This study aimed to validate the utility of commercially available vendor-neutral deep learning (DL) image enhancement software for improving the image quality of multiparametric MRI for gliomas in a multinational setting. A total of 294 patients fro...
Heart disease continues to rank among the world's top causes of death, underscoring the pressing need for precise and accurate prediction techniques. Performance issues with traditional machine learning techniques have been identified, particularly w...
QUS spectral parametric imaging offers a fast and accurate method for breast lesion characterization. This study explored using deep CNNs to classify breast lesions from QUS spectral parametric images, aiming to enhance radiomics and conventional mac...
Pneumonia is a prevalent and serious respiratory disease, responsible for a significant number of cases globally. With advancements in deep learning, the automatic diagnosis of pneumonia has attracted significant research attention in medical image c...
Brain metastases (BMs) are the most common intracranial tumors and stereotactic radiotherapy improved the life quality of patient with BMs, while it requires more time and experience to delineate BMs precisely by oncologists. Deep Learning techniques...
Monkeypox has arisen as a global health issue, requiring prompt and precise diagnosis for optimal management. Conventional diagnostic techniques, including PCR, are dependable yet frequently unattainable in resource-constrained environments. Deep lea...
BACKGROUND: Traditional Chinese medicine (TCM) education in China has evolved significantly, shaped by both national policy and social needs. Despite this, the academic community has yet to fully explore the long-term trends and core issues in TCM ed...
OBJECTIVES: Current dental CBCT segmentation tools often lack accuracy, accessibility, or comprehensive anatomical coverage. To address this, we constructed a densely annotated dental CBCT dataset and developed a deep learning model, OraSeg, for toot...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Sep 25, 2025
This paper examines the current challenges in computed tomography (CT), with a critical exploration of existing methodologies from a mathematical perspective. Specifically, it aims to identify research directions to enhance image quality in low-dose,...
Disaster medicine and public health preparedness
Sep 25, 2025
OBJECTIVES: Remote injury assessment during natural disasters poses major challenges for healthcare providers due to the inaccessibility of disaster sites. This study aimed to explore the feasibility of using artificial intelligence (AI) techniques f...
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