AIMC Topic: Ultrasonography, Mammary

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Segmentation of breast ultrasound image with semantic classification of superpixels.

Medical image analysis Jan 25, 2020
Breast cancer is a great threat to females. Ultrasound imaging has been applied extensively in diagnosis of breast cancer. Due to the poor image quality, segmentation of breast ultrasound (BUS) image remains a very challenging task. Besides, BUS imag...
Ultrasonography, Mammary Image Interpretation, Computer-Assisted Semantics Humans Neural Networks, Computer Female Breast Neoplasms
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Evaluation of the predictive ability of ultrasound-based assessment of breast cancer using BI-RADS natural language reporting against commercial transcriptome-based tests.

PloS one Jan 10, 2020
PURPOSE: The objective of this study was to assess the classification capability of Breast Imaging Reporting and Data System (BI-RADS) ultrasound feature descriptors targeting established commercial transcriptomic gene signatures that guide managemen...
Humans Research Design Retrospective Studies Female ROC Curve Natural Language Processing Area Under Curve Ultrasonography, Mammary Breast Neoplasms Middle Aged Gene Expression Profiling Cohort Studies
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Breast tumor classification through learning from noisy labeled ultrasound images.

Medical physics Dec 30, 2019
PURPOSE: To train deep learning models to differentiate benign and malignant breast tumors in ultrasound images, we need to collect many training samples with clear labels. In general, biopsy results can be used as benign/malignant labels. However, m...
Humans Machine Learning Breast Neoplasms Image Processing, Computer-Assisted Ultrasonography, Mammary Signal-To-Noise Ratio
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Automatic Identification of Breast Ultrasound Image Based on Supervised Block-Based Region Segmentation Algorithm and Features Combination Migration Deep Learning Model.

IEEE journal of biomedical and health informatics Dec 19, 2019
Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial role in the successful treatment of the disease and the effective reduction of deaths. In this paper, deep learning technology combined with ultrasound imagin...
Supervised Machine Learning Image Interpretation, Computer-Assisted Deep Learning Ultrasonography, Mammary Breast Humans Algorithms Female Sensitivity and Specificity Breast Neoplasms
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CAD and AI for breast cancer-recent development and challenges.

The British journal of radiology Dec 16, 2019
Computer-aided diagnosis (CAD) has been a popular area of research and development in the past few decades. In CAD, machine learning methods and multidisciplinary knowledge and techniques are used to analyze the patient information and the results ca...
Humans Neural Networks, Computer Artificial Intelligence Female Radiology Ultrasonography, Mammary Image Interpretation, Computer-Assisted Quality Assurance, Health Care Decision Support Systems, Clinical Bibliometrics Magnetic Resonance Imaging Mammography Breast Neoplasms Diagnosis, Computer-Assisted Deep Learning
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Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions.

Ultrasound in medicine & biology Nov 27, 2019
The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for cla...
Female Adolescent Aged Humans Ultrasonography, Mammary Machine Learning Adult Aged, 80 and over Data Systems Research Design Young Adult Breast Neoplasms Middle Aged
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Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.

Radiology Nov 19, 2019
Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve incre...
Neural Networks, Computer Algorithms Retrospective Studies Female Aged Aged, 80 and over Young Adult Predictive Value of Tests Adult Ultrasonography, Mammary Feasibility Studies Humans Deep Learning Image Interpretation, Computer-Assisted Cohort Studies Sensitivity and Specificity Lymph Nodes Breast Neoplasms Lymphatic Metastasis Middle Aged
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Diagnostic performance of machine learning applied to texture analysis-derived features for breast lesion characterisation at automated breast ultrasound: a pilot study.

European radiology experimental Nov 1, 2019
BACKGROUND: Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise A...
Ultrasonography, Mammary Image Interpretation, Computer-Assisted Breast Diseases Breast Neoplasms Middle Aged Pilot Projects Diagnosis, Differential Aged Humans Aged, 80 and over Machine Learning Adult Retrospective Studies Female
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Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique.

Sensors (Basel, Switzerland) Sep 19, 2019
We present a deep learning method used in conjunction with dual-modal microwave-ultrasound imaging to produce tomographic reconstructions of the complex-valued permittivity of numerical breast phantoms. We also assess tumor segmentation performance u...
Deep Learning Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Ultrasonography, Mammary Neural Networks, Computer Microwaves Female Breast Neoplasms
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Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.

IEEE transactions on medical imaging Aug 20, 2019
ABUS, or Automated breast ultrasound, is an innovative and promising method of screening for breast examination. Comparing to common B-mode 2D ultrasound, ABUS attains operator-independent image acquisition and also provides 3D views of the whole bre...
Middle Aged Deep Learning Ultrasonography, Mammary Breast Supervised Machine Learning Aged, 80 and over Humans Image Interpretation, Computer-Assisted Adult Female Sensitivity and Specificity Aged Breast Neoplasms
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