Sci. Data 4(March), 1\u201313 (2017). https:\/\/doi.org\/10.1038\/sdata.2017.117","journal-title":"Sci. Data"},{"key":"9_CR6","unstructured":"Bakas, S., et al.: Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (2018). http:\/\/arxiv.org\/abs\/1811.02629"},{"key":"9_CR7","doi-asserted-by":"crossref","unstructured":"Bertels, J., et al.: Optimizing the Dice score and Jaccard index for medical image segmentation: theory and practice. In: Medical Image Computing and Computer-Assisted Intervention (2019)","DOI":"10.1007\/978-3-030-32245-8_11"},{"issue":"2","key":"9_CR8","first-page":"49","volume":"35","author":"J De Tobel","year":"2017","unstructured":"De Tobel, J., Radesh, P., Vandermeulen, D., Thevissen, P.W.: An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study. J. Forensic Odonto-Stomatol. 35(2), 49\u201360 (2017)","journal-title":"J. Forensic Odonto-Stomatol."},{"key":"9_CR9","doi-asserted-by":"publisher","unstructured":"Drozdzal, M., Vorontsov, E., Chartrand, G., Kadoury, S., Pal, C.: Deep Learning and Data Labeling for Medical Applications. LNCS, vol. 10008, pp. 179\u2013187. Springer, Heidelberg (2016). https:\/\/doi.org\/10.1007\/978-3-319-46976-8","DOI":"10.1007\/978-3-319-46976-8"},{"key":"9_CR10","volume-title":"Deep Learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)"},{"issue":"10029","key":"9_CR11","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1016\/S0140-6736(16)00163-X","volume":"387","author":"M Goyal","year":"2016","unstructured":"Goyal, M., et al.: Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials. Lancet 387(10029), 1723\u20131731 (2016). https:\/\/doi.org\/10.1016\/S0140-6736(16)00163-X","journal-title":"Lancet"},{"key":"9_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-030-11726-9_21","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"F Isensee","year":"2019","unstructured":"Isensee, F., Kickingereder, P., Wick, W., Bendszus, M., Maier-Hein, K.H.: No new-net. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) BrainLes 2018. LNCS, vol. 11384, pp. 234\u2013244. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11726-9_21"},{"key":"9_CR13","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.media.2016.10.004","volume":"36","author":"K Kamnitsas","year":"2017","unstructured":"Kamnitsas, K., Ledig, C., Newcombe, V.F.J.: Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Med. Image Anal. 36, 61\u201378 (2017)","journal-title":"Med. Image Anal."},{"key":"9_CR14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694","author":"BH Menze","year":"2015","unstructured":"Menze, B.H., et al.: The multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Trans. Med. Imaging (2015). https:\/\/doi.org\/10.1109\/TMI.2014.2377694","journal-title":"IEEE Trans. Med. Imaging"},{"key":"9_CR15","doi-asserted-by":"publisher","unstructured":"Milletari, F., Navab, N., Ahmadi, S.A.: V-Net: fully convolutional neural networks for volumetric medical image segmentation. In: International Conference on 3D Vision, vol. 4, pp. 1\u201311 (2016). https:\/\/doi.org\/10.1109\/3DV.2016.79, http:\/\/arxiv.org\/abs\/1606.04797","DOI":"10.1109\/3DV.2016.79"},{"key":"9_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1007\/978-3-319-67558-9_28","volume-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","author":"CH Sudre","year":"2017","unstructured":"Sudre, C.H., Li, W., Vercauteren, T., Ourselin, S., Jorge Cardoso, M.: Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations. In: Cardoso, M.J., et al. (eds.) DLMIA\/ML-CDS -2017. LNCS, vol. 10553, pp. 240\u2013248. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67558-9_28"},{"key":"9_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-3264-1","volume-title":"The Nature of Statistical Learning Theory","author":"VN Vapnik","year":"1995","unstructured":"Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, Heidelberg (1995). https:\/\/doi.org\/10.1007\/978-1-4757-3264-1"},{"key":"9_CR18","doi-asserted-by":"publisher","unstructured":"Winzeck, S., et al.: ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI. Front. Neurol. 9(SEP) (2018). https:\/\/doi.org\/10.3389\/fneur.2018.00679","DOI":"10.3389\/fneur.2018.00679"}],"container-title":["Lecture Notes in Computer Science","Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-46640-4_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,18]],"date-time":"2025-05-18T22:03:34Z","timestamp":1747605814000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-46640-4_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030466398","9783030466404"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-46640-4_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"19 May 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BrainLes","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International MICCAI Brainlesion Workshop","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2019","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":"iwb2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.brainlesion-workshop.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}