IEEE journal of biomedical and health informatics
Mar 6, 2025
The performance of modern U-shaped neural networks for medical image segmentation has been significantly enhanced by incorporating Transformer layers. Although Transformer architectures are powerful at extracting global information, its ability to ca...
IEEE journal of biomedical and health informatics
Mar 6, 2025
The global increase in lung cancer cases, often marked by pulmonary nodules, underscores the critical importance of timely detection to mitigate cancer progression and reduce morbidity and mortality. The Faster R-CNN approach is a two-stage, high-pre...
IEEE journal of biomedical and health informatics
Mar 6, 2025
Low-dose computed tomography (LDCT) is a specialized CT scan with a lower radiation dose than normal-dose CT. However, the reduced radiation dose can introduce noise and artifacts, affecting diagnostic accuracy. To enhance the LDCT image quality, we ...
Ground-glass opacities (GGOs) are hazy opacities on chest computed tomography (CT) scans that can indicate various lung diseases, including early COVID-19, pneumonia, and lung cancer. Artificial intelligence (AI) is a promising tool for analyzing med...
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...
Large language models have shown efficacy across multiple medical tasks. However, their value in the assessment of longitudinal follow-up computed tomography (CT) images of patients with lung nodules is unclear. In this study, we evaluate the ability...
Journal of X-ray science and technology
Mar 3, 2025
BACKGROUND:  Myocardial blood flow (MBF) provides important diagnostic information for myocardial ischemia. However, dynamic computed tomography perfusion (CTP) needed for MBF involves multiple exposures, leading to high radiation doses.
Journal of applied clinical medical physics
Mar 2, 2025
BACKGROUND: This study aims to develop a novel predictive model for determining human papillomavirus (HPV) presence in oropharyngeal cancer using computed tomography (CT). Current image-based HPV prediction methods are hindered by high computational ...
BACKGROUND: To develop and validate a model that integrates clinical data, deep learning radiomics, and radiomic features to predict high-risk patients for cage subsidence (CS) after lumbar fusion.