AIMC Topic: Signal-To-Noise Ratio
Clear Filters Showing 111 to 120 of 871 articles
Accelerated Spine MRI with Deep Learning Based Image Reconstruction: A Prospective Comparison with Standard MRI.
Academic radiology
Nov 22, 2024
RATIONALE AND OBJECTIVES: To evaluate the performance of deep learning (DL) reconstructed MRI in terms of image acquisition time, overall image quality and diagnostic interchangeability compared to standard-of-care (SOC) MRI.
Unsupervised Deep Learning for Synthetic CT Generation from CBCT Images for Proton and Carbon Ion Therapy for Paediatric Patients.
Sensors (Basel, Switzerland)
Nov 22, 2024
Image-guided treatment adaptation is a game changer in oncological particle therapy (PT), especially for younger patients. The purpose of this study is to present a cycle generative adversarial network (CycleGAN)-based method for synthetic computed t...
GraFMRI: A graph-based fusion framework for robust multi-modal MRI reconstruction.
Magnetic resonance imaging
Nov 17, 2024
PURPOSE: This study introduces GraFMRI, a novel framework designed to address the challenges of reconstructing high-quality MRI images from undersampled k-space data. Traditional methods often suffer from noise amplification and loss of structural de...
Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.
Journal of applied clinical medical physics
Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Radiographic Image Enhancement
Phantoms, Imaging
Abdominal Neoplasms
Radiotherapy, Image-Guided
Humans
Algorithms
Feasibility Studies
Organs at Risk
Male
Radiotherapy Planning, Computer-Assisted
Prospective Studies
Radiation Dosage
Deep Learning
Tomography, X-Ray Computed
Image Processing, Computer-Assisted
Female
Signal-To-Noise Ratio
Radiographic Image Interpretation, Computer-Assisted
Pelvic Neoplasms
Radiotherapy Dosage
Radiotherapy, Intensity-Modulated
Comparison of different acceleration factors of artificial intelligence-compressed sensing for brachial plexus MRI imaging: scanning time and image quality.
BMC medical imaging
Nov 14, 2024
BACKGROUND: 3D brachial plexus MRI scanning is prone to examination failure due to the lengthy scan times, which can lead to patient discomfort and motion artifacts. Our purpose is to investigate the efficacy of artificial intelligence-assisted compr...
Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study.
Journal of computer assisted tomography
Nov 13, 2024
OBJECTIVE: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.
MRI denoising with a non-blind deep complex-valued convolutional neural network.
NMR in biomedicine
Nov 11, 2024
MR images with high signal-to-noise ratio (SNR) provide more diagnostic information. Various methods for MRI denoising have been developed, but the majority of them operate on the magnitude image and neglect the phase information. Therefore, the goal...
Image quality in three-dimensional (3D) contrast-enhanced dynamic magnetic resonance imaging of the abdomen using deep learning denoising technique: intraindividual comparison between T1-weighted sequences with compressed sensing and with a modified Fast 3D mode wheel.
Japanese journal of radiology
Nov 6, 2024
PURPOSE: To assess the image quality of a modified Fast three-dimensional (Fast 3D) mode wheel with sequential data filling (mFast 3D wheel) combined with a deep learning denoising technique (Advanced Intelligent Clear-IQ Engine [AiCE]) in contrast-e...
Speech recognition using an english multimodal corpus with integrated image and depth information.
Scientific reports
Nov 6, 2024
Traditional English corpora mainly collect information from a single modality, but lack information from multimodal information, resulting in low quality of corpus information and certain problems with recognition accuracy. To solve the above problem...
Self-Supervised Medical Image Denoising Based on WISTA-Net for Human Healthcare in Metaverse.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Medical image processing plays an important role in the interaction of real world and metaverse for healthcare. Self-supervised denoising based on sparse coding methods, without any prerequisite on large-scale training samples, has been attracting ex...
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