AIMC Topic: Phantoms, Imaging

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Low-contrast lesion detection in neck CT: a multireader study comparing deep learning, iterative, and filtered back projection reconstructions using realistic phantoms.

European radiology experimental Jul 24, 2024
BACKGROUND: Computed tomography (CT) reconstruction algorithms can improve image quality, especially deep learning reconstruction (DLR). We compared DLR, iterative reconstruction (IR), and filtered back projection (FBP) for lesion detection in neck C...
Phantoms, Imaging Head and Neck Neoplasms Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans Algorithms Tomography, X-Ray Computed Deep Learning
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Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.

Magnetic resonance in medicine Jul 19, 2024
PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods.
Mice Animals Magnetic Resonance Imaging Deep Learning Principal Component Analysis Image Processing, Computer-Assisted Signal-To-Noise Ratio Algorithms Phantoms, Imaging
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Deep coherence learning: An unsupervised deep beamformer for high quality single plane wave imaging in medical ultrasound.

Ultrasonics Jul 19, 2024
Plane wave imaging (PWI) in medical ultrasound is becoming an important reconstruction method with high frame rates and new clinical applications. Recently, single PWI based on deep learning (DL) has been studied to overcome lowered frame rates of tr...
Unsupervised Machine Learning Phantoms, Imaging Deep Learning Ultrasonography Image Processing, Computer-Assisted Humans
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Deep learning-enabled high-speed, multi-parameter diffuse optical tomography.

Journal of biomedical optics Jul 19, 2024
SIGNIFICANCE: Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical breast tumor characterization. However, conventional diffuse optical tomography (DOT) image reconstruction algorithms require case-by-case expert tuning and are...
Humans Algorithms Imaging, Three-Dimensional Image Processing, Computer-Assisted Breast Female Breast Neoplasms Deep Learning Phantoms, Imaging Tomography, Optical
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Deep learning reconstruction for zero echo time lung magnetic resonance imaging: impact on image quality and lesion detection.

Clinical radiology Jul 17, 2024
AIMS: This study aimed to examine the impact of deep-learning reconstruction (DLR) on zero echo time (ZTE) lung MRI.
Phantoms, Imaging Humans Middle Aged Aged Lung Lung Neoplasms Retrospective Studies Adult Magnetic Resonance Imaging Tomography, X-Ray Computed Deep Learning Male Image Interpretation, Computer-Assisted Female
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Fast, high-quality, and unshielded 0.2 T low-field mobile MRI using minimal hardware resources.

Magma (New York, N.Y.) Jul 5, 2024
OBJECTIVE: To propose a deep learning-based low-field mobile MRI strategy for fast, high-quality, unshielded imaging using minimal hardware resources.
Adult Male Deep Learning Algorithms Brain Female Healthy Volunteers Humans Signal-To-Noise Ratio Image Processing, Computer-Assisted Phantoms, Imaging Magnetic Resonance Imaging Equipment Design
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Single-Subject Deep-Learning Image Reconstruction With a Neural Optimization Transfer Algorithm for PET-Enabled Dual-Energy CT Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jul 4, 2024
Combining dual-energy computed tomography (DECT) with positron emission tomography (PET) offers many potential clinical applications but typically requires expensive hardware upgrades or increases radiation doses on PET/CT scanners due to an extra X-...
Image Processing, Computer-Assisted Algorithms Humans Positron Emission Tomography Computed Tomography Tomography, X-Ray Computed Neural Networks, Computer Phantoms, Imaging Deep Learning
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Immune Cell-Based Microrobots for Remote Magnetic Actuation, Antitumor Activity, and Medical Imaging.

Advanced healthcare materials Jun 25, 2024
Translating medical microrobots into clinics requires tracking, localization, and performing assigned medical tasks at target locations, which can only happen when appropriate design, actuation mechanisms, and medical imaging systems are integrated i...
Robotics RAW 264.7 Cells Humans Phantoms, Imaging Cell Line, Tumor Photoacoustic Techniques Macrophages Animals Mice Magnetic Resonance Imaging
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Learning-Assisted Fast Determination of Regularization Parameter in Constrained Image Reconstruction.

IEEE transactions on bio-medical engineering Jun 19, 2024
OBJECTIVE: To leverage machine learning (ML) for fast selection of optimal regularization parameter in constrained image reconstruction.
Machine Learning Algorithms Image Processing, Computer-Assisted Magnetic Resonance Imaging Phantoms, Imaging Humans Neural Networks, Computer
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Super-resolution deep-learning reconstruction for cardiac CT: impact of radiation dose and focal spot size on task-based image quality.

Physical and engineering sciences in medicine Jun 17, 2024
This study aimed to evaluate the impact of radiation dose and focal spot size on the image quality of super-resolution deep-learning reconstruction (SR-DLR) in comparison with iterative reconstruction (IR) and normal-resolution DLR (NR-DLR) algorithm...
Phantoms, Imaging Heart Tomography, X-Ray Computed Radiation Dosage Signal-To-Noise Ratio Deep Learning Image Processing, Computer-Assisted Humans Algorithms
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