Digital Breast Tomosynthesis: Towards Dose Reduction through Image Quality Improvement

Author:

Mota Ana M.1ORCID,Mendes João12ORCID,Matela Nuno1ORCID

Affiliation:

1. Faculdade de Ciências, Instituto de Biofísica e Engenharia Biomédica, Universidade de Lisboa, 1749-016 Lisboa, Portugal

2. Faculdade de Ciências, LASIGE, Universidade de Lisboa, 1749-016 Lisboa, Portugal

Abstract

Currently, breast cancer is the most commonly diagnosed type of cancer worldwide. Digital Breast Tomosynthesis (DBT) has been widely accepted as a stand-alone modality to replace Digital Mammography, particularly in denser breasts. However, the image quality improvement provided by DBT is accompanied by an increase in the radiation dose for the patient. Here, a method based on 2D Total Variation (2D TV) minimization to improve image quality without the need to increase the dose was proposed. Two phantoms were used to acquire data at different dose ranges (0.88–2.19 mGy for Gammex 156 and 0.65–1.71 mGy for our phantom). A 2D TV minimization filter was applied to the data, and the image quality was assessed through contrast-to-noise ratio (CNR) and the detectability index of lesions before and after filtering. The results showed a decrease in 2D TV values after filtering, with variations of up to 31%, increasing image quality. The increase in CNR values after filtering showed that it is possible to use lower doses (−26%, on average) without compromising on image quality. The detectability index had substantial increases (up to 14%), especially in smaller lesions. So, not only did the proposed approach allow for the enhancement of image quality without increasing the dose, but it also improved the chances of detecting small lesions that could be overlooked.

Funder

Fundação para a Ciência e Tecnologia—Portugal

Bolsa de Investigação para Doutoramento FCT

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging

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2. Image Quality Assessment of Breast Cancer with Various Modalities;2023 International Conference on Modeling, Simulation & Intelligent Computing (MoSICom);2023-12-07

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