{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:17:44Z","timestamp":1742912264924,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031439865"},{"type":"electronic","value":"9783031439872"}],"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\/978-3-031-43987-2_15","type":"book-chapter","created":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T23:07:48Z","timestamp":1696115268000},"page":"148-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Multi-task Method for\u00a0Immunofixation Electrophoresis Image Classification"],"prefix":"10.1007","author":[{"given":"Yi","family":"Shi","sequence":"first","affiliation":[]},{"given":"Rui-Xiang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Wen-Qi","family":"Shao","sequence":"additional","affiliation":[]},{"given":"Xin-Cen","family":"Duan","sequence":"additional","affiliation":[]},{"given":"Han-Jia","family":"Ye","sequence":"additional","affiliation":[]},{"given":"De-Chuan","family":"Zhan","sequence":"additional","affiliation":[]},{"given":"Bai-Shen","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Bei-Li","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Jiang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,1]]},"reference":[{"issue":"2013","key":"15_CR1","first-page":"332","volume":"1","author":"SM Abd Elrahman","year":"2013","unstructured":"Abd Elrahman, S.M., Abraham, A.: A review of class imbalance problem. J. Network Innovative Comput. 1(2013), 332\u2013340 (2013)","journal-title":"J. Network Innovative Comput."},{"issue":"5","key":"15_CR2","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1001\/jama.2022.0003","volume":"327","author":"AJ Cowan","year":"2022","unstructured":"Cowan, A.J., et al.: Diagnosis and management of multiple myeloma: a review. JAMA 327(5), 464\u2013477 (2022)","journal-title":"JAMA"},{"key":"15_CR3","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1007\/978-3-031-16446-0_39","volume-title":"MICCAI 2022","author":"S Dong","year":"2022","unstructured":"Dong, S., et al.: Multi-scale super-resolution magnetic resonance spectroscopic imaging with adjustable sharpness. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13436, pp. 410\u2013420. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16446-0_39"},{"key":"15_CR4","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1007\/978-3-031-16446-0_61","volume-title":"MICCAI 2022","author":"Y Gu","year":"2022","unstructured":"Gu, Y., et al.: BMD-GAN: bone mineral density estimation using x-ray image decomposition into projections of bone-segmented quantitative computed tomography using hierarchical learning. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13436, pp. 644\u2013654. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16446-0_61"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"2","key":"15_CR6","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1093\/clinchem\/hvac190","volume":"69","author":"H Hu","year":"2023","unstructured":"Hu, H., et al.: Expert-level immunofixation electrophoresis image recognition based on explainable and generalizable deep learning. Clin. Chem. 69(2), 130\u2013139 (2023)","journal-title":"Clin. Chem."},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: CVPR, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"15_CR8","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1007\/978-3-031-16434-7_33","volume-title":"MICCAI 2022","author":"G Jimenez","year":"2022","unstructured":"Jimenez, G., et al.: Visual deep learning-based explanation for Neuritic plaques segmentation in Alzheimer\u2019s disease using weakly annotated whole slide histopathological images. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13432, pp. 336\u2013344. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16434-7_33"},{"issue":"1","key":"15_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-019-0192-5","volume":"6","author":"JM Johnson","year":"2019","unstructured":"Johnson, J.M., Khoshgoftaar, T.M.: Survey on deep learning with class imbalance. J. Big Data 6(1), 1\u201354 (2019). https:\/\/doi.org\/10.1186\/s40537-019-0192-5","journal-title":"J. Big Data"},{"key":"15_CR10","doi-asserted-by":"crossref","unstructured":"Joyce, J.M.: Kullback-leibler divergence. In: International Encyclopedia of Statistical Science, pp. 720\u2013722 (2011)","DOI":"10.1007\/978-3-642-04898-2_327"},{"key":"15_CR11","unstructured":"Keren, D.F.: High-Resolution Electrophoresis and Immunofixation: Techniques and Interpretation (2017)"},{"key":"15_CR12","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1007\/978-3-031-16446-0_35","volume-title":"MICCAI 2022","author":"E Kuzmina","year":"2022","unstructured":"Kuzmina, E., Razumov, A., Rogov, O.Y., Adalsteinsson, E., White, J., Dylov, D.V.: Autofocusing+: noise-resilient motion correction in magnetic resonance imaging. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13436, pp. 365\u2013375. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16446-0_35"},{"key":"15_CR13","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1007\/978-3-031-16437-8_67","volume-title":"MICCAI 2022","author":"P L\u00f3pez Diez","year":"2022","unstructured":"L\u00f3pez Diez, P., et al.: Deep reinforcement learning for detection of inner ear abnormal anatomy in computed tomography. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13433, pp. 697\u2013706. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16437-8_67"},{"issue":"2","key":"15_CR14","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1016\/S0016-0032(96)00063-4","volume":"334","author":"M Men\u00e9ndez","year":"1997","unstructured":"Men\u00e9ndez, M., Pardo, J., Pardo, L., Pardo, M.: The jensen-shannon divergence. J. Franklin Inst. 334(2), 307\u2013318 (1997)","journal-title":"J. Franklin Inst."},{"key":"15_CR15","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1111\/vcp.12760","volume":"48","author":"AR Moore","year":"2019","unstructured":"Moore, A.R., Avery, P.R.: Protein characterization using electrophoresis and immunofixation; a case-based review of dogs and cats. Veterinary Clin. Pathol. 48, 29\u201344 (2019)","journal-title":"Veterinary Clin. Pathol."},{"issue":"3","key":"15_CR16","doi-asserted-by":"publisher","first-page":"e105","DOI":"10.1016\/S1470-2045(20)30756-7","volume":"22","author":"P Moreau","year":"2021","unstructured":"Moreau, P., et al.: Treatment of relapsed and refractory multiple myeloma: recommendations from the international myeloma working group. Lancet Oncol. 22(3), e105\u2013e118 (2021)","journal-title":"Lancet Oncol."},{"key":"15_CR17","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1007\/978-3-031-16446-0_74","volume-title":"MICCAI 2022","author":"S Oh","year":"2022","unstructured":"Oh, S., Kim, M.G., Kim, Y., Jung, G., Kwon, H., Bae, H.M.: Sensor geometry generalization to untrained conditions in quantitative ultrasound imaging. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13436, pp. 780\u2013789. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16446-0_74"},{"issue":"9","key":"15_CR18","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1038\/s41408-020-00359-2","volume":"10","author":"SV Rajkumar","year":"2020","unstructured":"Rajkumar, S.V., Kumar, S.: Multiple myeloma current treatment algorithms. Blood Cancer J. 10(9), 94 (2020)","journal-title":"Blood Cancer J."},{"key":"15_CR19","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1007\/978-3-031-16449-1_14","volume-title":"MICCAI 2022","author":"Y Shin","year":"2022","unstructured":"Shin, Y., et al.: Digestive organ recognition in video capsule endoscopy based on temporal segmentation network. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13437, pp. 136\u2013146. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16449-1_14"},{"key":"15_CR20","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/978-3-031-16440-8_11","volume-title":"MICCAI 2022","author":"Z Shui","year":"2022","unstructured":"Shui, Z., et al.: End-to-end cell recognition by point annotation. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13434, pp. 109\u2013118. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16440-8_11"},{"key":"15_CR21","doi-asserted-by":"publisher","DOI":"10.3389\/fradi.2021.796078","volume":"1","author":"M Tardy","year":"2022","unstructured":"Tardy, M., Mateus, D.: Leveraging multi-task learning to cope with poor and missing labels of mammograms. Front. Radiol. 1, 796078 (2022)","journal-title":"Front. Radiol."},{"key":"15_CR22","doi-asserted-by":"crossref","unstructured":"Wang, X., Girshick, R., Gupta, A., He, K.: Non-local neural networks. In: CVPR, pp. 7794\u20137803 (2018)","DOI":"10.1109\/CVPR.2018.00813"},{"key":"15_CR23","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1007\/978-3-031-16440-8_23","volume-title":"MICCAI 2022","author":"Y Wang","year":"2022","unstructured":"Wang, Y., et al.: Key-frame guided network for thyroid nodule recognition using ultrasound videos. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13434, pp. 238\u2013247. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16440-8_23"},{"issue":"7","key":"15_CR24","doi-asserted-by":"publisher","first-page":"1898","DOI":"10.1109\/TMI.2021.3068404","volume":"40","author":"XY Wei","year":"2021","unstructured":"Wei, X.Y., et al.: Deep collocative learning for immunofixation electrophoresis image analysis. IEEE Trans. Med. Imaging 40(7), 1898\u20131910 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"15_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.plabm.2021.e00256","volume":"27","author":"D Wilhite","year":"2021","unstructured":"Wilhite, D., Arfa, A., Cotter, T., Savage, N.M., Bollag, R.J., Singh, G.: Multiple myeloma: detection of free monoclonal light chains by modified immunofixation electrophoresis with antisera against free light chains. Pract. Lab. Med. 27, e00256 (2021)","journal-title":"Pract. Lab. Med."},{"key":"15_CR26","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.clinbiochem.2017.05.001","volume":"51","author":"MA Willrich","year":"2018","unstructured":"Willrich, M.A., Murray, D.L., Kyle, R.A.: Laboratory testing for monoclonal gammopathies: focus on monoclonal gammopathy of undetermined significance and smoldering multiple myeloma. Clin. Biochem. 51, 38\u201347 (2018)","journal-title":"Clin. Biochem."},{"key":"15_CR27","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: CBAM: convolutional block attention module. In: ECCV, pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"15_CR28","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-031-16440-8_1","volume-title":"MICCAI 2023","author":"C Xia","year":"2022","unstructured":"Xia, C., Wang, J., Qin, Y., Gu, Y., Chen, B., Yang, J.: An end-to-end combinatorial optimization method for r-band chromosome recognition with grouping guided attention. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2023. LNCS, vol. 13434, pp. 3\u201313. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16440-8_1"},{"key":"15_CR29","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1007\/978-3-031-16440-8_26","volume-title":"MICCAI 2022","author":"Y Xie","year":"2022","unstructured":"Xie, Y., Liao, H., Zhang, D., Chen, F.: Uncertainty-aware cascade network for ultrasound image segmentation with ambiguous boundary. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13434, pp. 268\u2013278. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16440-8_26"},{"issue":"1","key":"15_CR30","doi-asserted-by":"publisher","first-page":"14361","DOI":"10.1038\/s41598-020-71431-x","volume":"10","author":"X Yu","year":"2020","unstructured":"Yu, X., Pang, W., Xu, Q., Liang, M.: Mammographic image classification with deep fusion learning. Sci. Rep. 10(1), 14361 (2020)","journal-title":"Sci. Rep."},{"key":"15_CR31","series-title":"LNCS","first-page":"232","volume-title":"MICCAI 2022","author":"B Zeng","year":"2022","unstructured":"Zeng, B., et al.: Semi-supervised PR virtual staining for breast histopathological images. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13432, pp. 232\u2013241. Springer, Cham (2022)"}],"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\/978-3-031-43987-2_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T15:29:46Z","timestamp":1710170986000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43987-2_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031439865","9783031439872"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43987-2_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"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)"}}]}}