AIMC Journal:
Medical physics

Showing 461 to 470 of 732 articles

Deep learning segmentation of general interventional tools in two-dimensional ultrasound images.

Medical physics Aug 30, 2020
PURPOSE: Many interventional procedures require the precise placement of needles or therapy applicators (tools) to correctly achieve planned targets for optimal diagnosis or treatment of cancer, typically leveraging the temporal resolution of ultraso...
Needles Phantoms, Imaging Female Male Ultrasonography Liver Deep Learning
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Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT.

Medical physics Aug 27, 2020
PURPOSE: Deep learning-based whole-heart segmentation in coronary computed tomography angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction. Automatic extraction of these measures in patients und...
Humans Heart Tomography, X-Ray Computed Neural Networks, Computer Computed Tomography Angiography Deep Learning
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Spatial-channel relation learning for brain tumor segmentation.

Medical physics Aug 26, 2020
PURPOSE: Recently, research on brain tumor segmentation has made great progress. However, ambiguous patterns in magnetic resonance imaging data and linear fusion omitting semantic gaps between features in different branches remain challenging. We nee...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Brain Neoplasms
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Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.

Medical physics Aug 11, 2020
PURPOSE: Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (D...
Head and Neck Neoplasms Radiation Oncology Deep Learning Cone-Beam Computed Tomography Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Calibration Humans Phantoms, Imaging Spiral Cone-Beam Computed Tomography
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Technical Note: Deep Learning approach for automatic detection and identification of patient positioning devices for radiation therapy.

Medical physics Aug 8, 2020
PURPOSE: Automatic detection and identification of setup devices, using a deep convolutional neural network (CNN) for real-time multiclass object detection, has the potential to reduce errors in the treatment delivery process by avoiding documentatio...
Deep Learning Humans Automation Patient Positioning Neural Networks, Computer
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Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

Medical physics Aug 2, 2020
PURPOSE: Many researchers have developed deep learning models for predicting clinical dose distributions and Pareto optimal dose distributions. Models for predicting Pareto optimal dose distributions have generated optimal plans in real time using an...
Radiotherapy, Intensity-Modulated Deep Learning Humans Organs at Risk Radiotherapy Planning, Computer-Assisted Male Radiotherapy Dosage
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ADR-Net: Context extraction network based on M-Net for medical image segmentation.

Medical physics Aug 2, 2020
PURPOSE: Medical image segmentation is an essential component of medical image analysis. Accurate segmentation can assist doctors in diagnosis and relieve their fatigue. Although several image segmentation methods based on U-Net have been proposed, t...
Lung Image Processing, Computer-Assisted Neural Networks, Computer
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Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods.

Medical physics Jul 28, 2020
Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck (H&N), which requires a precise spatial description of the target volumes and organs at risk (OARs) to deliver a highly conformal radiation dose to the tumor c...
Radiotherapy Planning, Computer-Assisted Head Humans Head and Neck Neoplasms Deep Learning Organs at Risk
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A deep learning framework for prostate localization in cone beam CT-guided radiotherapy.

Medical physics Jul 27, 2020
PURPOSE: To develop a deep learning-based model for prostate planning target volume (PTV) localization on cone beam computed tomography (CBCT) to improve the workflow of CBCT-guided patient setup.
Prostatic Neoplasms Radiotherapy Planning, Computer-Assisted Deep Learning Humans Prostate Cone-Beam Computed Tomography Radiotherapy, Image-Guided Male
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Cone-beam CT-derived relative stopping power map generation via deep learning for proton radiotherapy.

Medical physics Jul 27, 2020
PURPOSE: In intensity-modulated proton therapy (IMPT), protons are used to deliver highly conformal dose distributions, targeting tumors, and sparing organs-at-risk. However, due to uncertainties in both patient setup and relative stopping power (RSP...
Cone-Beam Computed Tomography Radiotherapy, Intensity-Modulated Humans Image Processing, Computer-Assisted Protons Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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