{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T15:35:42Z","timestamp":1778600142540,"version":"3.51.4"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031164514","type":"print"},{"value":"9783031164521","type":"electronic"}],"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.springernature.com\/gp\/researchers\/text-and-data-mining"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-16452-1_56","type":"book-chapter","created":{"date-parts":[[2022,9,15]],"date-time":"2022-09-15T21:25:46Z","timestamp":1663277146000},"page":"588-598","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["A Self-guided Framework for Radiology Report Generation"],"prefix":"10.1007","author":[{"given":"Jun","family":"Li","sequence":"first","affiliation":[]},{"given":"Shibo","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Huiren","family":"Tao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,16]]},"reference":[{"key":"56_CR1","doi-asserted-by":"crossref","unstructured":"Vinyals, O., et al.: Show and tell: A neural image caption generator. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3156\u20133164 (2015)","DOI":"10.1109\/CVPR.2015.7298935"},{"key":"56_CR2","unstructured":"Xu, K., et al.: Show, attend and tell: Neural image caption generation with visual attention. In: International conference on machine learning, pp. 2048\u20132057, PMLR (2015)"},{"key":"56_CR3","doi-asserted-by":"crossref","unstructured":"Lu, J., et al.: Knowing when to look: adaptive attention via a visual sentinel for image captioning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 375\u2013383 (2017)","DOI":"10.1109\/CVPR.2017.345"},{"key":"56_CR4","doi-asserted-by":"crossref","unstructured":"Lu, J., et al.: Neural baby talk. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7219\u20137228 (2018)","DOI":"10.1109\/CVPR.2018.00754"},{"issue":"9","key":"56_CR5","doi-asserted-by":"publisher","first-page":"3786","DOI":"10.1109\/TNNLS.2021.3099165","volume":"32","author":"G Liu","year":"2021","unstructured":"Liu, G., et al.: Medical-VLBERT: medical visual language BERT for covid-19 CT report generation with alternate learning. IEEE Trans. Neural Netw. Learn. Syst. 32(9), 3786\u20133797 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"56_CR6","unstructured":"Yang, Y., et al.: Joint embedding of deep visual and semantic features for medical image report generation. IEEE Trans. Multimedia (2021)"},{"key":"56_CR7","doi-asserted-by":"crossref","unstructured":"Tran, A., et al.: Transform and tell: Entity-aware news image captioning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13035\u201313045 (2020)","DOI":"10.1109\/CVPR42600.2020.01305"},{"key":"56_CR8","doi-asserted-by":"crossref","unstructured":"Chen, L., et al.: Human-like controllable image captioning with verb-specific semantic roles. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16846\u201316856 (2021)","DOI":"10.1109\/CVPR46437.2021.01657"},{"key":"56_CR9","doi-asserted-by":"crossref","unstructured":"Xu, G., et al.: Towards accurate text-based image captioning with content diversity exploration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12637\u201312646 (2021)","DOI":"10.1109\/CVPR46437.2021.01245"},{"key":"56_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, Y., et al.: When radiology report generation meets knowledge graph. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 12910\u201312917 (2020)","DOI":"10.1609\/aaai.v34i07.6989"},{"key":"56_CR11","doi-asserted-by":"crossref","unstructured":"Liu, F., et al.: Exploring and distilling posterior and prior knowledge for radiology report generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13753\u201313762 (2021)","DOI":"10.1109\/CVPR46437.2021.01354"},{"key":"56_CR12","unstructured":"Li, C. Y., et al.: Hybrid retrieval-generation reinforced agent for medical image report generation. Adv. Neural Info Process. Syst.\u00a031 1537\u20131547 (2018)"},{"key":"56_CR13","doi-asserted-by":"crossref","unstructured":"Wang, Z., et al.: A self-boosting framework for automated radiographic report generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2433\u20132442 (2021)","DOI":"10.1109\/CVPR46437.2021.00246"},{"key":"56_CR14","doi-asserted-by":"crossref","unstructured":"Jing, B., et al.: Show, describe and conclude: on exploiting the structure information of chest X-ray reports. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 6570\u20136580 (2019)","DOI":"10.18653\/v1\/P19-1657"},{"key":"56_CR15","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in neural information processing systems, pp. 5998\u20136008 (2017)"},{"key":"56_CR16","doi-asserted-by":"crossref","unstructured":"Chen, Z., et al.: Generating radiology reports via memory-driven transformer. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1439\u20131449 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.112"},{"key":"56_CR17","doi-asserted-by":"crossref","unstructured":"You, D., et al.: Aligntransformer: hierarchical alignment of visual regions and disease tags for medical report generation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 72\u201382, Springer (2021)","DOI":"10.1007\/978-3-030-87199-4_7"},{"key":"56_CR18","doi-asserted-by":"crossref","unstructured":"Reimers, N., et al.: Sentence-BERT: sentence embeddings using siamese BERT-networks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing, pp. 671\u2013688, Association for Computational Linguistics (2019)","DOI":"10.18653\/v1\/D19-1410"},{"key":"56_CR19","doi-asserted-by":"crossref","unstructured":"Bowman, S.R., et al.: A large annotated corpus for learning natural language inference. arXiv preprint arXiv:1508.05326 (2015)","DOI":"10.18653\/v1\/D15-1075"},{"key":"56_CR20","doi-asserted-by":"crossref","unstructured":"Williams, A., et al.: A broad-coverage challenge corpus for sentence understanding through inference. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol 1 (Long Papers), pp. 1112\u20131122 (2018)","DOI":"10.18653\/v1\/N18-1101"},{"key":"56_CR21","doi-asserted-by":"crossref","unstructured":"McInnes, L., et al.: UMAP: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426 (2018)","DOI":"10.21105\/joss.00861"},{"key":"56_CR22","doi-asserted-by":"crossref","unstructured":"Campello, R.J., et al.: Density-based clustering based on hierarchical density estimates. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 160\u2013172, Springer (2013)","DOI":"10.1007\/978-3-642-37456-2_14"},{"key":"56_CR23","doi-asserted-by":"crossref","unstructured":"He, K., et al.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"56_CR24","doi-asserted-by":"crossref","unstructured":"Deng, J., et al.: Imagenet: A large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255, IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"56_CR25","unstructured":"Ba, J.L., et al.: Layer normalization. arXiv preprint arXiv:1607.06450(2016)"},{"issue":"2","key":"56_CR26","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1093\/jamia\/ocv080","volume":"23","author":"D Demner-Fushman","year":"2016","unstructured":"Demner-Fushman, D., et al.: Preparing a collection of radiology examinations for distribution and retrieval. J. Am. Med. Inform. Assoc. 23(2), 304\u2013310 (2016)","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"56_CR27","doi-asserted-by":"crossref","unstructured":"Papineni, K., et al.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311\u2013318 (2002)","DOI":"10.3115\/1073083.1073135"},{"key":"56_CR28","unstructured":"Lin, C.-Y.: Rouge: A package for automatic evaluation of summaries. In: Text summarization branches out, pp. 74\u201381 (2004)"},{"key":"56_CR29","unstructured":"Banerjee, S., et al.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and Summarization, pp. 65\u201372 (2005)"},{"key":"56_CR30","unstructured":"Chen, X., et al.: Microsoft COCO captions: Data collection and evaluation server. arXiv preprint arXiv:1504.00325 (2015)"},{"key":"56_CR31","unstructured":"Kingma, D.P., et al.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16452-1_56","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T11:51:37Z","timestamp":1710244297000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16452-1_56"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031164514","9783031164521"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16452-1_56","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"16 September 2022","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":"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":"18 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":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2022","order":10,"name":"conference_id","label":"Conference ID","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":"Microsoft Conference","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1831","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":"574","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":"31% - 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)"}}]}}