OBJECTIVES: To evaluate deep learning (DL)-based models for detecting periapical bone rarefaction (PBRs) in panoramic radiographs (PRs), analysing their feasibility and performance in dental practice.
PURPOSE: The purpose of this study is to perform image registration and averaging of multiple free-breathing single-shot cardiac images, where the individual images may have a low signal-to-noise ratio (SNR).
Static graphs play a pivotal role in modeling and analyzing biological and biomedical data. However, many real-world scenarios-such as disease progression and drug pharmacokinetic processes-exhibit dynamic behaviors. Consequently, static graph method...
In recent years, significant advancements have been achieved in applying deep learning (DL) to magnetic resonance imaging (MRI) reconstruction, which traditionally relies on fully sampled data. However, real-world clinical scenarios often demonstrate...
OBJECTIVES: This study explores the application of artificial intelligence (AI), specifically deep learning, in the detection and classification of mandibular fractures using CT scans.
OBJECTIVES: This study aimed to assess the efficacy of deep learning applications for the detection of nasal bone fracture on X-ray nasal bone lateral view.
OBJECTIVES: Deep learning-driven super resolution (SR) aims to enhance the quality and resolution of images, offering potential benefits in dental imaging. Although extensive research has focused on deep learning based dental classification tasks, th...
IEEE transactions on visualization and computer graphics
Sep 1, 2025
Accurately determining the clinical positions for each tooth is essential in orthodontics, while most existing solutions heavily rely on inefficient manual design. In this paper, we present the LETA, a dual-branch Latent Encoding based 3D Tooth Align...
The spine journal : official journal of the North American Spine Society
Sep 1, 2025
BACKGROUND CONTEXT: Lumbar foraminal stenosis (LFS) is a common spinal condition that requires accurate assessment. Current magnetic resonance imaging (MRI) reporting processes are often inefficient, and while deep learning has potential for improvem...
Medicinal and edible homologs (MEHs) offer significant preventive and therapeutic benefits for various diseases and health functions. However, the widespread application of MEHs faces significant challenges, particularly in quality control and rapid ...
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