AIMC Journal:
Medical physics

Showing 481 to 490 of 732 articles

Dose image prediction for range and width verifications from carbon ion-induced secondary electron bremsstrahlung x-rays using deep learning workflow.

Medical physics May 25, 2020
PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition,...
Workflow Electrons X-Rays Deep Learning Carbon
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Inspection of visible components in urine based on deep learning.

Medical physics May 14, 2020
PURPOSE: Urinary particles are particularly important parameters in clinical urinalysis, especially for the diagnosis of nephropathy. Therefore, it is highly important to precisely detect urinary particles in the clinical setting. However, artificial...
Neural Networks, Computer Algorithms Kidney Diseases Humans Microscopy Deep Learning Image Processing, Computer-Assisted
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Development of a real-time indoor location system using bluetooth low energy technology and deep learning to facilitate clinical applications.

Medical physics May 11, 2020
PURPOSE: An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy because Bl...
Neural Networks, Computer Algorithms Computer Systems Technology Humans Deep Learning
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AirNet: Fused analytical and iterative reconstruction with deep neural network regularization for sparse-data CT.

Medical physics Apr 30, 2020
PURPOSE: Sparse-data computed tomography (CT) frequently occurs, such as breast tomosynthesis, C-arm CT, on-board four-dimensional cone-beam CT (4D CBCT), and industrial CT. However, sparse-data image reconstruction remains challenging due to highly ...
Phantoms, Imaging Four-Dimensional Computed Tomography Algorithms Image Processing, Computer-Assisted Photons Neural Networks, Computer
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A hybrid convolutional neural network for super-resolution reconstruction of MR images.

Medical physics Apr 27, 2020
PURPOSE: Spatial resolution is an important parameter for magnetic resonance imaging (MRI). High-resolution MR images provide detailed information and benefit subsequent image analysis. However, higher resolution MR images come at the expense of long...
Algorithms Image Processing, Computer-Assisted Neural Networks, Computer Signal-To-Noise Ratio Magnetic Resonance Imaging
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Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.

Medical physics Apr 8, 2020
PURPOSE: Needle-based procedures for diagnosing and treating prostate cancer, such as biopsy and brachytherapy, have incorporated three-dimensional (3D) transrectal ultrasound (TRUS) imaging to improve needle guidance. Using these images effectively ...
Male Brachytherapy Prostate Deep Learning Image Processing, Computer-Assisted Humans Ultrasonography Prostatic Neoplasms Imaging, Three-Dimensional
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A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPU-accelerated Monte Carlo dose computing.

Medical physics Apr 3, 2020
PURPOSE: One technical barrier to patient-specific computed tomography (CT) dosimetry has been the lack of computational tools for the automatic patient-specific multi-organ segmentation of CT images and rapid organ dose quantification. When previous...
Prospective Studies Tomography, X-Ray Computed Deep Learning Monte Carlo Method Humans Phantoms, Imaging
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Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.

Medical physics Mar 18, 2020
PURPOSE: Multiview two-dimensional (2D) convolutional neural networks (CNNs) and three-dimensional (3D) CNNs have been successfully used for analyzing volumetric data in many state-of-the-art medical imaging applications. We propose an alternative mo...
Sensitivity and Specificity Radiography, Thoracic Neural Networks, Computer Humans Lung Neoplasms Image Processing, Computer-Assisted Tomography, X-Ray Computed False Positive Reactions
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A deep-learning-based approach for adenoid hypertrophy diagnosis.

Medical physics Mar 10, 2020
PURPOSE: Adenoid hypertrophy is a pathological hyperplasia of adenoids and may cause snoring, apnea, and impede breathing during sleep. In clinical practice, radiologists diagnose the severity of adenoid hypertrophy by measuring the ratio of adenoid ...
Adenoids Image Processing, Computer-Assisted Deep Learning Hypertrophy
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Multicontext multitask learning networks for mass detection in mammogram.

Medical physics Mar 5, 2020
PURPOSE: In this paper, for the purpose of accurate and efficient mass detection, we propose a new deep learning framework, including two major stages: Suspicious region localization (SRL) and Multicontext Multitask Learning (MCMTL).
Mammography Machine Learning Breast Neoplasms Image Processing, Computer-Assisted
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