{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T22:43:56Z","timestamp":1648939436794},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2015,3,1]],"date-time":"2015-03-01T00:00:00Z","timestamp":1425168000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,3,1]]},"abstract":"Abstract<\/jats:title>\n In automated image processing the intensity inhomogeneity of MR images causes significant errors. In this work we analyze three algorithms with the purpose of intensity inhomogeneity correction. The well-known N3 algorithm is compared to two more recent approaches: a modified level set method, which is able to deal with intensity inhomogeneity and it is, as well, compared to an adaptation of the fuzzy c-means clustering with intensity inhomogeneity compensation techniques. We evaluate the outcomes of these three algorithms with quantitative performance measures. The measurements are done on the bias fields and on the segmented images. We consider normal brain images obtained from the Montreal Simulated Brain Database.<\/jats:p>","DOI":"10.1515\/macro-2015-0008","type":"journal-article","created":{"date-parts":[[2018,5,3]],"date-time":"2018-05-03T11:45:39Z","timestamp":1525347939000},"page":"79-90","source":"Crossref","is-referenced-by-count":1,"title":["An Atlas Based Performance Evaluation of Inhomogeneity Correcting Effects"],"prefix":"10.1515","volume":"1","author":[{"given":"L\u00e1szl\u00f3","family":"Lefkovits","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Technical and Human Sciences, Sapientia University, Tg. Mure\u015f"}]},{"given":"Szid\u00f3nia","family":"Lefkovits","sequence":"additional","affiliation":[{"name":"Department Informatics, Faculty of Science and Letters, \u201cPetru Maior\u201d University, Tg. Mure\u015f"}]},{"given":"Mircea-Florin","family":"Vaida","sequence":"additional","affiliation":[{"name":"Department of Communications, Technical University of Cluj-Napoca"}]}],"member":"374","published-online":{"date-parts":[[2015,5,9]]},"container-title":["MACRo 2015"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/content.sciendo.com\/view\/journals\/macro\/1\/1\/article-p79.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/macro-2015-0008","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T03:08:38Z","timestamp":1617764918000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/macro-2015-0008"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,5,9]]},"published-print":{"date-parts":[[2015,3,1]]}},"alternative-id":["10.1515\/macro-2015-0008"],"URL":"https:\/\/doi.org\/10.1515\/macro-2015-0008","relation":{},"ISSN":["2247-0948"],"issn-type":[{"value":"2247-0948","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,3,1]]}}}