{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:48:40Z","timestamp":1775324920334,"version":"3.50.1"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319245522","type":"print"},{"value":"9783319245539","type":"electronic"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-24553-9_66","type":"book-chapter","created":{"date-parts":[[2015,9,24]],"date-time":"2015-09-24T06:01:29Z","timestamp":1443074489000},"page":"539-546","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Label Stability in Multiple Instance Learning"],"prefix":"10.1007","author":[{"given":"Veronika","family":"Cheplygina","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lauge","family":"S\u00f8rensen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David M. J.","family":"Tax","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marleen","family":"de Bruijne","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Loog","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,11,18]]},"reference":[{"key":"66_CR1","unstructured":"Andrews, S., Tsochantaridis, I., Hofmann, T.: Support vector machines for multiple-instance learning. In: NIPS, pp. 561\u2013568 (2002)"},{"key":"66_CR2","doi-asserted-by":"crossref","unstructured":"Ben-Hur, A., Elisseeff, A., Guyon, I.: A stability based method for discovering structure in clustered data. In: Pac. Symp. Biocomput., pp. 6\u201317 (2001)","DOI":"10.1142\/9789812799623_0002"},{"key":"66_CR3","doi-asserted-by":"crossref","unstructured":"Bi, J., Liang, J.: Multiple instance learning of pulmonary embolism detection with geodesic distance along vascular structure. In: CVPR, pp. 1\u20138 (2007)","DOI":"10.1109\/CVPR.2007.383141"},{"issue":"12","key":"66_CR4","doi-asserted-by":"publisher","first-page":"1931","DOI":"10.1109\/TPAMI.2006.248","volume":"28","author":"Y. Chen","year":"2006","unstructured":"Chen, Y., Bi, J., Wang, J.: MILES: Multiple-instance learning via embedded instance selection. IEEE T. Pattern. Anal. Mach. Intel.\u00a028(12), 1931\u20131947 (2006)","journal-title":"IEEE T. Pattern. Anal. Mach. Intel."},{"issue":"1","key":"66_CR5","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.patcog.2014.07.022","volume":"48","author":"V. Cheplygina","year":"2015","unstructured":"Cheplygina, V., Tax, D.M.J., Loog, M.: Multiple instance learning with bag dissimilarities. Pattern Recognition\u00a048(1), 264\u2013275 (2015)","journal-title":"Pattern Recognition"},{"key":"66_CR6","doi-asserted-by":"crossref","unstructured":"Cheplygina, V., et al.: Classification of COPD with multiple instance learning. In: ICPR, pp. 1508\u20131513 (2014)","DOI":"10.1109\/ICPR.2014.268"},{"key":"66_CR7","doi-asserted-by":"crossref","unstructured":"Decenci\u00e8re, E., et al.: Feedback on a publicly distributed image database: the Messidor database. Image Anal. Stereol., 231\u2013234 (2014)","DOI":"10.5566\/ias.1155"},{"issue":"3","key":"66_CR8","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1109\/TBME.2007.909544","volume":"55","author":"M.M. Dundar","year":"2008","unstructured":"Dundar, M.M., Fung, G., et al.: Multiple-instance learning algorithms for computer-aided detection. IEEE T. Biomed. Eng.\u00a055(3), 1015\u20131021 (2008)","journal-title":"IEEE T. Biomed. Eng."},{"key":"66_CR9","doi-asserted-by":"crossref","unstructured":"Kandemir, M., Hamprecht, F.A.: Computer-aided diagnosis from weak supervision: A benchmarking study. Comput. Med. Imag. Grap. (2014) (in press)","DOI":"10.1016\/j.compmedimag.2014.11.010"},{"key":"66_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1007\/978-3-319-10470-6_29","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2014","author":"M. Kandemir","year":"2014","unstructured":"Kandemir, M., Zhang, C., Hamprecht, F.A.: Empowering multiple instance histopathology cancer diagnosis by cell graphs. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014, Part II. LNCS, vol.\u00a08674, pp. 228\u2013235. Springer, Heidelberg (2014)"},{"key":"66_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1007\/978-3-540-73273-0_52","volume-title":"Information Processing in Medical Imaging","author":"J. Liang","year":"2007","unstructured":"Liang, J., Bi, J.: Computer aided detection of pulmonary embolism with tobogganing and mutiple instance classification in CT pulmonary angiography. In: Karssemeijer, N., Lelieveldt, B. (eds.) IPMI 2007. LNCS, vol.\u00a04584, pp. 630\u2013641. Springer, Heidelberg (2007)"},{"key":"66_CR12","unstructured":"Marques, J.: Osteoarthritis imaging by quantification of tibial trabecular bone. Ph.D. thesis, K\u00f8benhavns Universitet (2013)"},{"issue":"1","key":"66_CR13","first-page":"179","volume":"31","author":"J. Melendez","year":"2014","unstructured":"Melendez, J., et al.: A novel multiple-instance learning-based approach to computer-aided detection of tuberculosis on chest x-rays. TMI\u00a031(1), 179\u2013192 (2014)","journal-title":"TMI"},{"issue":"5","key":"66_CR14","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1097\/JTO.0b013e3181a0d98f","volume":"4","author":"J.H. Pedersen","year":"2009","unstructured":"Pedersen, J.H., et al.: The Danish randomized lung cancer CT screening trial-overall design and results of the prevalence round. J. Thorac. Oncol.\u00a04(5), 608\u2013614 (2009)","journal-title":"J. Thorac. Oncol."},{"issue":"6981","key":"66_CR15","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1038\/nature02341","volume":"428","author":"T. Poggio","year":"2004","unstructured":"Poggio, T., Rifkin, R., Mukherjee, S., Niyogi, P.: General conditions for predictivity in learning theory. Nature\u00a0428(6981), 419\u2013422 (2004)","journal-title":"Nature"},{"issue":"6","key":"66_CR16","first-page":"1228","volume":"16","author":"G. Quellec","year":"2012","unstructured":"Quellec, G., et al.: A multiple-instance learning framework for diabetic retinopathy screening. MedIA\u00a016(6), 1228\u20131240 (2012)","journal-title":"MedIA"},{"issue":"1","key":"66_CR17","first-page":"70","volume":"31","author":"L. S\u00f8rensen","year":"2012","unstructured":"S\u00f8rensen, L., Nielsen, M., Lo, P., Ashraf, H., Pedersen, J.H., de Bruijne, M.: Texture-based analysis of COPD: a data-driven approach. TMI\u00a031(1), 70\u201378 (2012)","journal-title":"TMI"},{"issue":"12","key":"66_CR18","doi-asserted-by":"publisher","first-page":"3348","DOI":"10.1109\/TBME.2012.2213597","volume":"59","author":"L. Sun","year":"2012","unstructured":"Sun, L., Lu, Y., Yang, K., Li, S.: ECG analysis using multiple instance learning for myocardial infarction detection. IEEE T. Biomed. Eng.\u00a059(12), 3348\u20133356 (2012)","journal-title":"IEEE T. Biomed. Eng."},{"key":"66_CR19","unstructured":"Viola, P., Platt, J., Zhang, C.: Multiple instance boosting for object detection. In: NIPS, pp. 1417\u20131424 (2005)"},{"issue":"5","key":"66_CR20","first-page":"1141","volume":"31","author":"S. Wang","year":"2012","unstructured":"Wang, S., et al.: Seeing is believing: Video classification for computed tomographic colonography using multiple-instance learning. TMI\u00a031(5), 1141\u20131153 (2012)","journal-title":"TMI"},{"key":"66_CR21","doi-asserted-by":"crossref","unstructured":"Wu, D., Bi, J., Boyer, K.: A min-max framework of cascaded classifier with multiple instance learning for computer aided diagnosis. In: CVPR, pp. 1359\u20131366 (2009)","DOI":"10.1109\/CVPR.2009.5206778"},{"issue":"3","key":"66_CR22","first-page":"591","volume":"18","author":"Y. Xu","year":"2014","unstructured":"Xu, Y., et al.: Weakly supervised histopathology cancer image segmentation and classification. MedIA\u00a018(3), 591\u2013604 (2014)","journal-title":"MedIA"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-24553-9_66","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T19:53:38Z","timestamp":1748634818000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-24553-9_66"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319245522","9783319245539"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-24553-9_66","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"18 November 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}