Multi-component T1ρ mapping of the knee joint using nonlinear least squares (NLS)-based methods is usually a computationally intensive task, limiting its application to only a few voxels in the knee joint. Deep learning (DL) is a computationally fast...
INTRODUCTION: Effective communication is a critical skill for surgeons that commences often with history-taking. While simulation-based training is utilized to enhance these skills, recent advancements in artificial intelligence (AI), especially deep...
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Sep 1, 2025
INTRODUCTION: Deep learning (DL) models have achieved remarkable performance in musculoskeletal (MSK) medical imaging research, yet their clinical integration remains hindered by their black-box nature and the absence of reliable confidence measures....
Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Sep 1, 2025
Middle ear disease occurs frequently in dogs. CT has proven to be an excellent diagnostic tool for detecting middle ear structures, helping to achieve rapid and accurate diagnoses. Deep learning techniques are now widely used in CT scan-based human m...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Sep 1, 2025
Ultrasonic attenuation can be used to characterize tissue properties of the human breast. Both quantitative ultrasound (QUS) and ultrasound tomography (USCT) can provide attenuation estimation. However, limitations have been identified for both appro...
Selection bias has been identified in hypotension prediction models, but its impact on an algorithm's ability to learn relevant information from the arterial waveform remains unclear. The recent study by Yang and colleagues sheds considerable light o...
Diabetes is one of the most common diseases worldwide and requires accurate diagnosis. Patients with diabetes are often affected by diabetic retinopathy (DR), which can lead to low vision, vision loss, or blindness. Therefore, a robust computer-aided...
Recent advances in PET image reconstruction have focused on achieving high image quality and quantitative accuracy. Bayesian penalized likelihood (BPL) algorithms, such as Q.Clear and HYPER Iterative that have been integrated into commercial PET syst...
Purpose To develop a deep learning model that uses a single inspiratory chest CT scan to perform parametric response mapping (PRM) and predict functional small airways disease (fSAD). Materials and Methods In this retrospective study, predictive and ...
RATIONALE AND OBJECTIVES: A common site of metastases for a variety of cancers is the bone, which is challenging and time consuming to review and important for cancer staging. Here, we developed a deep learning approach for detection and classificati...
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