by Lucas R Borges, Lucio Azzari, Predrag R Bakic, Andrew D A Maidment, Marcelo A C Vieira, Alessandro Foi
Abstract:
In breast cancer screening, the radiation dose must be kept to the minimum necessary to achieve the desired diagnostic objective, thus minimizing risks associated with cancer induction. However, decreasing the radiation dose also degrades the image quality. In this work we restore digital breast tomosynthesis (DBT) projections acquired at low radiation doses with the goal of achieving a quality comparable to that obtained from current standard full-dose imaging protocols. A multiframe denoising algorithm was applied to low-dose projections, which are filtered jointly. Furthermore, a weighted average was used to inject a varying portion of the noisy signal back into the denoised one, in order to attain a signal-to-noise ratio comparable to that of standard full-dose projections. The entire restoration framework leverages a signal-dependent noise model with quantum gain which varies both upon the projection angle and on the pixel position. A clinical DBT system and a 3D anthropomorphic breast phantom were used to validate the proposed method, both on DBT projections and slices from the 3D reconstructed volume. The framework is shown to attain the standard full-dose image quality from data acquired at 50\% lower radiation dose, whereas progressive loss of relevant details compromises the image quality if the dosage is further decreased.
Reference:
Lucas R Borges, Lucio Azzari, Predrag R Bakic, Andrew D A Maidment, Marcelo A C Vieira, Alessandro Foi, "Restoration of low-dose digital breast tomosynthesis", In Measurement Science and Technology, vol. 29, no. 6, pp. 064003, 2018.
Bibtex Entry:
@article{0957-0233-29-6-064003,
author={Lucas R Borges and Lucio Azzari and Predrag R Bakic and Andrew D A Maidment and Marcelo A C Vieira and Alessandro Foi},
title={Restoration of low-dose digital breast tomosynthesis},
journal={Measurement Science and Technology},
volume={29},
number={6},
pages={064003},
url={http://stacks.iop.org/0957-0233/29/i=6/a=064003},
year={2018},
doi={10.1088/1361-6501/aab2f6},
abstract={In breast cancer screening, the radiation dose must be kept to the minimum necessary to achieve the desired diagnostic objective, thus minimizing risks associated with cancer induction. However, decreasing the radiation dose also degrades the image quality. In this work we restore digital breast tomosynthesis (DBT) projections acquired at low radiation doses with the goal of achieving a quality comparable to that obtained from current standard full-dose imaging protocols. A multiframe denoising algorithm was applied to low-dose projections, which are filtered jointly. Furthermore, a weighted average was used to inject a varying portion of the noisy signal back into the denoised one, in order to attain a signal-to-noise ratio comparable to that of standard full-dose projections. The entire restoration framework leverages a signal-dependent noise model with quantum gain which varies both upon the projection angle and on the pixel position. A clinical DBT system and a 3D anthropomorphic breast phantom were used to validate the proposed method, both on DBT projections and slices from the 3D reconstructed volume. The framework is shown to attain the standard full-dose image quality from data acquired at 50\% lower radiation dose, whereas progressive loss of relevant details compromises the image quality if the dosage is further decreased.}
}