Actas de congresos
Investigating poisson noise filtering in Digital Breast Tomosynthesis
Date
2013Registration in:
Workshop de Visão Computacional - WVC , IX, 2013, Rio de Janeiro
Author
Vieira, Marcelo Andrade da Costa
Bakic, Predrag R
Maidment, Andrew Douglas Arnold
Mascarenhas, Nelson Delfino d’Ávila
Institutions
Abstract
Digital Breast Tomosynthesis (DBT) is a potential
candidate to substitute digital mammography in breast cancer
screening. In DBT, projection images are acquired with low
levels of radiation, which significantly increases image noise. In
this work, we evaluate the effect of a denoising filter, designed for
digital mammography, on the reduction of quantum noise in
DBT images. This filter is based on an adaptive Wiener filter and
the Anscombe transformation, to reduce Poisson noise without
significantly affecting image sharpness. Denoising was applied to
a set of synthetic DBT images generated using a 3D
anthropomorphic software breast phantom. Images without noise
was also created to provide ground-truth information. In order to
evaluate the denoising performance in different steps of the DBT
imaging, filtering was applied separately to the projections
(before reconstruction) and to the tomographic slices (after
reconstruction). The performance of the filter was evaluated
considering qualitative and quantitative analysis of the images
before and after denoising.