AIMC Journal:
Medical physics

Showing 401 to 410 of 732 articles

Improving CBCT quality to CT level using deep learning with generative adversarial network.

Medical physics May 14, 2021
PURPOSE: To improve image quality and computed tomography (CT) number accuracy of daily cone beam CT (CBCT) through a deep learning methodology with generative adversarial network.
Tomography, X-Ray Computed Deep Learning Humans Radiotherapy Planning, Computer-Assisted Spiral Cone-Beam Computed Tomography Cone-Beam Computed Tomography Image Processing, Computer-Assisted
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Interactive contouring through contextual deep learning.

Medical physics May 3, 2021
PURPOSE: To investigate a deep learning approach that enables three-dimensional (3D) segmentation of an arbitrary structure of interest given a user provided two-dimensional (2D) contour for context. Such an approach could decrease delineation times ...
Heart Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Artificial intelligence for prediction of measurement-based patient-specific quality assurance is ready for prime time.

Medical physics Apr 28, 2021
Artificial Intelligence Machine Learning Humans
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Incorporation of residual attention modules into two neural networks for low-dose CT denoising.

Medical physics Apr 23, 2021
PURPOSE: The low-dose computed tomography (CT) imaging can reduce the damage caused by x-ray radiation to the human body. However, low-dose CT images have a different degree of artifacts than conventional CT images, and their resolution is lower than...
Tomography, X-Ray Computed Neural Networks, Computer Humans Attention Algorithms Signal-To-Noise Ratio Image Processing, Computer-Assisted
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DVHnet: A deep learning-based prediction of patient-specific dose volume histograms for radiotherapy planning.

Medical physics Apr 18, 2021
PURPOSE: To develop a deep learning method to predict patient-specific dose volume histograms (DVHs) for radiotherapy planning.
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Deep Learning Humans
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Whole-brain functional MRI registration based on a semi-supervised deep learning model.

Medical physics Apr 15, 2021
PURPOSE: Traditional registration of functional magnetic resonance images (fMRI) is typically achieved through registering their coregistered structural MRI. However, it cannot achieve accurate performance in that functional units which are not neces...
Brain Mapping Deep Learning White Matter Gray Matter Magnetic Resonance Imaging Brain
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Accelerated multicontrast reconstruction for synthetic MRI using joint parallel imaging and variable splitting networks.

Medical physics Apr 12, 2021
PURPOSE: Synthetic magnetic resonance imaging (MRI) requires the acquisition of multicontrast images to estimate quantitative parameter maps, such as T , T , and proton density (PD). The study aims to develop a multicontrast reconstruction method bas...
Deep Learning Neural Networks, Computer Magnetic Resonance Imaging Image Processing, Computer-Assisted Tomography, X-Ray Computed
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Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification.

Medical physics Apr 12, 2021
PURPOSE: Transfer learning is commonly used in deep learning for medical imaging to alleviate the problem of limited available data. In this work, we studied the risk of feature leakage and its dependence on sample size when using pretrained deep con...
Algorithms Mammography Neural Networks, Computer Sample Size Breast Humans
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Point/Counterpoint. Artificial intelligence should be part of medical physics graduate program curriculum.

Medical physics Apr 11, 2021
Artificial Intelligence Curriculum Health Physics Education, Graduate Physics Education, Medical, Graduate
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Three-dimensional image volumes from two-dimensional digitally reconstructed radiographs: A deep learning approach in lower limb CT scans.

Medical physics Apr 3, 2021
PURPOSE: Three-dimensional (3D) reconstructions of the human anatomy have been available for surgery planning or diagnostic purposes for a few years now. The different image modalities usually rely on several consecutive two-dimensional (2D) acquisit...
Tomography, X-Ray Computed Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Neural Networks, Computer Radiography
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