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Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening

Clinical cancer research, 2018-12, Vol.24 (23), p.5902-5909

2018

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Deep learning modeling using normal mammograms for predicting breast cancer risk

Medical physics (Lancaster), 2020-01, Vol.47 (1), p.110-118

2020

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Assessing radiologist performance using combined digital mammography and breast tomosynthesis compared with digital mammography alone: results of a multicenter, multireader trial

Radiology, 2013-01, Vol.266 (1), p.104-113

2013

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Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes

BMC cancer, 2021-04, Vol.21 (1), p.370-370, Article 370

2021

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Detection and classification of calcifications on digital breast tomosynthesis and 2D digital mammography: a comparison

American journal of roentgenology (1976), 2011-02, Vol.196 (2), p.320-324

2011

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Deep learning of longitudinal mammogram examinations for breast cancer risk prediction

Pattern recognition, 2022-12, Vol.132, p.108919, Article 108919

2022

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Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk

Radiology, 2024-01, Vol.310 (1)

2024

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Digital breast tomosynthesis versus supplemental diagnostic mammographic views for evaluation of noncalcified breast lesions

Radiology, 2013-01, Vol.266 (1), p.89-95

2013

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Diagnostic Performance of MRI, Molecular Breast Imaging, and Contrast-enhanced Mammography in Women with Newly Diagnosed Breast Cancer

Radiology, 2019-12, Vol.293 (3), p.531-540

2019

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Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study

Breast cancer research : BCR, 2024-05, Vol.26 (1), p.82-82, Article 82

2024

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Digital breast tomosynthesis: observer performance study

American journal of roentgenology (1976), 2009-08, Vol.193 (2), p.586-591

2009

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Comparison of two-dimensional synthesized mammograms versus original digital mammograms alone and in combination with tomosynthesis images

Radiology, 2014-06, Vol.271 (3), p.664-671

2014

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Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment

European journal of radiology, 2012-11, Vol.81 (11), p.3222-3228

2012

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Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study

Journal of digital imaging, 2020-10, Vol.33 (5), p.1257-1265

2020

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Screening for early detection of breast cancer: overdiagnosis versus suboptimal patient management

Radiology, 2013-08, Vol.268 (2), p.327-328

2013

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State of Academic Radiology: Current Challenges, Future Adaptations

Seminars in ultrasound, CT, and MRI, 2024-04, Vol.45 (2), p.134-138

2024

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Diagnostic accuracy and recall rates for digital mammography and digital mammography combined with one-view and two-view tomosynthesis: results of an enriched reader study

American journal of roentgenology (1976), 2014-02, Vol.202 (2), p.273-281

2014

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Digital breast tomosynthesis in the diagnostic environment: A subjective side-by-side review

American journal of roentgenology (1976), 2010-08, Vol.195 (2), p.W172-W176

2010

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Integrated 2D and 3D mammography

The lancet oncology, 2013-07, Vol.14 (8), p.e292-e293

Sumkin, Jules H

2013

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DCE-MRI Background Parenchymal Enhancement Quantified from an Early versus Delayed Post-contrast Sequence: Association with Breast Cancer Presence

Scientific reports, 2017-05, Vol.7 (1), p.2115-11, Article 2115

2017

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Core Breast Biopsies Showing Lobular Carcinoma In Situ Should Be Excised and Surveillance Is Reasonable for Atypical Lobular Hyperplasia

American journal of roentgenology (1976), 2016-11, Vol.207 (5), p.1132-1145

2016

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Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer

Breast cancer research : BCR, 2016-07, Vol.18 (1), p.76-76, Article 76

2016

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Contrast Enhanced Digital Mammography (CEDM) Helps to Safely Reduce Benign Breast Biopsies for Low to Moderately Suspicious Soft Tissue Lesions

Academic radiology, 2020-07, Vol.27 (7), p.969-976

2020

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New screening technologies and practices: a different approach to estimation of performance improvement by using data from the transition period

Radiology, 2015-04, Vol.275 (1), p.9-12

2015

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Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening

Deep learning modeling using normal mammograms for predicting breast cancer risk

Assessing radiologist performance using combined digital mammography and breast tomosynthesis compared with digital mammography alone: results of a multicenter, multireader trial

Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes

Detection and classification of calcifications on digital breast tomosynthesis and 2D digital mammography: a comparison

Deep learning of longitudinal mammogram examinations for breast cancer risk prediction

Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk

Digital breast tomosynthesis versus supplemental diagnostic mammographic views for evaluation of noncalcified breast lesions

Diagnostic Performance of MRI, Molecular Breast Imaging, and Contrast-enhanced Mammography in Women with Newly Diagnosed Breast Cancer

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study

Digital breast tomosynthesis: observer performance study

Comparison of two-dimensional synthesized mammograms versus original digital mammograms alone and in combination with tomosynthesis images

Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment

Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study

Screening for early detection of breast cancer: overdiagnosis versus suboptimal patient management

State of Academic Radiology: Current Challenges, Future Adaptations

Diagnostic accuracy and recall rates for digital mammography and digital mammography combined with one-view and two-view tomosynthesis: results of an enriched reader study

Digital breast tomosynthesis in the diagnostic environment: A subjective side-by-side review

Integrated 2D and 3D mammography

DCE-MRI Background Parenchymal Enhancement Quantified from an Early versus Delayed Post-contrast Sequence: Association with Breast Cancer Presence

Addition of Contrast-enhanced Mammography to Tomosynthesis for Breast Cancer Detection in Women with a Personal History of Breast Cancer: Prospective TOCEM Trial Interim Analysis

Core Breast Biopsies Showing Lobular Carcinoma In Situ Should Be Excised and Surveillance Is Reasonable for Atypical Lobular Hyperplasia

Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer

Contrast Enhanced Digital Mammography (CEDM) Helps to Safely Reduce Benign Breast Biopsies for Low to Moderately Suspicious Soft Tissue Lesions

New screening technologies and practices: a different approach to estimation of performance improvement by using data from the transition period

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