Skip To Main Content
Bruno Barufaldi on Muck Rack

Bruno Barufaldi

As seen in: Wiley Online Library, MDPI
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Bruno

Contact Bruno, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Racial differences in quantitative background parenchymal enhancement on breast magnetic resonance imaging

|
By Mattia A. Mahmoud, Christine Edmonds, Bruno Barufaldi, Alex Nguyen
| Wiley Online Library Verified
INTRODUCTION Background parenchymal enhancement (BPE) is an imaging biomarker for breast cancer that has been shown to have a stronger association with breast cancer risk than breast density.1, 2 During a dynamic contrast-enhanced magnetic resonance imaging (MRI) of the breasts, images are obtained before and after intravenous injection of a gadolinium-based contrast agent. This technique enables visualization of lesions with vascularity, including the vast majority of breast malignancies.
Open in Who Shared Issue with article?

Impact of Tomosynthesis Acquisition on 3D Segmentations of Breast Outline and Adipose/Dense Tissue with AI: A Simulation-Based Study

|
By Bruno Barufaldi, Jordy Gomes, Yuri Malheiros, Lucas Borges
| MDPI
Open AccessArticle by Bruno Barufaldi 1,*, Jordy Gomes 2, Thais G. do Rego 2, Yuri Malheiros 2, Telmo M. Silva Filho 3, Lucas R. Borges 4, Raymond J. Acciavatti 1, Suleman Surti 1 and Andrew D. A.
Open in Who Shared Issue with article?

Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

|
By Bruno Barufaldi, Giulia Carvalhal, Yuri Malheiros, Raymond J. Acciavatti
| MDPI
4. Discussion DBT systems acquire images over a limited angular range with a limited number of projections; the resulting datasets are undersampled and produce out-of-plane artifacts in the reconstructions that may compromise the detectability of lesions. Our previous work with virtual phantoms demonstrated that there is benefit to customizing the scanning motion based on breast size, but it did not consider the impact of lesion detectability [6].
Open in Who Shared Issue with article?
See all 3 articles