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.
| Original language | English |
|---|---|
| Article number | 064003 |
| Journal | Measurement Science and Technology |
| Volume | 29 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 19 Apr 2018 |
| Publication type | A1 Journal article-refereed |
Funding
This work was supported by the São Paulo Research Foundation (FAPESP grants 2013/18915-5 and 2016/25750-0), the Brazilian Foundation for the Coordination of Improvement of Higher Education Personnel (CAPES grant 88881.030443/ 2013-01), the Burroughs Wellcome Fund (IRSA 1016451), the Komen Foundation (grant IIRI326610), the National Institutes of Health and National Cancer Institute (grant 1R01CA154444), the Academy of Finland (project 310779), and the European Commission (FP7-PEOPLE-ITN-2013-607290).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- denoising
- digital breast tomosynthesis
- dose reduction
- variance stabilization
Publication forum classification
- Publication forum level 2
ASJC Scopus subject areas
- Instrumentation
- Engineering (miscellaneous)
- Applied Mathematics
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