@inproceedings{99ce14ae42944aec93365eec7be60f97,
title = "A Multiscale Blob Representation of Mammographic Parenchymal Patterns and Mammographic Risk Assessment",
abstract = "Mammographic parenchymal patterns have been found to be a strong indicator of breast cancer risk and play an important role in mammographic risk assessment. In this paper, a novel representation of mammographic parenchymal patterns is proposed, which is based on multiscale blobs. Approximately blob-like tissue patterns are detected over a range of scales and parenchymal patterns are represented as a set of blobs. Spatial relations between blobs are considered to reduce the overlap between connected dense tissue regions. Quantitative measures of breast density are calculated from the resulting blobs and used for mammographic risk assessment. The proposed approach is evaluated using the full MIAS database and a large dataset from the DDSM database. A high agreement with expert radiologists is indicated according to the BIRADS density classification. The classification accuracies for the MIAS and DDSM databases are up to 79.44% and 76.90%, respectively.",
keywords = "breast density, mammographic parenchymal patterns, mammographic risk assessment, multiscale blob detection",
author = "Zhili Chen and Liping Wang and Denton, {Erika R. E.} and Reyer Zwiggelaar",
year = "2013",
month = aug,
day = "7",
doi = "10.1007/978-3-642-40246-3_43",
language = "English",
isbn = "978-3-642-40245-6",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
number = "PART 2",
pages = "346--353",
editor = "Richard Wilson and Edwin Hancock and Bors, {Adrian } and William Smith",
booktitle = "Computer Analysis of Images and Patterns - 15th International Conference, CAIP 2013, Proceedings",
address = "Switzerland",
edition = "PART 2",
}
