Artificial intelligence for breast MRI in 2008–2018: a systematic mapping review
M Codari, S Schiaffino, F Sardanelli… - American Journal of …, 2019 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study is to review literature from the past decade on
applications of artificial intelligence (AI) to breast MRI. MATERIALS AND METHODS. In June …
applications of artificial intelligence (AI) to breast MRI. MATERIALS AND METHODS. In June …
Breast cancer diagnosis in DCE-MRI using mixture ensemble of convolutional neural networks
This work addresses a novel computer-aided diagnosis (CAD) system in breast dynamic
contrast-enhanced magnetic resonance imaging (DCE-MRI). The CAD system is designed …
contrast-enhanced magnetic resonance imaging (DCE-MRI). The CAD system is designed …
Breast cancer molecular subtype classifier that incorporates MRI features
EJ Sutton, BZ Dashevsky, JH Oh… - Journal of Magnetic …, 2016 - Wiley Online Library
Purpose To use features extracted from magnetic resonance (MR) images and a machine‐
learning method to assist in differentiating breast cancer molecular subtypes. Materials and …
learning method to assist in differentiating breast cancer molecular subtypes. Materials and …
Breast cancer subtype intertumor heterogeneity: MRI‐based features predict results of a genomic assay
EJ Sutton, JH Oh, BZ Dashevsky… - Journal of Magnetic …, 2015 - Wiley Online Library
Purpose To investigate the association between a validated, gene‐expression‐based,
aggressiveness assay, Oncotype Dx RS, and morphological and texture‐based image …
aggressiveness assay, Oncotype Dx RS, and morphological and texture‐based image …
Application of radiomics and decision support systems for breast MR differential diagnosis
Over the years, MR systems have evolved from imaging modalities to advanced
computational systems producing a variety of numerical parameters that can be used for the …
computational systems producing a variety of numerical parameters that can be used for the …
Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal
dimension, a morphological measure of the complexity of pixel arrangement, have shown …
dimension, a morphological measure of the complexity of pixel arrangement, have shown …
Early prediction of breast cancer therapy response using multiresolution fractal analysis of DCE-MRI parametric maps
A Machireddy, G Thibault, A Tudorica, A Afzal… - …, 2019 - pmc.ncbi.nlm.nih.gov
We aimed to determine whether multiresolution fractal analysis of voxel-based dynamic
contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps can provide …
contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps can provide …
Fractal analysis: fractal dimension and lacunarity from MR images for differentiating the grades of glioma
KA Smitha, AK Gupta, RS Jayasree - Physics in Medicine & …, 2015 - iopscience.iop.org
Glioma, the heterogeneous tumors originating from glial cells, generally exhibit varied
grades and are difficult to differentiate using conventional MR imaging techniques. When …
grades and are difficult to differentiate using conventional MR imaging techniques. When …
[HTML][HTML] Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy
Breast cancer is one of the most spread and monitored pathologies in high-income
countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and …
countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and …
Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI
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 …
approach that is trained using weakly annotated data (ie, labels are available only at the …