Beyond breast density: a review on the advancing role of parenchymal texture analysis in breast cancer risk assessment
A Gastounioti, EF Conant, D Kontos - Breast cancer research, 2016 - Springer
Background The assessment of a woman's risk for developing breast cancer has become
increasingly important for establishing personalized screening recommendations and …
increasingly important for establishing personalized screening recommendations and …
Applying artificial intelligence technology to assist with breast cancer diagnosis and prognosis prediction
Breast cancer remains the most diagnosed cancer in women. Advances in medical imaging
modalities and technologies have greatly aided in the early detection of breast cancer and …
modalities and technologies have greatly aided in the early detection of breast cancer and …
Multi-view feature fusion based four views model for mammogram classification using convolutional neural network
Breast cancer is the second most common cause of cancer-related deaths among women.
Early detection leads to better prognosis and saves lives. The 5-year survival rate of breast …
Early detection leads to better prognosis and saves lives. The 5-year survival rate of breast …
Deep learning of longitudinal mammogram examinations for breast cancer risk prediction
S Dadsetan, D Arefan, WA Berg, ML Zuley, JH Sumkin… - Pattern recognition, 2022 - Elsevier
Abstract Information in digital mammogram images has been shown to be associated with
the risk of developing breast cancer. Longitudinal breast cancer screening mammogram …
the risk of developing breast cancer. Longitudinal breast cancer screening mammogram …
A comparison of computer-aided diagnosis schemes optimized using radiomics and deep transfer learning methods
Objective: Radiomics and deep transfer learning are two popular technologies used to
develop computer-aided detection and diagnosis (CAD) schemes of medical images. This …
develop computer-aided detection and diagnosis (CAD) schemes of medical images. This …
Development and assessment of a new global mammographic image feature analysis scheme to predict likelihood of malignant cases
M Heidari, S Mirniaharikandehei, W Liu… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
This study aims to develop and evaluate a new computer-aided diagnosis (CADx) scheme
based on analysis of global mammographic image features to predict likelihood of cases …
based on analysis of global mammographic image features to predict likelihood of cases …
Association between changes in mammographic image features and risk for near-term breast cancer development
The purpose of this study is to develop and test a new computerized model for predicting
near-term breast cancer risk based on quantitative assessment of bilateral mammographic …
near-term breast cancer risk based on quantitative assessment of bilateral mammographic …
Convolutional neural network based breast cancer risk stratification using a mammographic dataset
Rationale and Objectives We propose a novel convolutional neural network derived pixel-
wise breast cancer risk model using mammographic dataset. Materials and Methods An …
wise breast cancer risk model using mammographic dataset. Materials and Methods An …
Mammographic breast density: current assessment methods, clinical implications, and future directions
CE Edmonds, SR O'Brien, EF Conant - Seminars in Ultrasound, CT and …, 2023 - Elsevier
Mammographic breast density is widely accepted as an independent risk factor for the
development of breast cancer. In addition, because dense breast tissue may mask breast …
development of breast cancer. In addition, because dense breast tissue may mask breast …
Fusion of quantitative imaging features and serum biomarkers to improve performance of computer‐aided diagnosis scheme for lung cancer: a preliminary study
Objectives To develop and test a new multifeature‐based computer‐aided diagnosis (CAD
x) scheme of lung cancer by fusing quantitative imaging (QI) features and serum biomarkers …
x) scheme of lung cancer by fusing quantitative imaging (QI) features and serum biomarkers …