Artificial intelligence in the interpretation of breast cancer on MRI

D Sheth, ML Giger - Journal of Magnetic Resonance Imaging, 2020 - Wiley Online Library
Advances in both imaging and computers have led to the rise in the potential use of artificial
intelligence (AI) in various tasks in breast imaging, going beyond the current use in …

Automatic detection and segmentation of breast cancer on MRI using mask R-CNN trained on non–fat-sat images and tested on fat-sat images

Y Zhang, S Chan, VY Park, KT Chang, S Mehta… - Academic …, 2022 - Elsevier
Rationale and Objectives Computer-aided methods have been widely applied to diagnose
lesions on breast magnetic resonance imaging (MRI). The first step was to identify abnormal …

Fully automated detection of breast cancer in screening MRI using convolutional neural networks

MU Dalmış, S Vreemann, T Kooi… - Journal of Medical …, 2018 - spiedigitallibrary.org
Current computer-aided detection (CADe) systems for contrast-enhanced breast MRI rely on
both spatial information obtained from the early-phase and temporal information obtained …

Multireader study on the diagnostic accuracy of ultrafast breast magnetic resonance imaging for breast cancer screening

JCM van Zelst, S Vreemann, HJ Witt… - Investigative …, 2018 - journals.lww.com
Objectives Breast cancer screening using magnetic resonance imaging (MRI) has limited
accessibility due to high costs of breast MRI. Ultrafast dynamic contrast-enhanced breast …

Automatic breast lesion detection in ultrafast DCE‐MRI using deep learning

F Ayatollahi, SB Shokouhi, RM Mann… - Medical …, 2021 - Wiley Online Library
Purpose We propose a deep learning‐based computer‐aided detection (CADe) method to
detect breast lesions in ultrafast DCE‐MRI sequences. This method uses both the 3D spatial …

The added value of mammography in different age-groups of women with and without BRCA mutation screened with breast MRI

S Vreemann, JCM van Zelst, M Schlooz-Vries… - Breast Cancer …, 2018 - Springer
Background Breast magnetic resonance imaging (MRI) is the most sensitive imaging
method for breast cancer detection and is therefore offered as a screening technique to …

Using deep learning to improve nonsystematic viewing of breast cancer on MRI

S Eskreis-Winkler, N Onishi, K Pinker… - Journal of Breast …, 2021 - academic.oup.com
Objective To investigate the feasibility of using deep learning to identify tumor-containing
axial slices on breast MRI images. Methods This IRB–approved retrospective study included …

Screening in patients with increased risk of breast cancer (part 1): pros and cons of MRI screening

SA Roca, ABD Laguna, JA Lexarreta… - Radiología (English …, 2020 - Elsevier
Screening plays an important role in women with a high risk of breast cancer. Given this
population's high incidence of breast cancer and younger age of onset compared to the …

Breast MRI: false-negative results and missed opportunities

KE Korhonen, SP Zuckerman, SP Weinstein, J Tobey… - Radiographics, 2021 - pubs.rsna.org
Breast MRI is the most sensitive modality for the detection of breast cancer. However, false-
negative cases may occur, in which the cancer is not visualized at MRI and is instead …

Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI

G Maicas, AP Bradley, JC Nascimento, I Reid… - Medical image …, 2019 - Elsevier
We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc
approach that is trained using weakly annotated data (ie, labels are available only at the …