{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:43:59Z","timestamp":1778255039227,"version":"3.51.4"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031439896","type":"print"},{"value":"9783031439902","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-43990-2_3","type":"book-chapter","created":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T23:07:48Z","timestamp":1696115268000},"page":"23-32","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Eye-Guided Dual-Path Network for\u00a0Multi-organ Segmentation of\u00a0Abdomen"],"prefix":"10.1007","author":[{"given":"Chong","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daoqiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongjun","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,1]]},"reference":[{"issue":"3","key":"3_CR1","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1148\/radiol.2016151255","volume":"281","author":"R Bertram","year":"2016","unstructured":"Bertram, R., et al.: Eye movements of radiologists reflect expertise in CT study interpretation: a potential tool to measure resident development. Radiology 281(3), 805\u2013815 (2016)","journal-title":"Radiology"},{"issue":"1","key":"3_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s41235-019-0159-2","volume":"4","author":"TT Bruny\u00e9","year":"2019","unstructured":"Bruny\u00e9, T.T., Drew, T., Weaver, D.L., Elmore, J.G.: A review of eye tracking for understanding and improving diagnostic interpretation. Cogn. Res. Princ. Implic. 4(1), 1\u201316 (2019). https:\/\/doi.org\/10.1186\/s41235-019-0159-2","journal-title":"Cogn. Res. Princ. Implic."},{"key":"3_CR3","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/978-3-031-25066-8_9","volume-title":"Computer Vision","author":"H Cao","year":"2023","unstructured":"Cao, H., et al.: Swin-Unet: Unet-like pure transformer for medical image segmentation. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds.) ECCV 2022. LNCS, vol. 13803, pp. 205\u2013218. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-25066-8_9"},{"key":"3_CR4","unstructured":"Chen, J., et al.: Transunet: transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:2102.04306 (2021)"},{"key":"3_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1007\/978-3-030-59710-8_64","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"S Fu","year":"2020","unstructured":"Fu, S., et al.: Domain adaptive relational reasoning for 3D multi-organ segmentation. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12261, pp. 656\u2013666. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59710-8_64"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Herzig, J., Nowak, P.K., M\u00fcller, T., Piccinno, F., Eisenschlos, J.M.: Tapas: weakly supervised table parsing via pre-training. arXiv preprint arXiv:2004.02349 (2020)","DOI":"10.18653\/v1\/2020.acl-main.398"},{"issue":"7","key":"3_CR7","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1016\/j.acra.2008.01.023","volume":"15","author":"HL Kundel","year":"2008","unstructured":"Kundel, H.L., Nodine, C.F., Krupinski, E.A., Mello-Thoms, C.: Using gaze-tracking data and mixture distribution analysis to support a holistic model for the detection of cancers on mammograms. Acad. Radiol. 15(7), 881\u2013886 (2008)","journal-title":"Acad. Radiol."},{"key":"3_CR8","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1007\/978-3-031-16446-0_44","volume-title":"Medical Image Computing and Computer-Assisted Intervention","author":"G Li","year":"2022","unstructured":"Li, G., Lyu, J., Wang, C., Dou, Q., Qin, J.: WavTrans: synergizing wavelet and cross-attention transformer for multi-contrast MRI super-resolution. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13436, pp. 463\u2013473. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16446-0_44"},{"key":"3_CR9","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1007\/978-3-031-16449-1_10","volume-title":"Medical Image Computing and Computer Assisted Intervention","author":"Q Men","year":"2022","unstructured":"Men, Q., Teng, C., Drukker, L., Papageorghiou, A.T., Noble, J.A.: Multimodal-guidenet: gaze-probe bidirectional guidance in obstetric ultrasound scanning. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13437, pp. 94\u2013103. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16449-1_10"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Milletari, F., Navab, N., Ahmadi, S.A.: V-net: fully convolutional neural networks for volumetric medical image segmentation. In: 2016 Fourth International Conference on 3D Vision (3DV), pp. 565\u2013571. IEEE (2016)","DOI":"10.1109\/3DV.2016.79"},{"key":"3_CR11","unstructured":"Oktay, O., et al.: Attention U-net: learning where to look for the pancreas. arXiv preprint arXiv:1804.03999 (2018)"},{"issue":"10","key":"3_CR12","doi-asserted-by":"publisher","first-page":"2698","DOI":"10.1109\/TMI.2020.3042773","volume":"40","author":"X Ouyang","year":"2020","unstructured":"Ouyang, X., et al.: Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis. IEEE Trans. Med. Imaging 40(10), 2698\u20132710 (2020)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"3_CR13","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"},{"key":"3_CR14","unstructured":"Shu, R., Chen, Y., Kumar, A., Ermon, S., Poole, B.: Weakly supervised disentanglement with guarantees. arXiv preprint arXiv:1910.09772 (2019)"},{"key":"3_CR15","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"7","key":"3_CR16","doi-asserted-by":"publisher","first-page":"1688","DOI":"10.1109\/TMI.2022.3146973","volume":"41","author":"S Wang","year":"2022","unstructured":"Wang, S., Ouyang, X., Liu, T., Wang, Q., Shen, D.: Follow my eye: using gaze to supervise computer-aided diagnosis. IEEE Trans. Med. Imaging 41(7), 1688\u20131698 (2022)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"2","key":"3_CR17","doi-asserted-by":"publisher","first-page":"32","DOI":"10.3390\/vision3020032","volume":"3","author":"CC Wu","year":"2019","unstructured":"Wu, C.C., Wolfe, J.M.: Eye movements in medical image perception: a selective review of past, present and future. Vision 3(2), 32 (2019)","journal-title":"Vision"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43990-2_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T15:36:46Z","timestamp":1710171406000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43990-2_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031439896","9783031439902"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43990-2_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 October 2023","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":"Vancouver, BC","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2023\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2250","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":"730","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":"32% - 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":"5","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)"}}]}}