AIMC Journal:
Medical physics

Showing 581 to 590 of 759 articles

Grading of hepatocellular carcinoma based on diffusion weighted images with multiple b-values using convolutional neural networks.

Medical physics Jul 20, 2019
PURPOSE: To effectively grade hepatocellular carcinoma (HCC) based on deep features derived from diffusion weighted images (DWI) with multiple b-values using convolutional neural networks (CNN).
Diffusion Magnetic Resonance Imaging Middle Aged Liver Neoplasms Image Processing, Computer-Assisted Neoplasm Grading Neural Networks, Computer Humans Female Male Carcinoma, Hepatocellular
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A convolutional neural network for ultra-low-dose CT denoising and emphysema screening.

Medical physics Jul 17, 2019
PURPOSE: Reducing dose level to achieve ALARA is an important task in diagnostic and therapeutic applications of computed tomography (CT) imaging. Effective image quality enhancement strategies are crucial to compensate for the degradation caused by ...
Signal-To-Noise Ratio Lung Image Processing, Computer-Assisted Image Enhancement Radiation Dosage Pulmonary Emphysema Neural Networks, Computer Tomography, X-Ray Computed
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Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.

Medical physics Jul 12, 2019
PURPOSE: To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity-Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning.
Male Deep Learning Image Processing, Computer-Assisted Humans Radiotherapy, Intensity-Modulated Proton Therapy Radiometry Prostatic Neoplasms Radiotherapy Planning, Computer-Assisted
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Prediction of dosimetric accuracy for VMAT plans using plan complexity parameters via machine learning.

Medical physics Jul 9, 2019
PURPOSE: The dosimetric accuracies of volumetric modulated arc therapy (VMAT) plans were predicted using plan complexity parameters via machine learning.
Radiometry Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Machine Learning Regression Analysis
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Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based three-dimensional convolutional neural network.

Medical physics Jul 9, 2019
PURPOSE: To develop and evaluate a patch-based convolutional neural network (CNN) to generate synthetic computed tomography (sCT) images for magnetic resonance (MR)-only workflow for radiotherapy of head and neck tumors. A patch-based deep learning m...
Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Humans Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Head and Neck Neoplasms Magnetic Resonance Imaging Radiometry
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Fully automatic liver attenuation estimation combing CNN segmentation and morphological operations.

Medical physics Jul 5, 2019
PURPOSE: Manually tracing regions of interest (ROIs) within the liver is the de facto standard method for measuring liver attenuation on computed tomography (CT) in diagnosing nonalcoholic fatty liver disease (NAFLD). However, manual tracing is resou...
Image Processing, Computer-Assisted Humans Non-alcoholic Fatty Liver Disease Liver Tomography, X-Ray Computed Deep Learning
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Accurate colorectal tumor segmentation for CT scans based on the label assignment generative adversarial network.

Medical physics Jun 25, 2019
PURPOSE: Colorectal tumor segmentation is an important step in the analysis and diagnosis of colorectal cancer. This task is a time consuming one since it is often performed manually by radiologists. This paper presents an automatic postprocessing mo...
Aged, 80 and over Young Adult Colorectal Neoplasms Male Adult Tomography, X-Ray Computed Female Middle Aged Humans Aged Image Processing, Computer-Assisted Neural Networks, Computer
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Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach.

Medical physics Jun 23, 2019
PURPOSE: The purpose of this work was twofold: (a) To provide a robust and accurate method for image segmentation of dedicated breast CT (bCT) volume data sets, and (b) to improve Hounsfield unit (HU) accuracy in bCT by means of a postprocessing meth...
Humans Tomography, X-Ray Computed Deep Learning Artifacts Likelihood Functions Image Processing, Computer-Assisted Phantoms, Imaging Breast
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Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging.

Medical physics Jun 17, 2019
PURPOSE: To develop and evaluate a parallel imaging and convolutional neural network combined image reconstruction framework for low-latency and high-quality accelerated real-time MR imaging.
Magnetic Resonance Imaging Time Factors Heart Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss.

Medical physics Jun 17, 2019
PURPOSE: Our goal was to use a generative adversarial network (GAN) with feature matching and task-specific perceptual loss to synthesize standard-dose amyloid Positron emission tomography (PET) images of high quality and including accurate pathologi...
Radiation Dosage Signal-To-Noise Ratio Image Processing, Computer-Assisted Machine Learning Positron-Emission Tomography
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