AIMC Topic: Ultrasonography, Mammary

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Application of Deep Learning to Reduce the Rate of Malignancy Among BI-RADS 4A Breast Lesions Based on Ultrasonography.

Ultrasound in medicine & biology Aug 30, 2022
The aim of the work described here was to develop an ultrasound (US) image-based deep learning model to reduce the rate of malignancy among breast lesions diagnosed as category 4A of the Breast Imaging-Reporting and Data System (BI-RADS) during the p...
Retrospective Studies Female Breast Neoplasms Humans ROC Curve Ultrasonography, Mammary Deep Learning Ultrasonography
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C-Net: Cascaded convolutional neural network with global guidance and refinement residuals for breast ultrasound images segmentation.

Computer methods and programs in biomedicine Aug 24, 2022
BACKGROUND AND OBJECTIVE: Breast lesions segmentation is an important step of computer-aided diagnosis system. However, speckle noise, heterogeneous structure, and similar intensity distributions bring challenges for breast lesion segmentation.
Ultrasonography, Mammary Breast Humans Neural Networks, Computer Ultrasonography Female Image Processing, Computer-Assisted
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Establishment of a deep-learning system to diagnose BI-RADS4a or higher using breast ultrasound for clinical application.

Cancer science Aug 3, 2022
Although the categorization of ultrasound using the Breast Imaging Reporting and Data System (BI-RADS) has become widespread worldwide, the problem of inter-observer variability remains. To maintain uniformity in diagnostic accuracy, we have develope...
Humans Artificial Intelligence Female Deep Learning Ultrasonography Ultrasonography, Mammary Sensitivity and Specificity Breast Neoplasms
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Performance of novel deep learning network with the incorporation of the automatic segmentation network for diagnosis of breast cancer in automated breast ultrasound.

European radiology Apr 30, 2022
OBJECTIVE: To develop novel deep learning network (DLN) with the incorporation of the automatic segmentation network (ASN) for morphological analysis and determined the performance for diagnosis breast cancer in automated breast ultrasound (ABUS).
Breast Neoplasms Deep Learning Ultrasonography, Mammary Female Sensitivity and Specificity Breast Humans
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Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.

Japanese journal of radiology Mar 14, 2022
PURPOSE: To investigate the ability of deep learning (DL) using convolutional neural networks (CNNs) for distinguishing between normal and metastatic axillary lymph nodes on ultrasound images by comparing the diagnostic performance of radiologists.
Ultrasonography Lymph Nodes Ultrasonography, Mammary Lymphatic Metastasis Breast Neoplasms Deep Learning Neural Networks, Computer Female Sensitivity and Specificity Retrospective Studies Humans
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SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion Segmentation in Ultrasound Image.

IEEE transactions on medical imaging Feb 2, 2022
Deep learning methods, especially convolutional neural networks, have been successfully applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern complexity and intensity similarity between the surrounding tissues (i.e., back...
Image Processing, Computer-Assisted Ultrasonography, Mammary Humans Female Ultrasonography Neural Networks, Computer
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Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion.

Sensors (Basel, Switzerland) Jan 21, 2022
After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for...
Humans Ultrasonography, Mammary Female Breast Breast Neoplasms Probability Deep Learning
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Joint segmentation and classification of breast masses based on ultrasound radio-frequency data and convolutional neural networks.

Ultrasonics Jan 14, 2022
In this paper, we propose a novel deep learning method for joint classification and segmentation of breast masses based on radio-frequency (RF) ultrasound (US) data. In comparison to commonly used classification and segmentation techniques, utilizing...
Radio Waves Data Compression Breast Diseases Retrospective Studies Diagnosis, Differential Humans Neural Networks, Computer Ultrasonography, Mammary
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Deep learning applied to breast imaging classification and segmentation with human expert intervention.

Journal of ultrasound Jan 9, 2022
PURPOSE: Automatic classification and segmentation of tumors in breast ultrasound images enables better diagnosis and planning treatment strategies for breast cancer patients.
Machine Learning Algorithms Breast Neoplasms Deep Learning Female Humans Ultrasonography, Mammary
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Saliency map-guided hierarchical dense feature aggregation framework for breast lesion classification using ultrasound image.

Computer methods and programs in biomedicine Dec 31, 2021
Deep learning methods, especially convolutional neural networks, have advanced the breast lesion classification task using breast ultrasound (BUS) images. However, constructing a highly-accurate classification model still remains challenging due to c...
Ultrasonography Cluster Analysis Research Design Ultrasonography, Mammary Humans Female Neural Networks, Computer
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