{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T17:24:32Z","timestamp":1785518672869,"version":"3.56.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030117221","type":"print"},{"value":"9783030117238","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-11723-8_11","type":"book-chapter","created":{"date-parts":[[2019,1,25]],"date-time":"2019-01-25T13:47:41Z","timestamp":1548424061000},"page":"115-122","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Segmentation of Post-operative Glioblastoma in MRI by U-Net with Patient-Specific Interactive Refinement"],"prefix":"10.1007","author":[{"given":"Ashis Kumar","family":"Dhara","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kalyan Ram","family":"Ayyalasomayajula","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erik","family":"Arvids","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Markus","family":"Fahlstr\u00f6m","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johan","family":"Wikstr\u00f6m","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elna-Marie","family":"Larsson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robin","family":"Strand","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,1,26]]},"reference":[{"issue":"suppl 4","key":"11_CR1","doi-asserted-by":"publisher","first-page":"iv1","DOI":"10.1093\/neuonc\/nov189","volume":"17","author":"Quinn T. Ostrom","year":"2015","unstructured":"Ostrom, Q.T., et al.: CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008-2012. Neuro-oncology 17(Suppl. 4) (2015)","journal-title":"Neuro-Oncology"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Haider, S.A., et al.: Single-click, semi-automatic lung nodule contouring using hierarchical conditional random fields. In: 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), pp. 1139\u20131142. IEEE (2015)","DOI":"10.1109\/ISBI.2015.7164073"},{"issue":"3","key":"11_CR3","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1109\/83.661186","volume":"7","author":"C Xu","year":"1998","unstructured":"Xu, C., Prince, J.L.: Snakes, shapes, and gradient vector flow. IEEE Trans. Image Process. 7(3), 359\u2013369 (1998)","journal-title":"IEEE Trans. Image Process."},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Rother, C., Kolmogorov, V., Blake, A.: GrabCut: interactive foreground extraction using iterated graph cuts. In: ACM Transactions on Graphics (TOG), vol. 23, pp. 309\u2013314. ACM (2004)","DOI":"10.1145\/1015706.1015720"},{"key":"11_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/978-3-540-85988-8_43","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2008","author":"C-H Lee","year":"2008","unstructured":"Lee, C.-H., Wang, S., Murtha, A., Brown, M.R.G., Greiner, R.: Segmenting brain tumors using pseudo\u2013conditional random fields. In: Metaxas, D., Axel, L., Fichtinger, G., Sz\u00e9kely, G. (eds.) MICCAI 2008. LNCS, vol. 5241, pp. 359\u2013366. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-85988-8_43"},{"issue":"2","key":"11_CR6","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/s12021-014-9245-2","volume":"13","author":"NJ Tustison","year":"2015","unstructured":"Tustison, N.J., et al.: Optimal symmetric multimodal templates and concatenated random forests for supervised brain tumor segmentation (simplified) with ANTsR. Neuroinformatics 13(2), 209\u2013225 (2015)","journal-title":"Neuroinformatics"},{"issue":"10","key":"11_CR7","doi-asserted-by":"publisher","first-page":"1993","DOI":"10.1109\/TMI.2014.2377694","volume":"34","author":"BH Menze","year":"2015","unstructured":"Menze, B.H., et al.: The multimodal brain tumor image segmentation benchmark (BRATS). IEEE Trans. Med. Imaging 34(10), 1993\u20132024 (2015)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"11_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1007\/978-3-319-19665-7_17","volume-title":"Image Analysis","author":"M Lyksborg","year":"2015","unstructured":"Lyksborg, M., Puonti, O., Agn, M., Larsen, R.: An ensemble of 2D convolutional neural networks for tumor segmentation. In: Paulsen, R.R., Pedersen, K.S. (eds.) SCIA 2015. LNCS, vol. 9127, pp. 201\u2013211. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-19665-7_17"},{"key":"11_CR9","unstructured":"Dvorak, P., Menze, B.: Structured prediction with convolutional neural networks for multimodal brain tumor segmentation. In: Proceedings of the Multimodal Brain Tumor Image Segmentation Challenge, pp. 13\u201324 (2015)"},{"key":"11_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"2","key":"11_CR11","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1016\/j.cag.2006.11.015","volume":"31","author":"CJ Armstrong","year":"2007","unstructured":"Armstrong, C.J., Price, B.L., Barrett, W.A.: Interactive segmentation of image volumes with live surface. Comput. Graph. 31(2), 212\u2013229 (2007)","journal-title":"Comput. Graph."},{"issue":"3","key":"11_CR12","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1016\/j.media.2004.06.022","volume":"8","author":"JE Cates","year":"2004","unstructured":"Cates, J.E., Lefohn, A.E., Whitaker, R.T.: GIST an interactive, GPU-based level set segmentation tool for 3D medical images. Med. Image Anal. 8(3), 217\u2013231 (2004)","journal-title":"Med. Image Anal."},{"issue":"9","key":"11_CR13","doi-asserted-by":"publisher","first-page":"1124","DOI":"10.1109\/TPAMI.2004.60","volume":"26","author":"Y Boykov","year":"2004","unstructured":"Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut\/max-flow algorithms for energy minimization in vision. IEEE Trans. Pattern Anal. Mach. Intell. 26(9), 1124\u20131137 (2004)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR14","unstructured":"Malmberg, F., Strand, R., Kullberg, J., Nordenskj\u00f6ld, R., Bengtsson, E.: Smart paint a new interactive segmentation method applied to MR prostate segmentation. In: MICCAI Grand Challenge: Prostate MR Image Segmentation 2012 (2012)"},{"key":"11_CR15","unstructured":"Paul, M.: FSLeyes. https:\/\/fsl.fmrib.ox.ac.uk\/fsl\/fslwiki\/FSLeyes"},{"key":"11_CR16","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"11_CR17","unstructured":"Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: Improving neural networks by preventing co-adaptation of feature detectors. preprint arXiv:1207.0580 (2012)"},{"key":"11_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1007\/978-3-319-59126-1_32","volume-title":"Image Analysis","author":"KR Ayyalasomayajula","year":"2017","unstructured":"Ayyalasomayajula, K.R., Brun, A.: Historical document binarization combining semantic labeling and graph cuts. In: Sharma, P., Bianchi, F.M. (eds.) SCIA 2017. LNCS, vol. 10269, pp. 386\u2013396. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59126-1_32"},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Yushkevich, P.A., Gao, Y., Gerig, G.: ITK-SNAP: an interactive tool for semi-automatic segmentation of multi-modality biomedical images. In: 2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC), pp. 3342\u20133345. IEEE (2016)","DOI":"10.1109\/EMBC.2016.7591443"},{"issue":"9","key":"11_CR20","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","volume":"30","author":"A Fedorov","year":"2012","unstructured":"Fedorov, A., et al.: 3D slicer as an image computing platform for the quantitative imaging network. Magn. Reson. Imaging 30(9), 1323\u20131341 (2012)","journal-title":"Magn. Reson. Imaging"}],"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\/978-3-030-11723-8_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T15:57:26Z","timestamp":1710345446000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-11723-8_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030117221","9783030117238"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-11723-8_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"26 January 2019","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":"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":"iwb2018","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"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"95","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":"92","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":"97% - 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","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":"3","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"}]}}