BIBLIOS

Document type
Journal articles

Document subtype
Full paper

Title
Impact of total variation minimization in volume rendering visualization of breast tomosynthesis data

Participants in the publication
A.M. Mota (Author)
IBEB
M.J. Clarkson (Author)
P. Almeida (Author)
IBEB
L. Peralta (Author)
LIP
N. Matela (Author)
IBEB

Summary
Background and Objective: Total Variation (TV) minimization algorithms have achieved great attention due to the virtue of decreasing noise while preserving edges. The purpose of this work is to implement and evaluate two TV minimization methods in 3D. Their performance is analyzed through 3D visualization of digital breast tomosynthesis (DBT) data with volume rendering. Methods: Both filters were studied with real phantom and one clinical DBT data. One algorithm was applied sequentially to all slices and the other was applied to the entire volume at once. The suitable Lagrange multiplier used in each filter equation was studied to reach the minimum 3D TV and the maximum contrast-to-noise ratio (CNR). Imaging blur was measured at 0º and 90º using two disks with different diameters (0.5mm and 5.0 mm) and equal thickness. The quality of unfiltered and filtered data was analyzed with volume rendering at 0º and 90º. Results: For phantom data, with the sequential filter, a decrease of 25% in 3D TV value and an increase of 19% and 30% in CNR at 0º and 90º, respectively, were observed. When the filter is applied directly in 3D, TV value was reduced by 35% and an increase of 36% was achieved both for CNR at 0º and 90º. For the smaller disk, variations of 0% in width at half maximum (FWHM) at 0º and a decrease of about 2.5% for FWHM at 90º were observed for both filters. For the larger disk, there was a 2.5% increase in FWHM at 0º for both filters and a decrease of 6.28% and 1.69% in FWHM at 90º with the sequential filter and the 3D filter, respectively. When applied to clinical data, the performance of each filter was consistent with that obtained with the phantom. Conclusions: Data analysis confirmed the relevance of these methods in improving quality of DBT images. Additionally, this type of 3D visualization showed that it may play an important complementary role in DBT imaging. It allows to visualize all DBT data at once and to analyze properly filters applied to all the three dimensions.


Where published
Computer Methods and Programs in Biomedicine

Publication Identifiers
ISSN - 0169-2607

Publisher
Elsevier BV



Document Identifiers
DOI - https://doi.org/10.1016/j.cmpb.2020.105534

Rankings
SCIMAGO Q1 (2021) - 1329 - Computer Science Applications
SCIMAGO Q1 (2021) - 1329 - Health Informatics
SCIMAGO Q1 (2021) - 1329 - Software
Web Of Science Q1 (2021) - 7.027 - COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS - SCIE
Web Of Science Q1 (2021) - 7.027 - ENGINEERING, BIOMEDICAL - SCIE
SCOPUS Q1 (2021) - 9.7 - Computer Science Applications
SCOPUS Q1 (2021) - 9.7 - Software