AIMC Topic: Artifacts

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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...
Humans Dermoscopy Artifacts Hair Hair Removal Measles Deep Learning Image Processing, Computer-Assisted Skin
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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...
Motion Artifacts Signal-To-Noise Ratio Humans Algorithms Brain Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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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 ...
Artifacts Humans Large Language Models Language Models, Theoretical
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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...
Artifacts Four-Dimensional Computed Tomography Signal-To-Noise Ratio Deep Learning Phantoms, Imaging Image Processing, Computer-Assisted Humans Heart Neural Networks, Computer
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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...
Artifacts Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans
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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).
Humans Brain Female Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Artifacts Brain Diseases Signal-To-Noise Ratio Middle Aged Aged Deep Learning Adult Adolescent Male
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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).
Radiography, Dual-Energy Scanned Projection Deep Learning Algorithms Head and Neck Neoplasms Prospective Studies Neck Tomography, X-Ray Computed Adult Female Male Aged Humans Middle Aged Radiographic Image Interpretation, Computer-Assisted Aged, 80 and over Quality Improvement Artifacts Head Signal-To-Noise Ratio Computed Tomography Angiography
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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...
Humans Neural Networks, Computer Fourier Analysis Thermometry Hyperthermia Magnetic Resonance Imaging Neoplasms Artifacts Deep Learning Hyperthermia, Induced Image Processing, Computer-Assisted
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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...
Humans Deep Learning Metals Cone-Beam Computed Tomography Prostheses and Implants Artifacts
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VBVT-Net: VOI-Based VVBP-Tensor Network for High-Attenuation Artifact Suppression in Digital Breast Tomosynthesis Imaging.

IEEE transactions on medical imaging Apr 3, 2025
High-attenuation (HA) artifacts may lead to obscured subtle lesions and lesion over-estimation in digital breast tomosynthesis (DBT) imaging. High-attenuation artifact suppression (HAAS) is vital for widespread DBT applications in clinic. The convent...
Mammography Breast Artifacts Female Breast Neoplasms Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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