{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T11:45:00Z","timestamp":1791114300577,"version":"4.1.0"},"reference-count":44,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2000,1,6]],"date-time":"2000-01-06T00:00:00Z","timestamp":947116800000},"content-version":"vor","delay-in-days":5,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2000,1]]},"abstract":"<jats:p>Our purpose in this study was to identify computer\u2010extracted, mammographic parenchymal patterns that are associated with breast cancer risk. We extracted 14 features from the central breast region on digitized mammograms to characterize the mammographic parenchymal patterns of women at different risk levels. Two different approaches were employed to relate these mammographic features to breast cancer risk. In one approach, the features were used to distinguish mammographic patterns seen in low\u2010risk women from those who inherited a mutated form of the BRCA1\/BRCA2 gene, which confers a very high risk of developing breast cancer. In another approach, the features were related to risk as determined from existing clinical models (<jats:italic>Gail<\/jats:italic> and <jats:italic>Claus<\/jats:italic> models), which use well\u2010known epidemiological factors such as a woman's age, her family history of breast cancer, reproductive history, etc. Stepwise linear discriminant analysis was employed to identify features that were useful in differentiating between \u201clow\u2010risk\u201d women and BRCA1\/BRCA2\u2010mutation carriers. Stepwise linear regression analysis was employed to identify useful features in predicting the risk, as estimated from the <jats:italic>Gail<\/jats:italic> and <jats:italic>Claus<\/jats:italic> models. Similar computer\u2010extracted mammographic features were identified in the two approaches. Results show that women at high risk tend to have dense breasts and their mammographic patterns tend to be coarse and low in contrast.<\/jats:p>","DOI":"10.1118\/1.598851","type":"journal-article","created":{"date-parts":[[2002,7,26]],"date-time":"2002-07-26T14:01:44Z","timestamp":1027692104000},"page":"4-12","source":"Crossref","is-referenced-by-count":67,"title":["Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: Feature selection"],"prefix":"10.1002","volume":"27","author":[{"given":"Zhimin","family":"Huo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryellen L.","family":"Giger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dulcy E.","family":"Wolverton","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiming","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shelly","family":"Cumming","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olufunmilayo I.","family":"Olopade","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2000,1,6]]},"reference":[{"key":"e_1_2_1_2_1","unstructured":"American Cancer Society Cancer Facts and Figures\u20141998 New York 1998 p. 20."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(19890101)63:1<181::AID-CNCR2820630129>3.0.CO;2-H"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/0002-9610(94)90241-0"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(19920401)69:7 <1919::AID-CNCR2820691708>3.0.CO;2-M"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(19950401)75:7<1619::AID-CNCR2820750711>3.0.CO;2-T"},{"key":"e_1_2_1_7_1","unstructured":"J. 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