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- W1491858253 abstract "A novel method for accurate detection of regions of interest (ROIs) that contain circumscribed lesions in mammograms is presented. The mammograms are segmented using a statistical threshold and a number of candidate regions are extracted. Then a set of qualification criteria is employed to filter these regions retaining the most suspicious for which a radial-basis function neural network makes the final decision marking them as ROIs that contain abnormal tissue. The proposed method detects the exact location of the circumscribed lesions with an accuracy of 90.9%, and a very low number of false positive regions per image (2.1 ROIs per image) in the MIAS database." @default.
- W1491858253 created "2016-06-24" @default.
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- W1491858253 date "2002-11-13" @default.
- W1491858253 modified "2023-09-27" @default.
- W1491858253 title "Automatic detection of abnormal tissue in mammography" @default.
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- W1491858253 doi "https://doi.org/10.1109/icip.2001.958634" @default.
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