IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
One way of resolving the problem of scarce and expensive data in deep learning for medical applications is using transfer learning and fine-tuning a network which has been trained on a large data set. The common practice in transfer learning is to ke...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Single plane wave transmissions are promising for automated imaging tasks requiring high ultrasound frame rates over an extended field of view. However, a single plane wave insonification typically produces suboptimal image quality. To address this l...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Deep fully connected networks are often considered "universal approximators" that are capable of learning any function. In this article, we utilize this particular property of deep neural networks (DNNs) to estimate normalized cross correlation as a ...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Tracking the myotendinous junction (MTJ) in consecutive ultrasound images is crucial for understanding the mechanics and pathological conditions of the muscle-tendon unit. However, the lack of reliable and efficient identification of MTJ due to poor ...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
In recent years, deep learning (DL) has been successfully applied to the analysis and processing of ultrasound images. To date, most of this research has focused on segmentation and view recognition. This article benchmarks different convolutional ne...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Knee arthroscopy is a complex minimally invasive surgery that can cause unintended injuries to femoral cartilage or postoperative complications, or both. Autonomous robotic systems using real-time volumetric ultrasound (US) imaging guidance hold pote...
OBJECTIVES: To evaluate the prediction performance of deep convolutional neural network (DCNN) based on ultrasound (US) images for the assessment of breast cancer molecular subtypes.
PURPOSE: Clinically, the risk stratification of thyroid nodules is usually used to formulate the next treatment plan. The American College of Radiology (ACR) thyroid imaging reporting and data system (TI-RADS) is a type of medical standard widely use...
The international journal of cardiovascular imaging
Nov 12, 2020
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "m...
Breast and thyroid cancers are the two common cancers to affect women worldwide. Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast and thyroid cancers, but its clinical diagnostic accuracy for these cancers is con...