Published April 16, 2024 | Version v1
Dataset Open

Dataset related to article "Phantom‑based analysis of variations in automatic exposure control across three mammography systems: implications for radiation dose and image quality in mammography, DBT, and CEM"

  • 1. ROR icon Istituto Oncologico Veneto

Description

The dataset comprises  information from several DICOM tags extracted from digital mammography (DM), digital breast tomosynthesis (DBT), and contrast-enhanced mammography (CEM) images acquired in a phantom study aimed at characterizing the automatic exposure control (AEC) behavior of diverse mammography equipment. The final ten columns of the datasets encompass signal (mena pixel values, MPV) and noise (standard deviation, SD) measurements derived from phantom images. These measurements are used to compute several image quality metrics, including contrast, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), CNR relative difference in comparison to the 45 mm reference thickness, and a figure of merit (FOM) obtained by diving the squared CNR by the mean glandular dose (MGD).

Files

AEC_raw_data - CEM.csv

Files (162.0 kB)

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md5:0a7f7aa3b69456669e67995c1bface4e
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md5:11bc59a38d60e4e1a09aee6bfa6d4b53
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md5:3a226eea0543ec36a7d668027791086c
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Additional details

Related works

Is published in
Publication: 10.1186/s41747-024-00447-z (DOI)