{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T05:12:10Z","timestamp":1696828330487},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2010,6,23]],"date-time":"2010-06-23T00:00:00Z","timestamp":1277251200000},"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":[[2010,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Purpose:<\/jats:title><jats:p>To develop and evaluate a computerized segmentation method for breast MRI (BMRI) mass\u2010lesions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods:<\/jats:title><jats:p>A computerized segmentation algorithm was developed to segment mass\u2010like\u2010lesions on breast MRI. The segmentation algorithm involved: (i) interactive lesion selection, (ii) automatic intensity threshold estimation, (iii) connected component analysis, and (iv) a postprocessing procedure for hole\u2010filling and leakage removal. Seven observers manually traced the borders of all slices of 30 mass\u2010lesions using the same tools. To initiate the computerized segmentation, each user selected a seed\u2010point for each lesion interactively using two methods: direct seed\u2010point and robust region of interest (ROI) selections. The manual and computerized segmentations were compared pair\u2010wise using the measured size and overlap to evaluate similarity, and the reproducibility of the computerized segmentation was compared with the interobserver variability of the manual delineations.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results:<\/jats:title><jats:p>The observed inter\u2010 and intraobserver variations were similar (<jats:italic>P<\/jats:italic> &gt; 0.05). Computerized segmentation using the robust ROI selection method was significantly (<jats:italic>P<\/jats:italic> &lt; 0.001) more reproducible in measuring lesion size (stDev 1.8%) than either manual contouring (11.7%) or computerized segmentation using directly placed seed\u2010point method (13.7%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion:<\/jats:title><jats:p>The computerized segmentation method using robust ROI selection is more reproducible than manual delineation in terms of measuring the size of a mass\u2010lesion. J. Magn. Reson. Imaging 2010;32:110\u2013119. \u00a9 2010 Wiley\u2010Liss, Inc.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.22206","type":"journal-article","created":{"date-parts":[[2010,6,24]],"date-time":"2010-06-24T12:37:09Z","timestamp":1277383029000},"page":"110-119","source":"Crossref","is-referenced-by-count":11,"title":["Robust segmentation of mass\u2010lesions in contrast\u2010enhanced dynamic breast MR images"],"prefix":"10.1002","volume":"32","author":[{"given":"Lina A.","family":"Meinel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Buelow","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dezheng","family":"Huo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akiko","family":"Shimauchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ursula","family":"Kose","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Johannes","family":"Buurman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gillian","family":"Newstead","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2010,6,23]]},"reference":[{"key":"e_1_2_6_2_2","unstructured":"American Cancer Society. 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