{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:28:08Z","timestamp":1774366088703,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319661780","type":"print"},{"value":"9783319661797","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-66179-7_77","type":"book-chapter","created":{"date-parts":[[2017,9,3]],"date-time":"2017-09-03T19:24:46Z","timestamp":1504466686000},"page":"674-682","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Pancreas Segmentation in MRI Using Graph-Based Decision Fusion on Convolutional Neural Networks"],"prefix":"10.1007","author":[{"given":"Jinzheng","family":"Cai","sequence":"first","affiliation":[]},{"given":"Le","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Yuanpu","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Fuyong","family":"Xing","sequence":"additional","affiliation":[]},{"given":"Lin","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,4]]},"reference":[{"key":"77_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1007\/978-3-319-46723-8_51","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"J Cai","year":"2016","unstructured":"Cai, J., Lu, L., Zhang, Z., Xing, F., Yang, L., Yin, Q.: Pancreas segmentation in MRI using graph-based decision fusion on convolutional neural networks. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 442\u2013450. Springer, Cham (2016). doi:10.1007\/978-3-319-46723-8_51"},{"key":"77_CR2","unstructured":"Chen, J., Yang, L., Zhang, Y., Alber, M.S., Chen, D.Z.: Combining fully convolutional and recurrent neural networks for 3D biomedical image segmentation. CoRR abs\/1609.01006 (2016)"},{"issue":"1","key":"77_CR3","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1109\/TIP.2016.2624198","volume":"26","author":"A Farag","year":"2017","unstructured":"Farag, A., Lu, L., Roth, H.R., Liu, J., Turkbey, E., Summers, R.M.: A bottom-up approach for pancreas segmentation using cascaded superpixels and (deep) image patch labeling. IEEE Trans. Image Process. 26(1), 386\u2013399 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"77_CR4","doi-asserted-by":"crossref","unstructured":"Kamnitsas, K., Ledig, C., Newcombe, V.F.J., Simpson, J.P., Kane, A.D., Menon, D.K., Rueckert, D., Glocker, B.: Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. CoRR abs\/1603.05959 (2016)","DOI":"10.1016\/j.media.2016.10.004"},{"key":"77_CR5","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: IEEE CVPR, pp. 3431\u20133440, June 2015","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"77_CR6","doi-asserted-by":"crossref","unstructured":"Merkow, J., Kriegman, D.J., Marsden, A., Tu, Z.: Dense volume-to-volume vascular boundary detection. CoRR abs\/1605.08401 (2016)","DOI":"10.1007\/978-3-319-46726-9_43"},{"key":"77_CR7","doi-asserted-by":"crossref","unstructured":"Milletari, F., Navab, N., Ahmadi, S.: V-net: fully convolutional neural networks for volumetric medical image segmentation. CoRR abs\/1606.04797 (2016)","DOI":"10.1109\/3DV.2016.79"},{"key":"77_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1007\/978-3-319-46723-8_64","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"M Oda","year":"2016","unstructured":"Oda, M., et al.: Regression forest-based atlas localization and direction specific atlas generation for pancreas segmentation. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 556\u2013563. Springer, Cham (2016). doi:10.1007\/978-3-319-46723-8_64"},{"key":"77_CR9","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). doi:10.1007\/978-3-319-24574-4_28"},{"key":"77_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1007\/978-3-319-24553-9_68","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"HR Roth","year":"2015","unstructured":"Roth, H.R., Lu, L., Farag, A., Shin, H.-C., Liu, J., Turkbey, E.B., Summers, R.M.: DeepOrgan: multi-level deep convolutional networks for automated pancreas segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9349, pp. 556\u2013564. Springer, Cham (2015). doi:10.1007\/978-3-319-24553-9_68"},{"key":"77_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/978-3-319-46723-8_52","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"HR Roth","year":"2016","unstructured":"Roth, H.R., Lu, L., Farag, A., Sohn, A., Summers, R.M.: Spatial aggregation of holistically-nested networks for automated pancreas segmentation. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 451\u2013459. Springer, Cham (2016). doi:10.1007\/978-3-319-46723-8_52"},{"key":"77_CR12","doi-asserted-by":"crossref","unstructured":"Roth, H.R., Lu, L., Lay, N., Harrison, A.P., Farag, A., Summers, R.M.: Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation. CoRR abs\/1702.00045 (2017)","DOI":"10.1016\/j.media.2018.01.006"},{"key":"77_CR13","unstructured":"Shi, X., Chen, Z., Wang, H., Yeung, D., Wong, W., Woo, W.: Convolutional LSTM network: a machine learning approach for precipitation nowcasting. CoRR abs\/1506.04214 (2015)"},{"key":"77_CR14","unstructured":"Stollenga, M.F., Byeon, W., Liwicki, M., Schmidhuber, J.: Parallel multi-dimensional LSTM, with application to fast biomedical volumetric image segmentation. CoRR abs\/1506.07452 (2015)"},{"issue":"1","key":"77_CR15","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.media.2015.04.015","volume":"23","author":"T Tong","year":"2015","unstructured":"Tong, T., Wolz, R., Wang, Z., Gao, Q., Misawa, K., Fujiwara, M., Mori, K., Hajnal, J.V., Rueckert, D.: Discriminative dictionary learning for abdominal multi-organ segmentation. Med. Image Anal. 23(1), 92\u2013104 (2015)","journal-title":"Med. Image Anal."},{"issue":"9","key":"77_CR16","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1109\/TMI.2013.2265805","volume":"32","author":"R Wolz","year":"2013","unstructured":"Wolz, R., Chu, C., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D.: Automated abdominal multi-organ segmentation with subject-specific atlas generation. IEEE Trans. Med. Imaging 32(9), 1723\u20131730 (2013)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"77_CR17","doi-asserted-by":"crossref","unstructured":"Xie, S., Tu, Z.: Holistically-nested edge detection. In: IEEE ICCV, pp. 1395\u20131403 (2015)","DOI":"10.1109\/ICCV.2015.164"},{"key":"77_CR18","unstructured":"Zhou, Y., Xie, L., Shen, W., Fishman, E., Yuille, A.L.: Pancreas segmentation in abdominal CT scan: a coarse-to-fine approach. CoRR abs\/1612.08230 (2016)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2212 MICCAI 2017"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-66179-7_77","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,5]],"date-time":"2022-09-05T00:16:13Z","timestamp":1662336973000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-66179-7_77"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319661780","9783319661797"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-66179-7_77","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"4 September 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Quebec City, QC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.miccai2017.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}