{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T15:59:39Z","timestamp":1762271979935},"reference-count":36,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["International Journal of Biomedical Imaging"],"published-print":{"date-parts":[[2016]]},"abstract":"<jats:p>This paper presents an automatic lesion segmentation method based on similarities between multichannel patches. A patch database is built using training images for which the label maps are known. For each patch in the testing image,<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi>k<\/mml:mi><\/mml:mrow><\/mml:math>similar patches are retrieved from the database. The matching labels for these<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>k<\/mml:mi><\/mml:mrow><\/mml:math>patches are then combined to produce an initial segmentation map for the test case. Finally an iterative patch-based label refinement process based on the initial segmentation map is performed to ensure the spatial consistency of the detected lesions. The method was evaluated in experiments on multiple sclerosis (MS) lesion segmentation in magnetic resonance images (MRI) of the brain. An evaluation was done for each image in the MICCAI 2008 MS lesion segmentation challenge. Results are shown to compete with the state of the art in the challenge. We conclude that the proposed algorithm for segmentation of lesions provides a promising new approach for local segmentation and global detection in medical images.<\/jats:p>","DOI":"10.1155\/2016\/7952541","type":"journal-article","created":{"date-parts":[[2016,1,24]],"date-time":"2016-01-24T16:02:03Z","timestamp":1453651323000},"page":"1-13","source":"Crossref","is-referenced-by-count":31,"title":["Patch-Based Segmentation with Spatial Consistency: Application to MS Lesions in Brain MRI"],"prefix":"10.1155","volume":"2016","author":[{"given":"Roey","family":"Mechrez","sequence":"first","affiliation":[{"name":"Biomedical Engineering Department, Tel-Aviv University, 69978 Tel Aviv, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacob","family":"Goldberger","sequence":"additional","affiliation":[{"name":"Engineering Faculty, Bar-Ilan University, 52900 Ramat Gan, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hayit","family":"Greenspan","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Department, Tel-Aviv University, 69978 Tel Aviv, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"98","reference":[{"key":"8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.09.018"},{"key":"30","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2011.2156806"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2004.833105"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1109\/38.988747"},{"key":"43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-02267-3_13"},{"key":"1","series-title":"Lecture Notes in Computer Science","first-page":"409","volume-title":"STREM: a robust multidimensional parametric method to segment MS lesions in MRI","volume":"8, part 1","year":"2005"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/121.1.3"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1177\/135245850401000107"},{"key":"47","doi-asserted-by":"publisher","DOI":"10.1007\/s002340000500"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2012.09.004"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.03.080"},{"key":"45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40811-3_92"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2258403"},{"key":"41","doi-asserted-by":"publisher","DOI":"10.1109\/42.938237"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2003.10.012"},{"key":"46","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.04.211"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/715124"},{"key":"38","first-page":"1","year":"2008","journal-title":"MIDAS Journal"},{"key":"36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.09.005"},{"issue":"1","key":"4","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.ijrobp.2004.08.055","volume":"61","year":"2005","journal-title":"International Journal of Radiation Oncology, Biology, Physics"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1002\/cnm.2537"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2011.08.047"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.11.032"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2012.2186639"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1109\/42.836373"},{"key":"40","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2010.2046908"},{"key":"34","doi-asserted-by":"publisher","DOI":"10.1016\/s1361-8415(02)00054-3"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20159"},{"key":"35","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.2000.0730"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2007.906087"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.02.018"},{"key":"44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-36620-8_10"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.11.040"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2012.05.001"},{"issue":"6","key":"22","first-page":"721","volume":"6","year":"1984","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"}],"container-title":["International Journal of Biomedical Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijbi\/2016\/7952541.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijbi\/2016\/7952541.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijbi\/2016\/7952541.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T00:25:06Z","timestamp":1498263906000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/ijbi\/2016\/7952541\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":36,"alternative-id":["7952541","7952541"],"URL":"https:\/\/doi.org\/10.1155\/2016\/7952541","relation":{},"ISSN":["1687-4188","1687-4196"],"issn-type":[{"value":"1687-4188","type":"print"},{"value":"1687-4196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016]]}}}