AIMC Topic: Ultrasonography, Mammary

Clear Filters Showing 171 to 180 of 227 articles

Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images.

European radiology experimental Aug 5, 2019
BACKGROUND: The purpose of this work was to evaluate computable Breast Imaging Reporting and Data System (BI-RADS) radiomic features to classify breast masses on ultrasound B-mode images.
Humans Machine Learning Software Breast Neoplasms Middle Aged Algorithms Ultrasonography, Mammary Prospective Studies Breast Diseases Female Adult
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Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software.

Acta radiologica (Stockholm, Sweden : 1987) Jul 19, 2019
BACKGROUND: Computer-aided detection software for automated breast ultrasound has been shown to have potential in improving the accuracy of radiologists. Alternative ways of implementing computer-aided detection, such as independent validation or pre...
Image Interpretation, Computer-Assisted Radiologists Ultrasonography, Mammary Breast Female Aged Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Imaging, Three-Dimensional Humans Artificial Intelligence
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Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data.

Scientific reports Jul 19, 2019
Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for bre...
Humans Neural Networks, Computer Algorithms Female Mammography Equipment Design Ultrasonography, Mammary Breast Breast Neoplasms ROC Curve Support Vector Machine Magnetic Resonance Imaging Scattering, Radiation Microwave Imaging Clinical Trials as Topic Statistics, Nonparametric Dielectric Spectroscopy
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Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making.

European radiology Mar 29, 2019
OBJECTIVES: To evaluate a deep convolutional neural network (dCNN) for detection, highlighting, and classification of ultrasound (US) breast lesions mimicking human decision-making according to the Breast Imaging Reporting and Data System (BI-RADS).
Humans Breast Neoplasms Middle Aged ROC Curve Ultrasonography, Mammary Image Interpretation, Computer-Assisted Observer Variation Neural Networks, Computer Algorithms Retrospective Studies Clinical Decision-Making Female Aged Adult
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Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.

Japanese journal of radiology Mar 19, 2019
PURPOSE: We aimed to use deep learning with convolutional neural network (CNN) to discriminate between benign and malignant breast mass images from ultrasound.
Ultrasonography, Mammary Breast Image Interpretation, Computer-Assisted Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Deep Learning ROC Curve Diagnosis, Differential Reproducibility of Results Aged Aged, 80 and over Humans Databases, Factual Young Adult Neural Networks, Computer Retrospective Studies Female
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Two-stage CNNs for computerized BI-RADS categorization in breast ultrasound images.

Biomedical engineering online Jan 24, 2019
BACKGROUND: Quantizing the Breast Imaging Reporting and Data System (BI-RADS) criteria into different categories with the single ultrasound modality has always been a challenge. To achieve this, we proposed a two-stage grading system to automatically...
Models, Statistical Radiology Biopsy Ultrasonography, Mammary Breast Pattern Recognition, Automated Reproducibility of Results Breast Neoplasms Diagnosis, Computer-Assisted Humans Image Processing, Computer-Assisted Neural Networks, Computer Female
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Automated diagnosis of breast ultrasonography images using deep neural networks.

Medical image analysis Dec 20, 2018
Ultrasonography images of breast mass aid in the detection and diagnosis of breast cancer. Manually analyzing ultrasonography images is time-consuming, exhausting and subjective. Automated analyzing such images is desired. In this study, we develop a...
Female Breast Neoplasms Ultrasonography, Mammary Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks.

Medical engineering & physics Dec 19, 2018
The main goal of this study is to build an artificial intelligence (AI) architecture for automated extraction of dual-modal image features from both shear-wave elastography (SWE) and B-mode ultrasound, and to evaluate the AI architecture for classifi...
Breast Neoplasms Humans Image Processing, Computer-Assisted Artificial Intelligence Ultrasonography, Mammary Elasticity Imaging Techniques Machine Learning
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Is Intensity Inhomogeneity Correction Useful for Classification of Breast Cancer in Sonograms Using Deep Neural Network?

Journal of healthcare engineering Dec 4, 2018
The sonogram is currently an effective cancer screening and diagnosis way due to the convenience and harmlessness in humans. Traditionally, lesion boundary segmentation is first adopted and then classification is conducted, to reach the judgment of b...
Image Interpretation, Computer-Assisted Breast Neoplasms Humans Deep Learning Algorithms Ultrasonography, Mammary Female Breast
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Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.

Medical physics Nov 28, 2018
PURPOSE: Due to the low contrast, blurry boundaries, and large amount of shadows in breast ultrasound (BUS) images, automatic tumor segmentation remains a challenging task. Deep learning provides a solution to this problem, since it can effectively e...
Automation Humans Neural Networks, Computer Breast Neoplasms Image Processing, Computer-Assisted Models, Theoretical Ultrasonography, Mammary
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