{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,18]],"date-time":"2025-10-18T20:55:09Z","timestamp":1760820909979,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319598758"},{"type":"electronic","value":"9783319598765"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-3-319-59876-5_9","type":"book-chapter","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T01:09:35Z","timestamp":1496279375000},"page":"71-78","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Probabilistic Segmentation of Brain White Matter Lesions Using Texture-Based Classification"],"prefix":"10.1007","author":[{"given":"Mariana","family":"Bento","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Sym","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Frayne","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roberto","family":"Lotufo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Let\u00edcia","family":"Rittner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,6,2]]},"reference":[{"issue":"6","key":"9_CR1","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1002\/ana.21483","volume":"64","author":"S Appenzeller","year":"2008","unstructured":"Appenzeller, S., Li, L.M., Faria, A.V., Costallat, L.T., Cendes, F.: Quantitative magnetic resonance imaging analyses and clinical significance of hyperintense white matter lesions in systemic lupus erythematosus patients. Ann. Neurol. 64(6), 635\u2013643 (2008)","journal-title":"Ann. Neurol."},{"issue":"18","key":"9_CR2","doi-asserted-by":"publisher","first-page":"1821","DOI":"10.1056\/NEJMoa070972","volume":"357","author":"MW Vernooij","year":"2007","unstructured":"Vernooij, M.W., Arfan Ikram, M., Tanghe, H.L., Vincent, A.J.P.E., Hofman, A., Krestin, G.P., Niessen, W.J., Breteler, M.M.B., Lugt, A.: Incidental findings on brain MRI in the general population. New Engl. J. Med. 357(18), 1821\u20131828 (2007)","journal-title":"New Engl. J. Med."},{"issue":"1","key":"9_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/450341","volume":"2015","author":"I Despotovic","year":"2015","unstructured":"Despotovic, I., Goossens, B., Philips, W.: MRI segmentation of the human brain: challenges, methods, and applications. Comput. Math. Methods in Med. 2015(1), 1\u201323 (2015)","journal-title":"Comput. Math. Methods in Med."},{"issue":"10","key":"9_CR4","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1007\/s00234-015-1552-2","volume":"57","author":"E Roura","year":"2015","unstructured":"Roura, E., Oliver, A., Cabezas, M., Valverde, S., Pareto, D., Vilanova, J., Rami\u00f3-Torrent\u00e0, L., Rovira, A., Llad\u00f3, X.: A toolbox for multiple sclerosis lesion segmentation. Neuroradiology 57(10), 1031\u20131043 (2015)","journal-title":"Neuroradiology"},{"key":"9_CR5","first-page":"2015","volume":"1\u201314","author":"K Oppedal","year":"2015","unstructured":"Oppedal, K., Eftestol, T., Engan, K., Beyer, M., Aarsland, D.: Classifying dementia using local binary patterns from different regions in magnetic resonance images. Int. J. Biomed. Imaging 1\u201314, 2015 (2015)","journal-title":"Int. J. Biomed. Imaging"},{"issue":"1","key":"9_CR6","first-page":"20","volume":"3","author":"C Loizou","year":"2013","unstructured":"Loizou, C., Pantziaris, M., Pattichis, C., Seimenis, I.: Brain MR image normalization in texture analysis of multiple sclerosis. J. Biomed. Graph. Comput. 3(1), 20 (2013)","journal-title":"J. Biomed. Graph. Comput."},{"issue":"2","key":"9_CR7","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1016\/j.neuroimage.2011.04.053","volume":"57","author":"S Kloppel","year":"2011","unstructured":"Kloppel, S., Abdulkadir, A., Hadjidemetriou, S., Issleib, S., Frings, L., Thanh, T.N., Mader, I., Teipel, S.J., Hull, M., Ronnebeger, O.: A comparison of different automated methods for the detection of white matter lesions in MRI data. Neuroimage 57(2), 416\u2013422 (2011)","journal-title":"Neuroimage"},{"key":"9_CR8","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1016\/j.nicl.2013.10.003","volume":"3","author":"M Steenwijk","year":"2013","unstructured":"Steenwijk, M., Pouwels, P., Daams, M., Dalen, J., Caan, M., Richard, E., Barkhof, F., Vrenken, H.: Accurate white matter lesion segmentation by k nearest neighbor classification with tissue type priors (kNN-TTPs). NeuroImage: Clin. 3, 462\u2013469 (2013)","journal-title":"NeuroImage: Clin."},{"issue":"3","key":"9_CR9","doi-asserted-by":"publisher","first-page":"1037","DOI":"10.1016\/j.neuroimage.2003.10.012","volume":"21","author":"P Anbeek","year":"2004","unstructured":"Anbeek, P., Vincken, K.L., Osch, M.J.P., Bisschops, R.H.C., Grond, J.: Probabilistic segmentation of white matter lesions in MR imaging. NeuroImage 21(3), 1037\u20131044 (2004)","journal-title":"NeuroImage"},{"key":"9_CR10","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.media.2016.07.009","volume":"35","author":"O Maier","year":"2017","unstructured":"Maier, O., Menze, B.H., von der Gablentz, J., H\u00e4ni, L., Heinrich, M.P., Liebrand, M., Winzeck, S., Basit, A., Bentley, P., Chen, L., Christiaens, D., Dutil, F., Egger, K., Feng, C., Glocker, B., G\u00f6tz, M., Haeck, T., Halme, H.L., Havaei, M., Iftekharuddin, K.M., Jodoin, P.M., Kamnitsas, K., Kellner, E., Korvenoja, A., Larochelle, H., Ledig, C., Lee, J.H., Maes, F., Mahmood, Q., Maier-Hein, K.H., McKinley, R., Muschelli, J., Pal, C., Pei, L., Rangarajan, J.R., Reza, S.M., Robben, D., Rueckert, D., Salli, E., Suetens, P., Wang, C.W., Wilms, M., Kirschke, J.S., Kr\u00e4mer, U.M., M\u00fcnte, T.F., Schramm, P., Wiest, R., Handels, H., Reyes, M.: ISLES 2015 - a public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI. Med. Image Anal. 35, 250\u2013269 (2017)","journal-title":"Med. Image Anal."},{"issue":"8","key":"9_CR11","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/42.796284","volume":"18","author":"D Rueckert","year":"1999","unstructured":"Rueckert, D., Sonoda, L., Hayes, C., Hill, D., Leach, M., Hawkes, D.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imaging 18(8), 712\u2013721 (1999)","journal-title":"IEEE Trans. Med. Imaging"},{"unstructured":"Lu, Q., Gobbi, D., Frayne. R., Salluzzi, M.: Cerebra-WML: a stand-alone application for quantification of white matter lesion. In: Proceedings of Imaging Network Ontario Symposium (2014)","key":"9_CR12"},{"key":"9_CR13","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.neuroimage.2016.07.018","volume":"141","author":"L Griffanti","year":"2016","unstructured":"Griffanti, L., Zamboni, G., Khan, A., Li, L., Bonifacio, G., Sundaresan, V., Schulz, U., Kuker, W., Battaglini, M., Rothwell, P., Jenkinson, M.: BIANCA (Brain Intensity Abnormality Classification Algorithm): a new tool for automated segmentation of white matter hyperintensities. NeuroImage 141, 191\u2013205 (2016)","journal-title":"NeuroImage"},{"issue":"1","key":"9_CR14","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in python. J. Mach. Learn. Res. 12(1), 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"9_CR15","volume-title":"Digital Image Processing","author":"R Woods","year":"2000","unstructured":"Woods, R., Gonzalez, R.C.: Digital Image Processing. Edgard Blucher, S\u00e3o Paulo (2000)"},{"key":"9_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/978-3-319-30858-6_17","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"M Havaei","year":"2016","unstructured":"Havaei, M., Dutil, F., Pal, C., Larochelle, H., Jodoin, P.-M.: A convolutional neural network approach to brain tumor segmentation. In: Crimi, A., Menze, B., Maier, O., Reyes, M., Handels, H. (eds.) BrainLes 2015. LNCS, vol. 9556, pp. 195\u2013208. Springer, Cham (2016). doi:10.1007\/978-3-319-30858-6_17"},{"unstructured":"Kamnitsas, K., Chen, L., Ledig, C., Rueckert, D., Glocker, B.: Multi-scale 3D convolutional neural networks for lesion segmentation in brain MRI. In: Proceedings of Ischemic Stroke Lesion Segmentation Challenge, Held in Conjunction with International Conference on Medical Image Computing and Computer Assisted Intervention 2015 (2015)","key":"9_CR17"},{"unstructured":"Chen, L., Bentley, P., Rueckert, D.: A novel framework for sub-acute stroke lesion segmentation based on random forest. In: Proceedings of Ischemic Stroke Lesion Segmentation Challenge, Held in Conjunction with International Conference on Medical Image Computing and Computer Assisted Intervention 2015 (2015)","key":"9_CR18"},{"doi-asserted-by":"crossref","unstructured":"Feng, C., Zhao, D., Huang, M.: Segmentation of stroke lesions in multi-spectral MR images using bias correction embedded FCM and three phase level set. In: Proceedings of Ischemic Stroke Lesion Segmentation Challenge, Held in Conjunction with International Conference on Medical Image Computing and Computer Assisted Intervention 2015 (2015)","key":"9_CR19","DOI":"10.1007\/978-3-319-30858-6_20"},{"key":"9_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/978-3-319-30858-6_18","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"H-L Halme","year":"2016","unstructured":"Halme, H.-L., Korvenoja, A., Salli, E.: ISLES (SISS) challenge 2015: segmentation of stroke lesions using spatial normalization, random forest classification and contextual clustering. In: Crimi, A., Menze, B., Maier, O., Reyes, M., Handels, H. (eds.) BrainLes 2015. LNCS, vol. 9556, pp. 211\u2013221. Springer, Cham (2016). doi:10.1007\/978-3-319-30858-6_18"}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-59876-5_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T12:03:33Z","timestamp":1715861013000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-59876-5_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319598758","9783319598765"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-59876-5_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"2 June 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Montreal, QC","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":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciar2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.aimiconf.org\/iciar17\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}