{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T17:15:10Z","timestamp":1790270110711,"version":"4.1.0"},"reference-count":21,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2007,2,5]],"date-time":"2007-02-05T00:00:00Z","timestamp":1170633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2007,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To investigate the use of four\u2010dimensional (4D) co\u2010occurrence\u2010based texture analysis to distinguish between nonmalignant and malignant tissues in dynamic contrast\u2010enhanced (DCE) MR images.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>4D texture analysis was performed on DCE\u2010MRI data sets of breast lesions. A model\u2010free neural network\u2010based classification system assigned each voxel a \u201cnonmalignant\u201d or \u201cmalignant\u201d label based on the textural features. The classification results were compared via receiver operating characteristic (ROC) curve analysis with the manual lesion segmentation produced by two radiologists (observers 1 and 2).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The mean sensitivity and specificity of the classifier agreed with the mean observer 2 performance when compared with segmentations by observer 1 for a 95% confidence interval, using a two\u2010sided <jats:italic>t<\/jats:italic>\u2010test with \u03b1 = 0.05. The results show that an area under the ROC curve (<jats:italic>A<\/jats:italic><jats:sub><jats:italic>z<\/jats:italic><\/jats:sub>) of 0.99948, 0.99867, and 0.99957 can be achieved by comparing the classifier vs. observer 1, classifier vs. union of both observers, and classifier vs. intersection of both observers, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study shows that a neural network classifier based on 4D texture analysis inputs can achieve a performance comparable to that achieved by human observers, and that further research in this area is warranted. J. Magn. Reson. Imaging 2007. \u00a9 2007 Wiley\u2010Liss, Inc.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.20837","type":"journal-article","created":{"date-parts":[[2007,2,5]],"date-time":"2007-02-05T18:18:14Z","timestamp":1170699494000},"page":"495-501","source":"Crossref","is-referenced-by-count":74,"title":["Malignant\u2010lesion segmentation using 4D co\u2010occurrence texture analysis applied to dynamic contrast\u2010enhanced magnetic resonance breast image data"],"prefix":"10.1002","volume":"25","author":[{"given":"Brent J.","family":"Woods","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bradley D.","family":"Clymer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tahsin","family":"Kurc","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johannes T.","family":"Heverhagen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Stevens","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adem","family":"Orsdemir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Orhan","family":"Bulan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael V.","family":"Knopp","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2007,2,5]]},"reference":[{"key":"e_1_2_5_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2586(200003)11:3<233::AID-JMRI1>3.0.CO;2-X"},{"key":"e_1_2_5_3_2","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/S0033-8389(22)02488-5","article-title":"Breast masses: mammographic and sonographic evaluation","volume":"30","author":"Feig SA","year":"1992","journal-title":"Radiol Clin N Am"},{"key":"e_1_2_5_4_2","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.73.872.11026854"},{"key":"e_1_2_5_5_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.213.2.r99nv49317"},{"key":"e_1_2_5_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/0730-725X(93)90205-R"},{"key":"e_1_2_5_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.10496"},{"key":"e_1_2_5_8_2","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.10259"},{"key":"e_1_2_5_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0730-725X(02)00464-2"},{"key":"e_1_2_5_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0730-725X(01)00222-3"},{"key":"e_1_2_5_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2005.854517"},{"key":"e_1_2_5_12_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.210.1.r99ja18233"},{"key":"e_1_2_5_13_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2594(200001)43:1<9::AID-MRM2>3.0.CO;2-C"},{"key":"e_1_2_5_14_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.10161"},{"key":"e_1_2_5_15_2","doi-asserted-by":"publisher","DOI":"10.1097\/00004728-199107000-00018"},{"key":"e_1_2_5_16_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2586(199912)10:6<903::AID-JMRI1>3.0.CO;2-A"},{"key":"e_1_2_5_17_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.211.1.r99ap38101"},{"key":"e_1_2_5_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/MEMB.2004.1360410"},{"key":"e_1_2_5_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1980.4767008"},{"key":"e_1_2_5_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1973.4309314"},{"key":"e_1_2_5_21_2","unstructured":"WoodsBJ ClymerB SaltzJ KurcT.A parallel implementation of 4Dimensional Haralick texture analysis for disk\u2010resident image datasets. 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