AIMC Journal:
Medical physics

Showing 381 to 390 of 732 articles

H-scan trajectories indicate the progression of specific diseases.

Medical physics Aug 3, 2021
PURPOSE: The ability of ultrasound to assess pathology is increasing with the development of quantitative parameters. Among these are a set of parameters derived from the recent H-scan analysis of subresolvable scattering. The emergence of these quan...
Humans Pancreatic Neoplasms Radionuclide Imaging Ultrasonography Support Vector Machine
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Generation of synthetic PET images of synaptic density and amyloid from F-FDG images using deep learning.

Medical physics Jul 27, 2021
PURPOSE: Positron emission tomography (PET) imaging with various tracers is increasingly used in Alzheimer's disease (AD) studies. However, access to PET scans using new or less-available tracers with sophisticated synthesis and short half-life isoto...
Fluorodeoxyglucose F18 Humans Brain Aniline Compounds Positron-Emission Tomography Deep Learning Alzheimer Disease
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Recognition of honeycomb lung in CT images based on improved MobileNet model.

Medical physics Jul 17, 2021
PURPOSE: The research is to improve the efficiency and accuracy of recognition of honeycomb lung in CT images.
Lung Machine Learning Tomography, X-Ray Computed
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Detecting lumbar lesions in Tc-MDP SPECT by deep learning: Comparison with physicians.

Medical physics Jul 11, 2021
PURPOSE: Tc-MDP single-photon emission computed tomography (SPECT) is an established tool for diagnosing lumbar stress, a common cause of low back pain (LBP) in pediatric patients. However, detection of small stress lesions is complicated by the low...
Humans Physicians Retrospective Studies Tomography, Emission-Computed, Single-Photon Technetium Tc 99m Medronate Deep Learning Child
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Using neural networks to extend cropped medical images for deformable registration among images with differing scan extents.

Medical physics Jul 11, 2021
PURPOSE: Missing or discrepant imaging volume is a common challenge in deformable image registration (DIR). To minimize the adverse impact, we train a neural network to synthesize cropped portions of head and neck CT's and then test its use in DIR.
Neck Head Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Imaging, Three-Dimensional
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A feasibility study on deep learning-based individualized 3D dose distribution prediction.

Medical physics Jul 11, 2021
PURPOSE: Radiation therapy treatment planning is a trial-and-error, often time-consuming process. An approximately optimal dose distribution corresponding to a specific patient's anatomy can be predicted by using pre-trained deep learning (DL) models...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Male Deep Learning Feasibility Studies
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DCANet: Dual contextual affinity network for mass segmentation in whole mammograms.

Medical physics Jul 7, 2021
PURPOSE: Breast mass segmentation in mammograms remains a crucial yet challenging topic in computer-aided diagnosis systems. Existing algorithms mainly used mass-centered patches to achieve mass segmentation, which is time-consuming and unstable in c...
Databases, Factual Diagnosis, Computer-Assisted Humans Neural Networks, Computer Breast Image Processing, Computer-Assisted Mammography
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FDRN: A fast deformable registration network for medical images.

Medical physics Jul 6, 2021
PURPOSE: Deformable image registration is a fundamental task in medical imaging. Due to the large computational complexity of deformable registration of volumetric images, conventional iterative methods usually face the tradeoff between the registrat...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Magnetic Resonance Imaging Neuroimaging Neural Networks, Computer
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Development of attenuation correction methods using deep learning in brain-perfusion single-photon emission computed tomography.

Medical physics Jun 28, 2021
PURPOSE: Computed tomography (CT)-based attenuation correction (CTAC) in single-photon emission computed tomography (SPECT) is highly accurate, but it requires hybrid SPECT/CT instruments and additional radiation exposure. To obtain attenuation corre...
Image Processing, Computer-Assisted Perfusion Brain Deep Learning Tomography, Emission-Computed, Single-Photon Single Photon Emission Computed Tomography Computed Tomography Humans
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Technical Note: Dose prediction for head and neck radiotherapy using a three-dimensional dense dilated U-net architecture.

Medical physics Jun 22, 2021
PURPOSE: Radiation therapy treatment planning is a time-consuming and iterative manual process. Consequently, plan quality varies greatly between and within institutions. Artificial intelligence shows great promise in improving plan quality and reduc...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Artificial Intelligence Radiotherapy, Intensity-Modulated Humans Deep Learning
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