AIMC Journal:
Medical physics

Showing 501 to 510 of 732 articles

Technical Note: 3D localization of lung tumors on cone beam CT projections via a convolutional recurrent neural network.

Medical physics Jan 28, 2020
PURPOSE: To design a convolutional recurrent neural network (CRNN) that calculates three-dimensional (3D) positions of lung tumors from continuously acquired cone beam computed tomography (CBCT) projections, and facilitates the sorting and reconstruc...
Imaging, Three-Dimensional Lung Neoplasms Humans Neural Networks, Computer Cone-Beam Computed Tomography
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Reconstruction of multicontrast MR images through deep learning.

Medical physics Jan 28, 2020
PURPOSE: Magnetic resonance (MR) imaging with a long scan time can lead to degraded images due to patient motion, patient discomfort, and increased costs. For these reasons, the role of rapid MR imaging is important. In this study, we propose the joi...
Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Deep Learning
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A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation.

Medical physics Jan 28, 2020
PURPOSE: The purpose of this study is to develop a deep learning (DL) method for producing four-dimensional computed tomography (4DCT) ventilation imaging and to evaluate the accuracy of the DL-based ventilation imaging against single-photon emission...
Pulmonary Ventilation Tomography, Emission-Computed, Single-Photon Four-Dimensional Computed Tomography Deep Learning Image Processing, Computer-Assisted Humans
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Fast contour propagation for MR-guided prostate radiotherapy using convolutional neural networks.

Medical physics Jan 23, 2020
PURPOSE: To quickly and automatically propagate organ contours from pretreatment to fraction images in magnetic resonance (MR)-guided prostate external-beam radiotherapy.
Magnetic Resonance Imaging Prostatic Neoplasms Humans Dose Fractionation, Radiation Radiotherapy, Image-Guided Neural Networks, Computer Male Time Factors Image Processing, Computer-Assisted
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DC-AL GAN: Pseudoprogression and true tumor progression of glioblastoma multiform image classification based on DCGAN and AlexNet.

Medical physics Jan 20, 2020
PURPOSE: Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM on the follow-up magn...
Area Under Curve Magnetic Resonance Imaging Deep Learning Glioblastoma Image Processing, Computer-Assisted Humans Disease Progression
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A fast deep learning approach for beam orientation optimization for prostate cancer treated with intensity-modulated radiation therapy.

Medical physics Jan 20, 2020
PURPOSE: Beam orientation selection, whether manual or protocol-based, is the current clinical standard in radiation therapy treatment planning, but it is tedious and can yield suboptimal results. Many algorithms have been designed to optimize beam o...
Prostatic Neoplasms Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Deep Learning Time Factors Humans Male
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Synthetic CT generation from CBCT images via deep learning.

Medical physics Jan 13, 2020
PURPOSE: Cone-beam computed tomography (CBCT) scanning is used daily or weekly (i.e., on-treatment CBCT) for accurate patient setup in image-guided radiotherapy. However, inaccuracy of CT numbers prevents CBCT from performing advanced tasks such as d...
Humans Deep Learning Image Processing, Computer-Assisted Cone-Beam Computed Tomography
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Adaptive weighted log subtraction based on neural networks for markerless tumor tracking using dual-energy fluoroscopy.

Medical physics Jan 10, 2020
PURPOSE: To present a novel method, based on convolutional neural networks (CNN), to automate weighted log subtraction (WLS) for dual-energy (DE) fluoroscopy to be used in conjunction with markerless tumor tracking (MTT).
Neoplasms Phantoms, Imaging Fluoroscopy Image Processing, Computer-Assisted Neural Networks, Computer Subtraction Technique Calibration
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A 3D deep convolutional neural network approach for the automated measurement of cerebellum tracer uptake in FDG PET-CT scans.

Medical physics Jan 6, 2020
PURPOSE: The purpose of this work was to assess the potential of deep convolutional neural networks in automated measurement of cerebellum tracer uptake in F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) scans.
Positron Emission Tomography Computed Tomography Biological Transport Neural Networks, Computer Imaging, Three-Dimensional Fluorodeoxyglucose F18 Cerebellum Automation Humans
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A computer-aided diagnosis system for differentiation and delineation of malignant regions on whole-slide prostate histopathology image using spatial statistics and multidimensional DenseNet.

Medical physics Jan 6, 2020
PURPOSE: Prostate cancer (PCa) is a major health concern in aging males, and proper management of the disease depends on accurately interpreting pathology specimens. However, reading prostatectomy histopathology slides, which is basically for staging...
Neural Networks, Computer Prostatic Neoplasms Male Humans Diagnosis, Computer-Assisted Image Processing, Computer-Assisted
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