AIMC Topic: Breast Density

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Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Radiology Oct 5, 2021
Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI...
Humans Female Breast Neoplasms Middle Aged Breast Feasibility Studies Image Interpretation, Computer-Assisted Breast Density Deep Learning Magnetic Resonance Imaging Triage
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Deep-Learning-Driven Full-Waveform Inversion for Ultrasound Breast Imaging.

Sensors (Basel, Switzerland) Jul 3, 2021
Ultrasound breast imaging is a promising alternative to conventional mammography because it does not expose women to harmful ionising radiation and it can successfully image dense breast tissue. However, conventional ultrasound imaging only provides ...
Ultrasonography, Mammary Phantoms, Imaging Humans Breast Density Female Image Processing, Computer-Assisted Mammography Breast Neoplasms Deep Learning
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Application of deep learning in the detection of breast lesions with four different breast densities.

Cancer medicine Jun 16, 2021
OBJECTIVE: This retrospective study evaluated the model from populations with different breast densities and showed the model's performance on malignancy prediction.
Aged Adult Sensitivity and Specificity Breast Neoplasms Humans Retrospective Studies Female Breast Density Triple Negative Breast Neoplasms Middle Aged Calcinosis Deep Learning Mammography ROC Curve
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Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

Medical image analysis Apr 15, 2021
The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly us...
Mammography Breast Radiation Dosage Breast Density Female Breast Neoplasms Deep Learning Humans
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Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics With Invasive Breast Cancer Risk.

JNCI cancer spectrum Feb 6, 2021
BACKGROUND: Benign breast disease (BBD) is a strong breast cancer risk factor, but identifying patients that might develop invasive breast cancer remains a challenge.
Breast Supervised Machine Learning Confidence Intervals Breast Diseases Odds Ratio Breast Density Age Factors Mammography Biopsy Middle Aged Case-Control Studies Diagnosis, Computer-Assisted Female Risk Factors Aged Adult Breast Neoplasms Aged, 80 and over Young Adult Humans
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Volumetric breast density estimation on MRI using explainable deep learning regression.

Scientific reports Oct 22, 2020
To purpose of this paper was to assess the feasibility of volumetric breast density estimations on MRI without segmentations accompanied with an explainability step. A total of 615 patients with breast cancer were included for volumetric breast densi...
Aged Aged, 80 and over Adult Deep Learning Image Processing, Computer-Assisted Breast Neoplasms Middle Aged Prospective Studies Prognosis Female Humans Carcinoma, Ductal, Breast Neural Networks, Computer Breast Density Algorithms Follow-Up Studies Carcinoma, Lobular Magnetic Resonance Imaging Neoplasm Invasiveness
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A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation.

Computer methods and programs in biomedicine Jul 24, 2020
BACKGROUND AND OBJECTIVE: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic women are taken with early di...
Humans Image Processing, Computer-Assisted Breast Female Breast Density Mammography Breast Neoplasms Deep Learning
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Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density.

Journal of the American College of Radiology : JACR Jun 24, 2020
OBJECTIVE: We developed deep learning algorithms to automatically assess BI-RADS breast density.
Mammography Crowdsourcing Humans Female Breast Density Artificial Intelligence Breast Neoplasms Deep Learning
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External Validation of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

Academic radiology Feb 20, 2020
RATIONALE AND OBJECTIVES: Federal legislation requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit the sensitivity of mammography. As previously described, we clin...
Breast Neoplasms Humans Deep Learning Mammography Breast Breast Density
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Harnessing the Power of Deep Learning to Assess Breast Cancer Risk.

Radiology Dec 17, 2019
Risk Breast Density Machine Learning Deep Learning Mammography
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