OBJECTIVES: The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue phantom of fat, muscle and bone. Virtual monoenergetic images (VMI) by dual-energy measurements and...
The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on elderly patients with chronic heart failure (CHF) complicated with sarcopenia, so as to analyze the ...
INTRODUCTION: Low-dose computed tomography tends to produce lower image quality than normal dose computed tomography (CT) although it can help to reduce radiation hazards of CT scanning. Research has shown that Artificial Intelligence (AI) technologi...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jul 26, 2021
Ultrasound sound-speed tomography (USST) has shown great prospects for breast cancer diagnosis due to its advantages of nonradiation, low cost, 3-D breast images, and quantitative indicators. However, the reconstruction quality of USST is highly depe...
The need to classify targets and features in high-resolution imagery is of interest in applications such as detection of landmines in ground penetrating radar and tumors in medical ultrasound images. Convolutional neural networks (CNNs) trained using...
Our study aims to improve the signal-to-noise ratio of positron emission tomography (PET) imaging using conditional unsupervised learning. The proposed method does not require low- and high-quality pairs for network training which can be easily appli...
PURPOSE: This work was aimed at designing a deep-learning-based approach for MR image phase unwrapping to improve the robustness and efficiency of traditional methods.
Computer methods and programs in biomedicine
Jul 13, 2021
Background and Objective Electrocardiogram (ECG) quality assessment is significant for automatic diagnosis of cardiovascular disease and reducing the massive workload of reviewing continuous ECGs. Hence, how to design an appropriate algorithm for obj...
BACKGROUND: To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in pediatric head CT for improving image quality and lesion detection with 0.625 mm thin-slice images.
Raman spectroscopy is a powerful diagnostic tool in biomedical science, whereby different disease groups can be classified based on subtle differences in the cell or tissue spectra. A key component in the classification of Raman spectra is the applic...