{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T03:58:42Z","timestamp":1785556722476,"version":"3.56.0"},"reference-count":34,"publisher":"IOP Publishing","issue":"9","license":[{"start":{"date-parts":[[2017,4,11]],"date-time":"2017-04-11T00:00:00Z","timestamp":1491868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2017,4,11]],"date-time":"2017-04-11T00:00:00Z","timestamp":1491868800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"European Union\u2019s Seventh Framework Programme FP7","award":["306088"],"award-info":[{"award-number":["306088"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2017,5,7]]},"abstract":"Abstract<\/jats:title>\n Fibroglandular tissue volume and percent density can be estimated in unprocessed mammograms using a physics-based method, which relies on an internal reference value representing the projection of fat only. However, pixels representing fat only may not be present in dense breasts, causing an underestimation of density measurements. In this work, we investigate alternative approaches for obtaining a tissue reference value to improve density estimations, particularly in dense breasts.<\/jats:p>\n \n Two of three investigated reference values (\n F<\/jats:italic>\n 1,\n F<\/jats:italic>\n 2) are percentiles of the pixel value distribution in the breast interior (the contact area of breast and compression paddle).\n F<\/jats:italic>\n 1 is determined in a small breast interior, which minimizes the risk that peripheral pixels are included in the measurement at the cost of increasing the chance that no proper reference can be found.\n F<\/jats:italic>\n 2 is obtained using a larger breast interior. The new approach which is developed for very dense breasts does not require the presence of a fatty tissue region. As reference region we select the densest region in the mammogram and assume that this represents a projection of entirely dense tissue embedded between the subcutaneous fatty tissue layers. By measuring the thickness of the fat layers a reference (\n F<\/jats:italic>\n 3) can be computed. To obtain accurate breast density estimates irrespective of breast composition we investigated a combination of the results of the three reference values. We collected 202 pairs of MRI\u2019s and digital mammograms from 119 women. We compared the percent dense volume estimates based on both modalities and calculated Pearson\u2019s correlation coefficients.\n <\/jats:p>\n \n With the references\n F<\/jats:italic>\n 1\u2013\n F<\/jats:italic>\n 3 we found respectively a correlation of\n \n \n \n <\/jats:tex-math>\n \n \n \n R<\/mml:mi>\n <\/mml:mrow>\n =<\/mml:mo>\n 0.80<\/mml:mn>\n <\/mml:mstyle>\n <\/mml:math>\n <\/jats:inline-formula>\n ,\n \n \n \n <\/jats:tex-math>\n \n \n \n R<\/mml:mi>\n <\/mml:mrow>\n =<\/mml:mo>\n 0.89<\/mml:mn>\n <\/mml:mstyle>\n <\/mml:math>\n <\/jats:inline-formula>\n and\n \n \n \n <\/jats:tex-math>\n \n \n \n R<\/mml:mi>\n <\/mml:mrow>\n =<\/mml:mo>\n 0.74<\/mml:mn>\n <\/mml:mstyle>\n <\/mml:math>\n <\/jats:inline-formula>\n . Best results were obtained with the combination of the density estimations (\n \n \n \n <\/jats:tex-math>\n \n \n \n R<\/mml:mi>\n <\/mml:mrow>\n =<\/mml:mo>\n 0.90<\/mml:mn>\n <\/mml:mstyle>\n <\/mml:math>\n <\/jats:inline-formula>\n ).\n <\/jats:p>\n Results show that better volumetric density estimates can be obtained with the hybrid method, in particular for dense breasts, when algorithms are combined to obtain a fatty tissue reference value depending on breast composition.<\/jats:p>","DOI":"10.1088\/1361-6560\/aa628f","type":"journal-article","created":{"date-parts":[[2017,2,23]],"date-time":"2017-02-23T13:13:11Z","timestamp":1487855591000},"page":"3779-3797","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Optimization of volumetric breast density estimation in digital mammograms"],"prefix":"10.1088","volume":"62","author":[{"given":"Katharina","family":"Holland","sequence":"first","affiliation":[{"name":"Radboud University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Albert","family":"Gubern-M\u00e9rida","sequence":"additional","affiliation":[{"name":"Radboud University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ritse M","family":"Mann","sequence":"additional","affiliation":[{"name":"Radboud University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nico","family":"Karssemeijer","sequence":"additional","affiliation":[{"name":"Radboud University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2017,4,11]]},"reference":[{"key":"pmbaa628fbib001","doi-asserted-by":"publisher","first-page":"7443","DOI":"10.1088\/0031-9155\/57\/22\/7443","type":"journal-article","article-title":"Volumetric breast density characteristics as determined from digital mammograms","volume":"57","author":"Alonzo-Proulx","year":"2012","journal-title":"Phys. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2016-04-14","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2017-02-23","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2017-04-11","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}