@inproceedings{39dc13f1b0614ae49cf178422a687a57,
title = "Risk Classification of Mammograms Using Anatomical Linear Structure and Density Information",
abstract = "Mammographic risk assessment is concerned with the probability of a woman developing breast cancer. Recently, it has been suggested that the density of linear structures is related to risk. For 321 images from the MIAS database, the images were segmented in to dense and non-dense tissue using a method described by Sivaramakrishna, et al. In addition, a measure of line strength was obtained for each pixel using the Line Operator method. The above-threshold linearity was calculated in dense and non-dense tissue for each image and the images were then classified by BIRADS class using linear discriminant analysis. The results show a marked improvement when both density and linear structure information is used in classification over density information alone.",
keywords = "biomedical imaging, classifier systems, document analysis, face recognition, feature extraction, filtering, fuzzy logic, image analysis, image processing, image segementation, inforation theory, machine translation, modeling, neural network, pattern recognition",
author = "Hadley, {Edward Michael} and Denton, {Erika R. E.} and Josep Pont and Elsa P{\'e}rez and Reyer Zwiggelaar",
year = "2007",
month = may,
day = "31",
doi = "10.1007/978-3-540-72849-8_24",
language = "English",
isbn = "978-3-540-72848-1",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "186--193",
editor = "Joan Mart{\'i} and Bened{\'i}, {Jos{\'e} Miguel} and Mendon{\c c}a, {Ana Maria} and Joan Serrat",
booktitle = "Pattern Recognition and Image Analysis",
address = "Switzerland",
note = "Third Iberian Conference, IbPRIA 2007 : Pattern Recognition and Image Analysis ; Conference date: 06-06-2007 Through 08-06-2007",
}
