Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jun 27, 2020
OBJECTIVES: We sought to generate realistic synthetic breast ultrasound images and express virtual interpolation images of tumors using a deep convolutional generative adversarial network (DCGAN).
Breast cancer ranks first among cancers affecting women's health. Our work aims to realize the intelligence of the medical ultrasound equipment with limited computational capability, which is used for the assistant detection of breast lesions. We emb...
The automated whole breast ultrasound (AWBUS) is a new breast imaging technique that can depict the whole breast anatomy. To facilitate the reading of AWBUS images and support the breast density estimation, an automatic breast anatomy segmentation me...
We propose a novel BIRADS-SSDL network that integrates clinically-approved breast lesion characteristics (BIRADS features) into task-oriented semi-supervised deep learning (SSDL) for accurate diagnosis of ultrasound (US) images with a small training ...
In current breast ultrasound computer aided diagnosis systems, the radiologist preselects a region of interest (ROI) as an input for computerised breast ultrasound image analysis. This task is time consuming and there is inconsistency among human exp...
AJR. American journal of roentgenology
Apr 22, 2020
The objective of this study was to assess the impact of artificial intelligence (AI)-based decision support (DS) on breast ultrasound (US) lesion assessment. A multicenter retrospective review of 900 breast lesions (470/900 [52.2%] benign; 430/900 ...
To assist radiologists in breast cancer classification in automated breast ultrasound (ABUS) imaging, we propose a computer-aided diagnosis based on a convolutional neural network (CNN) that classifies breast lesions as benign and malignant. The prop...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Feb 10, 2020
Breast cancer accounts for the second-largest number of deaths in women around the world, and more than 8% of women will suffer from the disease in their lifetime. Mortality due to breast cancer can be reduced by its early and precise diagnosis. Many...
Accurate tracking of tissue motion is critically important for several ultrasound elastography methods. In this study, we investigate the feasibility of using three published convolution neural network (CNN) models built for optical flow (hereafter r...
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