{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T10:25:26Z","timestamp":1743071126351,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031188138"},{"type":"electronic","value":"9783031188145"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-18814-5_12","type":"book-chapter","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T07:06:39Z","timestamp":1665644799000},"page":"121-129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Improved Multi-modal Patch Based Lymphoma Segmentation with\u00a0Negative Sample Augmentation and\u00a0Label Guidance on\u00a0PET\/CT Scans"],"prefix":"10.1007","author":[{"given":"Liangchen","family":"Liu","sequence":"first","affiliation":[]},{"given":"Jianfei","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Manas Kumar","family":"Nag","sequence":"additional","affiliation":[]},{"given":"Navid","family":"Hasani","sequence":"additional","affiliation":[]},{"given":"Seung Yeon","family":"Shin","sequence":"additional","affiliation":[]},{"given":"Sriram S.","family":"Paravastu","sequence":"additional","affiliation":[]},{"given":"Babak","family":"Saboury","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Lingyun","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Ronald M.","family":"Summers","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,12]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","unstructured":"A predictive model for aggressive Non-Hodgkin\u2019s lymphoma. N. Engl. J. Med. 329(14), 987\u2013994 (1993). https:\/\/doi.org\/10.1056\/NEJM199309303291402","DOI":"10.1056\/NEJM199309303291402"},{"issue":"3","key":"12_CR2","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s40134-013-0016-x","volume":"1","author":"J Czernin","year":"2013","unstructured":"Czernin, J., Allen-Auerbach, M., Nathanson, D., Herrmann, K.: PET\/CT in oncology: current status and perspectives. Curr. Radiol. Rep. 1(3), 177\u2013190 (2013)","journal-title":"Curr. Radiol. Rep."},{"key":"12_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1007\/978-3-030-88601-1_16","volume-title":"Belief Functions: Theory and Applications","author":"L Huang","year":"2021","unstructured":"Huang, L., Ruan, S., Decazes, P., Den\u0153ux, T.: Evidential segmentation of 3D PET\/CT images. In: Den\u0153ux, T., Lef\u00e8vre, E., Liu, Z., Pichon, F. (eds.) BELIEF 2021. LNCS (LNAI), vol. 12915, pp. 159\u2013167. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88601-1_16"},{"issue":"5","key":"12_CR4","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1056\/NEJMra050276","volume":"354","author":"ME Juweid","year":"2006","unstructured":"Juweid, M.E., Cheson, B.D.: Positron-emission tomography and assessment of cancer therapy. N. Engl. J. Med. 354(5), 496\u2013507 (2006)","journal-title":"N. Engl. J. Med."},{"issue":"1","key":"12_CR5","first-page":"164","volume":"35","author":"CK Kim","year":"1994","unstructured":"Kim, C.K., Gupta, N.C., Chandramouli, B., Alavi, A.: Standardized uptake values of FDG: body surface area correction is preferable to body weight correction. J. Nucl. Med. 35(1), 164\u2013167 (1994)","journal-title":"J. Nucl. Med."},{"key":"12_CR6","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Bengio, Y., LeCun, Y. (eds.) 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, 7\u20139 May 2015, Conference Track Proceedings (2015). http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"12_CR7","doi-asserted-by":"publisher","first-page":"8004","DOI":"10.1109\/ACCESS.2019.2963254","volume":"8","author":"H Li","year":"2019","unstructured":"Li, H., et al.: DenseX-Net: an end-to-end model for lymphoma segmentation in whole-body PET\/CT images. IEEE Access 8, 8004\u20138018 (2019)","journal-title":"IEEE Access"},{"key":"12_CR8","doi-asserted-by":"publisher","first-page":"80","DOI":"10.3389\/fonc.2013.00080","volume":"3","author":"J Li","year":"2013","unstructured":"Li, J., Xiao, Y.: Application of FDG-PET\/CT in radiation oncology. Front. Oncol. 3, 80 (2013)","journal-title":"Front. Oncol."},{"issue":"9","key":"12_CR9","doi-asserted-by":"publisher","first-page":"4345","DOI":"10.1109\/TIP.2018.2831454","volume":"27","author":"L Liu","year":"2018","unstructured":"Liu, L., Nie, F., Wiliem, A., Li, Z., Zhang, T., Lovell, B.C.: Multi-modal joint clustering with application for unsupervised attribute discovery. IEEE Trans. Image Process. 27(9), 4345\u20134356 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"12_CR10","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1093\/annonc\/mdn657","volume":"20","author":"A Noy","year":"2009","unstructured":"Noy, A., et al.: The majority of transformed lymphomas have high standardized uptake values (SUVs) on positron emission tomography (PET) scanning similar to diffuse large b-cell lymphoma (DLBCL). Ann. Oncol. 20(3), 508\u2013512 (2009)","journal-title":"Ann. Oncol."},{"issue":"1","key":"12_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40658-020-00346-3","volume":"7","author":"AJ Weisman","year":"2020","unstructured":"Weisman, A.J., et al.: Automated quantification of baseline imaging pet metrics on FDG PET\/CT images of pediatric Hodgkin lymphoma patients. EJNMMI Phys. 7(1), 1\u201312 (2020)","journal-title":"EJNMMI Phys."},{"key":"12_CR12","unstructured":"Xu, P., Zhu, X., Clifton, D.A.: Multimodal learning with transformers: a survey. arXiv preprint arXiv:2206.06488 (2022)"}],"container-title":["Lecture Notes in Computer Science","Multiscale Multimodal Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18814-5_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T07:08:11Z","timestamp":1665644891000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18814-5_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031188138","9783031188145"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18814-5_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"12 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Multiscale Multimodal Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmmi2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mmmi2022.github.io\/","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":"18","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":"12","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":"67% - 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":"2,5","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":"1,67","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)"}}]}}