AIMC Journal:
Medical physics

Showing 451 to 460 of 732 articles

A multiple-channel and atrous convolution network for ultrasound image segmentation.

Medical physics Oct 18, 2020
PURPOSE: Ultrasound image segmentation is a challenging task due to a low signal-to-noise ratio and poor image quality. Although several approaches based on the convolutional neural network (CNN) have been applied to ultrasound image segmentation, th...
Neural Networks, Computer Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Self-contained deep learning-based boosting of 4D cone-beam CT reconstruction.

Medical physics Oct 15, 2020
PURPOSE: Four-dimensional cone-beam computed tomography (4D CBCT) imaging has been suggested as a solution to account for interfraction motion variability of moving targets like lung and liver during radiotherapy (RT) of moving targets. However, due ...
Humans Image Processing, Computer-Assisted Four-Dimensional Computed Tomography Algorithms Deep Learning Phantoms, Imaging Cone-Beam Computed Tomography
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A deep learning model to predict dose-volume histograms of organs at risk in radiotherapy treatment plans.

Medical physics Oct 15, 2020
PURPOSE: To develop a deep learning-based model to predict achievable dose-volume histograms (DVHs) of organs at risk (OARs) for automation of inverse planning.
Humans Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Deep Learning Organs at Risk
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Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation.

Medical physics Oct 15, 2020
PURPOSE: Volumetric pancreas segmentation can be used in the diagnosis of pancreatic diseases, the research about diabetes and surgical planning. Since manual delineation is time-consuming and laborious, we develop a deep learning-based framework for...
Pancreas Image Processing, Computer-Assisted Abdomen Neural Networks, Computer Tomography, X-Ray Computed
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The delineation of largely deformed brain midline using regression-based line detection network.

Medical physics Oct 15, 2020
PURPOSE: The human brain has two cerebral hemispheres that are roughly symmetric and separated by a midline, which is nearly a straight line shown in axial computed tomography (CT) images in healthy subjects. However, brain diseases such as hematoma ...
Humans Tomography, X-Ray Computed Cohort Studies Neural Networks, Computer Brain
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Automatic segmentation, classification, and follow-up of optic pathway gliomas using deep learning and fuzzy c-means clustering based on MRI.

Medical physics Oct 8, 2020
PURPOSE: Optic pathway gliomas (OPG) are low-grade pilocytic astrocytomas accounting for 3-5% of pediatric intracranial tumors. Accurate and quantitative follow-up of OPG using magnetic resonance imaging (MRI) is crucial for therapeutic decision maki...
Glioma Follow-Up Studies Magnetic Resonance Imaging Cluster Analysis Deep Learning Child Humans Retrospective Studies
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Complete abdomen and pelvis segmentation using U-net variant architecture.

Medical physics Oct 7, 2020
PURPOSE: Organ segmentation of computed tomography (CT) imaging is essential for radiotherapy treatment planning. Treatment planning requires segmentation not only of the affected tissue, but nearby healthy organs-at-risk, which is laborious and time...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Humans Neural Networks, Computer Organs at Risk Abdomen Pelvis
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Technical Note: Automatic segmentation of CT images for ventral body composition analysis.

Medical physics Oct 3, 2020
PURPOSE: Body composition is known to be associated with many diseases including diabetes, cancers, and cardiovascular diseases. In this paper, we developed a fully automatic body tissue decomposition procedure to segment three major compartments tha...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Body Composition Torso Humans Neural Networks, Computer
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Evaluation of a multiview architecture for automatic vertebral labeling of palliative radiotherapy simulation CT images.

Medical physics Sep 15, 2020
PURPOSE: The purpose of this work was to evaluate the performance of X-Net, a multiview deep learning architecture, to automatically label vertebral levels (S2-C1) in palliative radiotherapy simulation CT scans.
Tomography, X-Ray Computed Neural Networks, Computer Humans Lumbar Vertebrae ROC Curve Computer Simulation
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Comparison of iterative parametric and indirect deep learning-based reconstruction methods in highly undersampled DCE-MR Imaging of the breast.

Medical physics Sep 6, 2020
PURPOSE: To compare the performance of iterative direct and indirect parametric reconstruction methods with indirect deep learning-based reconstruction methods in estimating tracer-kinetic parameters from highly undersampled DCE-MR Imaging breast dat...
Deep Learning Humans Magnetic Resonance Imaging Algorithms Image Processing, Computer-Assisted Kinetics Retrospective Studies
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