{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T08:09:03Z","timestamp":1771056543230,"version":"3.50.1"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031723773","type":"print"},{"value":"9783031723780","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-72378-0_43","type":"book-chapter","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T07:02:53Z","timestamp":1727852573000},"page":"461-471","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CheXtriev: Anatomy-Centered Representation for\u00a0Case-Based Retrieval of\u00a0Chest Radiographs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5218-8434","authenticated-orcid":false,"given":"Naren","family":"Akash R. J.","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5554-1703","authenticated-orcid":false,"given":"Arihanth","family":"Tadanki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9588-0482","authenticated-orcid":false,"given":"Jayanthi","family":"Sivaswamy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,3]]},"reference":[{"key":"43_CR1","unstructured":"Kolodner, J.L.: The role of experience in development of expertise. In: Annual AAAI Conference on Artificial Intelligence (1982)"},{"issue":"1","key":"43_CR2","first-page":"42","volume":"12","author":"S Slade","year":"1991","unstructured":"Slade, S.: Case-based reasoning: a research paradigm. AI Mag. 12(1), 42\u201342 (1991)","journal-title":"AI Mag."},{"issue":"3","key":"43_CR3","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1109\/TSMC.1987.4309058","volume":"17","author":"JL Kolodner","year":"1987","unstructured":"Kolodner, J.L., et al.: Using experience in clinical problem solving: introduction and framework. IEEE Trans. Syst. Man Cybern. 17(3), 420\u2013431 (1987)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"43_CR4","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.media.2017.09.007","volume":"43","author":"Z Li","year":"2018","unstructured":"Li, Z., et al.: large-scale retrieval for medical image analytics: a comprehensive review. Med. Image Anal. 43, 66\u201384 (2018)","journal-title":"Med. Image Anal."},{"issue":"3","key":"43_CR5","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1016\/j.chest.2022.10.039","volume":"163","author":"WB Gefter","year":"2023","unstructured":"Gefter, W.B., et al.: Commonly missed findings on chest radiographs: causes and consequences. Chest 163(3), 650\u2013661 (2023)","journal-title":"Chest"},{"key":"43_CR6","doi-asserted-by":"publisher","first-page":"5261","DOI":"10.1007\/s10462-020-09820-x","volume":"53","author":"J Rodrigues","year":"2020","unstructured":"Rodrigues, J., et al.: deep hashing for multi-label image retrieval. a survey. Artifi. Intell. Rev. 53, 5261\u20135307 (2020)","journal-title":"Artifi. Intell. Rev."},{"key":"43_CR7","doi-asserted-by":"publisher","unstructured":"Conjeti, S., Roy, A.G., Katouzian, A., Navab, N.: Hashing with residual networks for image retrieval. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10435, pp. 541\u2013549. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66179-7_62","DOI":"10.1007\/978-3-319-66179-7_62"},{"key":"43_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1007\/978-3-030-00928-1_70","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018","author":"Z Chen","year":"2018","unstructured":"Chen, Z., Cai, R., Lu, J., Feng, J., Zhou, J.: Order-sensitive deep hashing for multimorbidity medical image\u00a0retrieval. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-L\u00f3pez, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11070, pp. 620\u2013628. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00928-1_70"},{"key":"43_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/978-3-030-87240-3_20","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"P Huang","year":"2021","unstructured":"Huang, P., Zhou, X., Wei, Z., Guo, G.: Energy-based supervised hashing for multimorbidity image retrieval. In: de Bruijne, M., et al. (eds.) MICCAI 2021. LNCS, vol. 12905, pp. 205\u2013214. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87240-3_20"},{"key":"43_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.101981","volume":"69","author":"J Fang","year":"2021","unstructured":"Fang, J., et al.: Deep triplet hashing network for case-based medical image retrieval. Med. Image Anal. 69, 101981 (2021)","journal-title":"Med. Image Anal."},{"key":"43_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1007\/978-3-030-87240-3_58","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"Y Yu","year":"2021","unstructured":"Yu, Y., Hu, P., Lin, J., Krishnaswamy, P.: Multimodal multitask deep learning for X-ray image retrieval. In: de Bruijne, M., et al. (eds.) MICCAI 2021. LNCS, vol. 12905, pp. 603\u2013613. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87240-3_58"},{"key":"43_CR12","doi-asserted-by":"publisher","unstructured":"van Sonsbeek, T., et al.: X-TRA: improving chest x-ray tasks with cross-modal retrieval augmentation. In: International Conference on Information Processing in Medical Imaging - IPMI. LNCS. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-34048-2_36","DOI":"10.1007\/978-3-031-34048-2_36"},{"issue":"2","key":"43_CR13","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1378\/chest.10-1302","volume":"141","author":"S Raoof","year":"2012","unstructured":"Raoof, S., et al.: Interpretation of plain chest roentgenogram. Chest 141(2), 545\u2013558 (2012)","journal-title":"Chest"},{"key":"43_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1007\/978-3-030-87240-3_77","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"NN Agu","year":"2021","unstructured":"Agu, N.N., Agu, N.N., et al.: AnaXNet: anatomy aware multi-label finding classification in chest x-ray. In: de Bruijne, M., et al. (eds.) MICCAI 2021. LNCS, vol. 12905, pp. 804\u2013813. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87240-3_77"},{"key":"43_CR15","doi-asserted-by":"publisher","unstructured":"Karwande, G., et al.: CheXRelNet: an anatomy-aware model for tracking longitudinal relationships between chest x-rays. In: Medical Image Computing and Computer-Assisted Intervention - MICCAI. LNCS. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16431-6_55","DOI":"10.1007\/978-3-031-16431-6_55"},{"key":"43_CR16","doi-asserted-by":"crossref","unstructured":"Tanida, T., et al. Interactive and explainable region-guided radiology report generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.00718"},{"issue":"6","key":"43_CR17","doi-asserted-by":"publisher","first-page":"847","DOI":"10.1002\/ca.22397","volume":"27","author":"K Yammine","year":"2014","unstructured":"Yammine, K.: Evidence-based Anatomy. Clin. Anat. 27(6), 847\u2013852 (2014)","journal-title":"Clin. Anat."},{"key":"43_CR18","unstructured":"Dwivedi, Vijay Prakash, et al.: A generalization of transformer networks to graphs. In: AAAI 2021 Workshop on Deep Learning on Graphs: Methods and Applications (2020)"},{"key":"43_CR19","unstructured":"Douze, M., et al.: The Faiss Library. arXiv preprint arXiv:2401.08281 (2024)"},{"key":"43_CR20","doi-asserted-by":"crossref","unstructured":"Hu, B., et al.: X-MIR: explainable medical image retrieval. In IEEE\/CVF Winter Conference on Applications of Computer Vision (2022)","DOI":"10.1109\/WACV51458.2022.00161"},{"key":"43_CR21","doi-asserted-by":"crossref","unstructured":"Johnson, A., et al.: MIMIC-CXR-JPG, A Large Publicly Available Database of Labeled Chest Radiographs. arXiv preprint arXiv:1901.07042 (2019)","DOI":"10.1038\/s41597-019-0322-0"},{"key":"43_CR22","doi-asserted-by":"crossref","unstructured":"Johnson, A., et al.: MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports. Sci. Data 6(1), 317 (2019)","DOI":"10.1038\/s41597-019-0322-0"},{"key":"43_CR23","unstructured":"Wu, J.T., et al.: Chest imagenome dataset for clinical reasoning. In: Advances in Neural Information Processing Systems (2021)"},{"key":"43_CR24","doi-asserted-by":"crossref","unstructured":"Ropp, A., et al.: Did i miss that: subtle and commonly missed findings on chest radiographs. Current Problems Diagnostic Radiol., 44(3), 277-289 (2015)","DOI":"10.1067\/j.cpradiol.2014.09.003"},{"key":"43_CR25","doi-asserted-by":"crossref","unstructured":"de Groot, P.M., et al.: Pitfalls in chest radiographic interpretation: blind spots. Seminars Roentgenol. 50(3), 197-209, (2015)","DOI":"10.1053\/j.ro.2015.01.008"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72378-0_43","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T07:30:12Z","timestamp":1771054212000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72378-0_43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031723773","9783031723780"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72378-0_43","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"There are no conflicts of interest to declare.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"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":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}