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Pitfall: Case of a malignant hyperechoic breast lesion at ultrasound

RöFo : Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebende Verfahren, 2024-06, Vol.196 (6), p.613

2024

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Dual-Modality Photoacoustic and Ultrasound Imaging System for Noninvasive Sentinel Lymph Node Detection in Patients with Breast Cancer

Scientific reports, 2015-10, Vol.5 (1), p.15748-15748, Article 15748

2015

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Breast ultrasonography: state of the art

Radiology, 2013-09, Vol.268 (3), p.642

2013

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A deep learning framework for supporting the classification of breast lesions in ultrasound images

Physics in medicine & biology, 2017-09, Vol.62 (19), p.7714-7728

2017

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CAD and AI for breast cancer-recent development and challenges

British journal of radiology, 2020-04, Vol.93 (1108), p.20190580-20190580

2020

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Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning

Radiology, 2020-01, Vol.294 (1), p.19-28

2020

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Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review

Ultrasound in medicine & biology, 2018-01, Vol.44 (1), p.37-70

2018

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Computer-aided diagnosis system for breast ultrasound images using deep learning

Physics in medicine & biology, 2019-12, Vol.64 (23), p.235013-235013

2019

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Frequency domain ultrasound waveform tomography: breast imaging using a ring transducer

Physics in medicine & biology, 2015-07, Vol.60 (14), p.5381-5398

2015

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Assessing teat canal morphology in the dry period and during lactation by high-resolution ultrasound - ERRATUM

Journal of dairy research, 2024-02, Vol.91 (1), p.65-66

2024

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Segmentation of breast ultrasound image with semantic classification of superpixels

Medical image analysis, 2020-04, Vol.61, p.101657-101657, Article 101657

2020

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Detection and classification the breast tumors using mask R-CNN on sonograms

Medicine (Baltimore), 2019-05, Vol.98 (19), p.e15200

2019

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Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses

Radiology, 2012-02, Vol.262 (2), p.435

2012

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EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 1: Basic principles and technology

Ultraschall in der Medizin, 2013-04, Vol.34 (2), p.169

2013

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In Vivo Validation of an In Situ Calibration Bead as a Reference for Backscatter Coefficient Calculation

Ultrasound in medicine & biology, 2024-06, Vol.50 (6), p.833-842

2024

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Addition of ultrasound to mammography in the case of dense breast tissue: systematic review and meta-analysis

British journal of cancer, 2018-06, Vol.118 (12), p.1559-1570

2018

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Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

IEEE transactions on medical imaging, 2012-09, Vol.31 (9), p.1821-1832

2012

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Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems

American journal of roentgenology (1976), 2021-04, Vol.216 (4), p.860

2021

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Evaluation of Screening US-detected Breast Masses by Combined Use of Elastography and Color Doppler US with B-Mode US in Women with Dense Breasts: A Multicenter Prospective Study

Radiology, 2017-11, Vol.285 (2), p.660

2017

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Breast density implications and supplemental screening

European radiology, 2019-04, Vol.29 (4), p.1762-1777

2019

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Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study

British journal of radiology, 2018-01, Vol.91 (1083), p.20170576-20170576

2018

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Deep learning based classification of breast tumors with shear-wave elastography

Ultrasonics, 2016-12, Vol.72, p.150-157

2016

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EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 2: Clinical applications

Ultraschall in der Medizin, 2013-06, Vol.34 (3), p.238

2013

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Adding 3D Automated Breast Ultrasound to mammography screening in women with heterogeneously and extremely dense breasts. Report from a hospital-based, high-volume, single-center breast cancer screening program

European journal of radiology, 2016-09, Vol.85 (9), p.1554-1563

2016

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Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound

IEEE transactions on medical imaging, 2020-04, Vol.39 (4), p.866-876

2020

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Pitfall: Case of a malignant hyperechoic breast lesion at ultrasound

Dual-Modality Photoacoustic and Ultrasound Imaging System for Noninvasive Sentinel Lymph Node Detection in Patients with Breast Cancer

Breast ultrasonography: state of the art

A deep learning framework for supporting the classification of breast lesions in ultrasound images

CAD and AI for breast cancer-recent development and challenges

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning

Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review

Computer-aided diagnosis system for breast ultrasound images using deep learning

Frequency domain ultrasound waveform tomography: breast imaging using a ring transducer

Assessing teat canal morphology in the dry period and during lactation by high-resolution ultrasound - ERRATUM

Segmentation of breast ultrasound image with semantic classification of superpixels

Detection and classification the breast tumors using mask R-CNN on sonograms

Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses

EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 1: Basic principles and technology

In Vivo Validation of an In Situ Calibration Bead as a Reference for Backscatter Coefficient Calculation

Addition of ultrasound to mammography in the case of dense breast tissue: systematic review and meta-analysis

Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems

Evaluation of Screening US-detected Breast Masses by Combined Use of Elastography and Color Doppler US with B-Mode US in Women with Dense Breasts: A Multicenter Prospective Study

Breast density implications and supplemental screening

Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study

Deep learning based classification of breast tumors with shear-wave elastography

EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 2: Clinical applications

Adding 3D Automated Breast Ultrasound to mammography screening in women with heterogeneously and extremely dense breasts. Report from a hospital-based, high-volume, single-center breast cancer screening program

Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound

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