Multi-institutional assessment and crowdsourcing evaluation of deep learning for automated classification of breast density
Objective We developed deep learning algorithms to automatically assess BI-RADS breast
density. Methods Using a large multi-institution patient cohort of 108,230 digital screening …
density. Methods Using a large multi-institution patient cohort of 108,230 digital screening …
[HTML][HTML] Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race
Background Breast density is an important risk factor for breast cancer complemented by a
higher risk of cancers being missed during screening of dense breasts due to reduced …
higher risk of cancers being missed during screening of dense breasts due to reduced …
Mammographic breast density assessment using deep learning: clinical implementation
Purpose To develop a deep learning (DL) algorithm to assess mammographic breast
density. Materials and Methods In this retrospective study, a deep convolutional neural …
density. Materials and Methods In this retrospective study, a deep convolutional neural …
External validation of a deep learning model for predicting mammographic breast density in routine clinical practice
Rationale and Objectives Federal legislation requires patient notification of dense
mammographic breast tissue because increased density is a marker of breast cancer risk …
mammographic breast tissue because increased density is a marker of breast cancer risk …
A deep learning method for classifying mammographic breast density categories
AA Mohamed, WA Berg, H Peng, Y Luo… - Medical …, 2018 - Wiley Online Library
Purpose Mammographic breast density is an established risk marker for breast cancer and
is visually assessed by radiologists in routine mammogram image reading, using four …
is visually assessed by radiologists in routine mammogram image reading, using four …
Understanding clinical mammographic breast density assessment: a deep learning perspective
AA Mohamed, Y Luo, H Peng, RC Jankowitz… - Journal of digital …, 2018 - Springer
Mammographic breast density has been established as an independent risk marker for
developing breast cancer. Breast density assessment is a routine clinical need in breast …
developing breast cancer. Breast density assessment is a routine clinical need in breast …
Deep learning for mammographic breast density assessment and beyond
HP Chan, MA Helvie - Radiology, 2019 - pubs.rsna.org
Deep Learning for Mammographic Breast Density 60 radiology. rsna. org n Radiology:
Volume 290: Number 1—January 2019 decision if it can improve or if it does not impede the …
Volume 290: Number 1—January 2019 decision if it can improve or if it does not impede the …
[HTML][HTML] Deep learning models for automated assessment of breast density using multiple mammographic image types
Simple Summary The DL model predictions in automated breast density assessment were
independent of the imaging technologies, moderately or substantially agreed with the …
independent of the imaging technologies, moderately or substantially agreed with the …
Automatic assessment of mammographic density using a deep transfer learning method
S Squires, E Harkness… - Journal of Medical …, 2023 - spiedigitallibrary.org
Purpose Mammographic breast density is one of the strongest risk factors for cancer. Density
assessed by radiologists using visual analogue scales has been shown to provide better …
assessed by radiologists using visual analogue scales has been shown to provide better …
[HTML][HTML] A novel deep learning architecture outperforming 'off‑the‑shelf'transfer learning and feature‑based methods in the automated assessment of mammographic …
E Trivizakis, GS Ioannidis… - Oncology …, 2019 - spandidos-publications.com
Potentially suspicious breast neoplasms could be masked by high tissue density, thus
increasing the probability of a false‑negative diagnosis. Furthermore, differentiating breast …
increasing the probability of a false‑negative diagnosis. Furthermore, differentiating breast …