AIMC Topic: Artifacts
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Accelerating brain T2-weighted imaging using artificial intelligence-assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI.
BMC medical imaging
Jul 1, 2025
BACKGROUND: T2-weighted imaging (T2WI), renowned for its sensitivity to edema and lesions, faces clinical limitations due to prolonged scanning time, increasing patient discomfort, and motion artifacts. The individual applications of artificial intel...
Deep learning model for hair artifact removal and Mpox skin lesion analysis and detection.
Scientific reports
Jul 1, 2025
Accurate identification of Mpox is essential for timely diagnosis and treatment. However, traditional image-based diagnostic methods often struggle with challenges such as body hair obscuring skin lesions and complicating accurate assessment. To addr...
Artifact estimation network for MR images: effectiveness of batch normalization and dropout layers.
BMC medical imaging
May 1, 2025
BACKGROUND: Magnetic resonance imaging (MRI) is an essential tool for medical diagnosis. However, artifacts may degrade images obtained through MRI, especially owing to patient movement. Existing methods that mitigate the artifact problem are subject...
Prompt architecture induces methodological artifacts in large language models.
PloS one
Apr 28, 2025
We examine how the seemingly arbitrary way a prompt is posed, which we term "prompt architecture," influences responses provided by large language models (LLMs). Five large-scale, full-factorial experiments performing standard (zero-shot) similarity ...
An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans.
Physics in medicine and biology
Apr 22, 2025
Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These artifacts result from involuntary cardiac motion, and traditional mitigation methods typically rely...
One for multiple: Physics-informed synthetic data boosts generalizable deep learning for fast MRI reconstruction.
Medical image analysis
Apr 20, 2025
Magnetic resonance imaging (MRI) is a widely used radiological modality renowned for its radiation-free, comprehensive insights into the human body, facilitating medical diagnoses. However, the drawback of prolonged scan times hinders its accessibili...
Assessment of AI-accelerated T2-weighted brain MRI, based on clinical ratings and image quality evaluation.
European journal of radiology
Apr 16, 2025
OBJECTIVE: To compare clinical ratings and signal-to-noise ratio (SNR) measures of a commercially available Deep Learning-based MRI reconstruction method (T2) against conventional T2- turbo spin echo brain MRI (T2).
Image quality improvement in head and neck angiography based on dual-energy CT and deep learning.
BMC medical imaging
Apr 10, 2025
OBJECTIVE: Compare the image quality of image reconstructed using deep learning-based image reconstruction (DLIR) and iterative reconstruction algorithms for head and neck dual-energy CT angiography (DECTA).
Head and Neck Neoplasms
Neck
Radiographic Image Interpretation, Computer-Assisted
Male
Middle Aged
Deep Learning
Signal-To-Noise Ratio
Algorithms
Aged, 80 and over
Computed Tomography Angiography
Prospective Studies
Quality Improvement
Humans
Radiography, Dual-Energy Scanned Projection
Adult
Tomography, X-Ray Computed
Artifacts
Female
Head
Aged
Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.
Scientific reports
Apr 6, 2025
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...
Parametric-MAA: fast, object-centric avoidance of metal artifacts for intraoperative CBCT.
International journal of computer assisted radiology and surgery
Apr 5, 2025
PURPOSE: Metal artifacts remain a persistent issue in intraoperative CBCT imaging. Particularly in orthopedic and trauma applications, these artifacts obstruct clinically relevant areas around the implant, reducing the modality's clinical value. Meta...
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