{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:45:22Z","timestamp":1767624322059,"version":"3.44.0"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032049261"},{"type":"electronic","value":"9783032049278"}],"license":[{"start":{"date-parts":[[2025,9,21]],"date-time":"2025-09-21T00:00:00Z","timestamp":1758412800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,21]],"date-time":"2025-09-21T00:00:00Z","timestamp":1758412800000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-04927-8_36","type":"book-chapter","created":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T17:08:40Z","timestamp":1758388120000},"page":"376-385","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MiCo: Multiple Instance Learning with\u00a0Context-Aware Clustering for\u00a0Whole Slide Image Analysis"],"prefix":"10.1007","author":[{"given":"Junjian","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hulin","family":"Kuang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailin","family":"Yue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengshen","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,21]]},"reference":[{"key":"36_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/978-3-030-87237-3_33","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"RJ Chen","year":"2021","unstructured":"Chen, R.J., Lu, M.Y., Shaban, M., Chen, C., Chen, T.Y., Williamson, D.F.K., Mahmood, F.: Whole slide images are 2D point clouds: context-aware survival prediction using patch-based graph convolutional Networks. In: de Bruijne, M., et al. (eds.) MICCAI 2021. LNCS, vol. 12908, pp. 339\u2013349. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87237-3_33"},{"key":"36_CR2","doi-asserted-by":"crossref","unstructured":"Cruz-Roa, A., et al.: Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. In: Medical Imaging 2014: Digital Pathology, vol.\u00a09041, p. 904103. SPIE (2014)","DOI":"10.1117\/12.2043872"},{"key":"36_CR3","doi-asserted-by":"crossref","unstructured":"Das, K., Conjeti, S., Roy, A.G., Chatterjee, J., Sheet, D.: Multiple instance learning of deep convolutional neural networks for breast histopathology whole slide classification. In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp. 578\u2013581. IEEE (2018)","DOI":"10.1109\/ISBI.2018.8363642"},{"key":"36_CR4","unstructured":"Ding, T., et al.: Multimodal whole slide foundation model for pathology (2024). https:\/\/arxiv.org\/abs\/2411.19666"},{"key":"36_CR5","unstructured":"Ilse, M., Tomczak, J., Welling, M.: Attention-based deep multiple instance learning. In: International Conference on Machine Learning, pp. 2127\u20132136. PMLR (2018)"},{"issue":"8","key":"36_CR6","doi-asserted-by":"publisher","first-page":"897","DOI":"10.3390\/bioengineering10080897","volume":"10","author":"M Lee","year":"2023","unstructured":"Lee, M.: Recent advancements in deep learning using whole slide imaging for cancer prognosis. Bioengineering 10(8), 897 (2023)","journal-title":"Bioengineering"},{"key":"36_CR7","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: Dynamic graph representation with knowledge-aware attention for histopathology whole slide image analysis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11323\u201311332 (2024)","DOI":"10.1109\/CVPR52733.2024.01076"},{"key":"36_CR8","doi-asserted-by":"publisher","first-page":"5095","DOI":"10.1109\/JBHI.2025.3552640","volume":"29","author":"J Li","year":"2025","unstructured":"Li, J., Kuang, H., Liu, J., Yue, H., Wang, J.: Ca2cl: cluster-aware adversarial contrastive learning for pathological image analysis. IEEE J. Biomed. Health Inform. 29, 5095\u20135108 (2025)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"36_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102521","volume":"80","author":"J Li","year":"2022","unstructured":"Li, J., et al.: DARC: deep adaptive regularized clustering for histopathological image classification. Med. Image Anal. 80, 102521 (2022)","journal-title":"Med. Image Anal."},{"key":"36_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1007\/978-3-030-00934-2_20","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018","author":"R Li","year":"2018","unstructured":"Li, R., Yao, J., Zhu, X., Li, Y., Huang, J.: Graph CNN for survival analysis on whole slide pathological images. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-L\u00f3pez, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11071, pp. 174\u2013182. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00934-2_20"},{"issue":"1","key":"36_CR11","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0262257","volume":"17","author":"M Lia","year":"2022","unstructured":"Lia, M., Horn, L.C., Sodeikat, P., H\u00f6ckel, M., Aktas, B., Wolf, B.: The diagnostic value of core needle biopsy in cervical cancer: A retrospective analysis. PLoS ONE 17(1), e0262257 (2022)","journal-title":"PLoS ONE"},{"issue":"3","key":"36_CR12","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1038\/s41591-022-01709-2","volume":"28","author":"J Lipkova","year":"2022","unstructured":"Lipkova, J., et al.: Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies. Nat. Med. 28(3), 575\u2013582 (2022)","journal-title":"Nat. Med."},{"issue":"1","key":"36_CR13","first-page":"22","volume":"22","author":"O Medvedev","year":"2021","unstructured":"Medvedev, O., et al.: Perineural spread in head-and-neck malignancies: imaging findings-an updated literature review. Bosn. J. Basic Med. Sci. 22(1), 22 (2021)","journal-title":"Bosn. J. Basic Med. Sci."},{"key":"36_CR14","doi-asserted-by":"crossref","unstructured":"Qu, L., Liu, S., Liu, X., Wang, M., Song, Z.: Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self-supervised techniques in histopathological image analysis. Phys. Med. Biol. 67(20), 20TR01 (2022)","DOI":"10.1088\/1361-6560\/ac910a"},{"key":"36_CR15","first-page":"2136","volume":"34","author":"Z Shao","year":"2021","unstructured":"Shao, Z., Bian, H., Chen, Y., Wang, Y., Zhang, J., Ji, X., et al.: Transmil: transformer based correlated multiple instance learning for whole slide image classification. Adv. Neural. Inf. Process. Syst. 34, 2136\u20132147 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"36_CR16","doi-asserted-by":"crossref","unstructured":"Shao, Z., Chen, Y., Bian, H., Zhang, J., Liu, G., Zhang, Y.: HVTSurv: hierarchical vision transformer for patient-level survival prediction from whole slide image. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037, pp. 2209\u20132217 (2023)","DOI":"10.1609\/aaai.v37i2.25315"},{"key":"36_CR17","doi-asserted-by":"crossref","unstructured":"Song, C., et al.: LVPnet: a latent-variable-based prediction-driven end-to-end framework for lossless compression of medical images (2025). https:\/\/arxiv.org\/abs\/2506.17983","DOI":"10.1007\/978-3-032-04984-1_28"},{"key":"36_CR18","doi-asserted-by":"crossref","unstructured":"Tang, W., Zhou, F., Huang, S., Zhu, X., Zhang, Y., Liu, B.: Feature re-embedding: Towards foundation model-level performance in computational pathology. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11343\u201311352 (2024)","DOI":"10.1109\/CVPR52733.2024.01078"},{"key":"36_CR19","unstructured":"Van Den\u00a0Oord, A., Vinyals, O., et\u00a0al.: Neural discrete representation learning. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"36_CR20","unstructured":"Xiang, J., Zhang, J.: Exploring low-rank property in multiple instance learning for whole slide image classification. In: The Eleventh International Conference on Learning Representations (2023)"},{"issue":"2","key":"36_CR21","doi-asserted-by":"publisher","first-page":"222","DOI":"10.5858\/arpa.2018-0343-RA","volume":"143","author":"MD Zarella","year":"2019","unstructured":"Zarella, M.D., et al.: A practical guide to whole slide imaging: a white paper from the digital pathology association. Arch. Pathol. Lab. Med. 143(2), 222\u2013234 (2019)","journal-title":"Arch. Pathol. Lab. Med."}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-04927-8_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T17:08:47Z","timestamp":1758388127000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-04927-8_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,21]]},"ISBN":["9783032049261","9783032049278"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-04927-8_36","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,9,21]]},"assertion":[{"value":"21 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","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":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}