AIMC Journal:
Medical physics

Showing 561 to 570 of 759 articles

Computationally efficient deep neural network for computed tomography image reconstruction.

Medical physics Sep 21, 2019
PURPOSE: Deep neural network-based image reconstruction has demonstrated promising performance in medical imaging for undersampled and low-dose scenarios. However, it requires large amount of memory and extensive time for the training. It is especial...
Deep Learning Time Factors Tomography, X-Ray Computed Quality Control Radiation Dosage Imaging, Three-Dimensional Image Processing, Computer-Assisted
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Image reconstruction for positron emission tomography based on patch-based regularization and dictionary learning.

Medical physics Sep 20, 2019
PURPOSE: Positron emission tomography (PET) is an important tool for nuclear medical imaging. It has been widely used in clinical diagnosis, scientific research, and drug testing. PET is a kind of emission computed tomography. Its basic imaging princ...
Humans Positron-Emission Tomography Time Factors Signal-To-Noise Ratio Machine Learning Image Processing, Computer-Assisted Brain
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Segmentation of dental cone-beam CT scans affected by metal artifacts using a mixed-scale dense convolutional neural network.

Medical physics Sep 13, 2019
PURPOSE: In order to attain anatomical models, surgical guides and implants for computer-assisted surgery, accurate segmentation of bony structures in cone-beam computed tomography (CBCT) scans is required. However, this image segmentation step is of...
Prostheses and Implants Artifacts Tooth Cone-Beam Computed Tomography Image Processing, Computer-Assisted Metals Humans Neural Networks, Computer
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HYDRA: Hybrid deep magnetic resonance fingerprinting.

Medical physics Sep 10, 2019
PURPOSE: Magnetic resonance fingerprinting (MRF) methods typically rely on dictionary matching to map the temporal MRF signals to quantitative tissue parameters. Such approaches suffer from inherent discretization errors, as well as high computationa...
Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted
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A modality conversion approach to MV-DRs and KV-DRRs registration using information bottlenecked conditional generative adversarial network.

Medical physics Sep 6, 2019
PURPOSE: As affordable equipment, electronic portal imaging devices (EPIDs) are wildly used in radiation therapy departments to verify patients' positions for accurate radiotherapy. However, these devices tend to produce visually ambiguous and low-co...
Image Processing, Computer-Assisted Radiography Machine Learning
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Toward predicting the evolution of lung tumors during radiotherapy observed on a longitudinal MR imaging study via a deep learning algorithm.

Medical physics Sep 6, 2019
PURPOSE: To predict the spatial and temporal trajectories of lung tumor during radiotherapy monitored under a longitudinal magnetic resonance imaging (MRI) study via a deep learning algorithm for facilitating adaptive radiotherapy (ART).
Humans Retrospective Studies Magnetic Resonance Imaging Deep Learning Lung Neoplasms
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Physics-driven learning of x-ray skin dose distribution in interventional procedures.

Medical physics Sep 6, 2019
PURPOSE: Radiation doses accumulated during very complicated image-guided x-ray procedures have the potential to cause stochastic, but also deterministic effects, such as skin rashes or even hair loss. To monitor and reduce radiation-related risks to...
Neural Networks, Computer Monte Carlo Method Uncertainty Machine Learning Fluoroscopy Skin Radiation Dosage
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Technical Note: PYRO-NN: Python reconstruction operators in neural networks.

Medical physics Aug 27, 2019
PURPOSE: Recently, several attempts were conducted to transfer deep learning to medical image reconstruction. An increasingly number of publications follow the concept of embedding the computed tomography (CT) reconstruction as a known operator into ...
Neural Networks, Computer Software Tomography, X-Ray Computed Image Processing, Computer-Assisted
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The effects of physics-based data augmentation on the generalizability of deep neural networks: Demonstration on nodule false-positive reduction.

Medical physics Aug 27, 2019
PURPOSE: An important challenge for deep learning models is generalizing to new datasets that may be acquired with acquisition protocols different from the training set. It is not always feasible to expand training data to the range encountered in cl...
Deep Learning Radiation Dosage Tomography, X-Ray Computed Image Processing, Computer-Assisted Normal Distribution Humans Sensitivity and Specificity Lung Neoplasms False Positive Reactions
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Predicting gamma passing rates for portal dosimetry-based IMRT QA using machine learning.

Medical physics Aug 27, 2019
PURPOSE: Intensity-modulated radiation therapy (IMRT) quality assurance (QA) measurements are routinely performed prior to treatment delivery to verify dose calculation and delivery accuracy. In this work, we applied a machine learning-based approach...
Radiometry Gamma Rays Uncertainty Calibration Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Machine Learning Quality Control
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