@inproceedings{c90357038b324baab4feb1d460a1b4aa,
title = "Breast density assessment using breast tomosynthesis images",
abstract = "In this work we evaluate an approach for breast density assessment of digital breast tomosynthesis (DBT) data using the central projection image. A total of 348 random cases (both FFDM CC and MLO views and DBT MLO views) were collected using a Siemens Mammomat Inspiration tomosynthesis unit at Unilabs, Malm{\"o}. The cases underwent both BI-RADS 5th Edition labeling by radiologists and automated volumetric breast density analysis (VBDA) by an algorithm. Preliminary results showed an observed agreement of 70% (weighted Kappa, κ = 0.73) between radiologists and VBDA using FFDM images and 63% (κ = 0.62) for radiologists and VBDA using DBT images. Comparison between densities for FFDM and DBT resulted in high correlation (r = 0.94) and an observed agreement of 72% (κ = 0.76). The automated analysis is a promising approach using low dose central projection DBT images in order to get radiologist- like density ratings similar to results obtained from FFDM.",
keywords = "BI-RADS, Breast density, Breast tomosynthesis, Mammography",
author = "Pontus Timberg and Andreas Fieselmann and Magnus Dustler and Hannie Petersson and Hanna Sartor and Kristina L{\aa}ng and Daniel F{\"o}rnvik and Sophia Zackrisson",
year = "2016",
doi = "10.1007/978-3-319-41546-8_26",
language = "English",
isbn = "9783319415451",
volume = "9699",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "197--202",
editor = "Tingberg, {Anders } and Kristina L{\aa}ng and Pontus Timberg",
booktitle = "Breast Imaging",
address = "Germany",
note = "13th International Workshop on Breast Imaging, IWDM 2016 ; Conference date: 19-06-2016 Through 22-06-2016",
}