Mammogram Density Assessment Dataset

Published: 8 April 2024| Version 4 | DOI: 10.17632/tdx3h2fn9v.4
Contributors:
Hamid Behravan,
,
,

Description

This dataset consists of mammogram images, complete with corresponding segmentation masks for dense tissue and breast area annotated by an expert radiologist. *Files* train.zip: Comprises three sub-folders: 'images', 'breast_masks', and 'dense_masks'. The 'images' sub-folder houses the original images. The 'breast_masks' and 'dense_masks' sub-folders contain the ground truth segmentation masks for the breast area and dense tissue segmentation, respectively. All images are in JPG format. All masks and the corresponding images have the same dimension. test.zip: Contains the images for test set in JPG format. No ground truths are provided for the test set. *File lists* train.csv: The training set filelist consists of two columns. The first column is the ‘Filename’, and the second column is the ‘Density', the ground truth for the breast density prediction task. test.csv: The test set filelist contains the filenames of the test sets. This dataset can be utilized for tasks such as segmentation and breast density estimation. The mammograms were sourced from the public VinDr-Mammo dataset, which can be found at [this link](^https://vindr.ai/datasets/mammo^). We have given annotations, including both segmentation masks and density values, for this public dataset. If you use this dataset in your research or other purposes, please cite the following studies: Gudhe, N.R., Behravan, H., Sudah, M. et al. Area-based breast percentage density estimation in mammograms using weight-adaptive multitask learning. Sci Rep 12, 12060 (2022). https://doi.org/10.1038/s41598-022-16141-2 Hieu T. Nguyen et al. “A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography”. 2022. https://doi.org/10.1101/2022.03.07.22272009

Files

Institutions

Ita-Suomen yliopisto

Categories

Image Segmentation, Breast Imaging, Image Analysis (Medical Imaging), Breast Density, Deep Learning, Image Analysis

Funding

Finnish Innovation Fund - Sitra

29330000451

Licence