AI Medical Compendium Journal:
Journal of applied clinical medical physics

Showing 101 to 110 of 159 articles

Machine learning for contour classification in TG-263 noncompliant databases.

Journal of applied clinical medical physics Jun 10, 2022
A large volume of medical data are labeled using nonstandardized nomenclature. Although efforts have been made by the American Association of Physicists in Medicine (AAPM) to standardize nomenclature through Task Group 263 (TG-263), there remain nonc...
Head and Neck Neoplasms Algorithms Databases, Factual Humans Neural Networks, Computer Machine Learning
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Machine learning models to predict the delivered positions of Elekta multileaf collimator leaves for volumetric modulated arc therapy.

Journal of applied clinical medical physics Jun 7, 2022
PURPOSE: Accurate positioning of multileaf collimator (MLC) leaves during volumetric modulated arc therapy (VMAT) is essential for accurate treatment delivery. We developed a linear regression, support vector machine, random forest, extreme gradient ...
Humans Radiotherapy Dosage Radiotherapy, Intensity-Modulated Particle Accelerators Machine Learning Radiotherapy Planning, Computer-Assisted
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Automatic contouring QA method using a deep learning-based autocontouring system.

Journal of applied clinical medical physics May 17, 2022
PURPOSE: To determine the most accurate similarity metric when using an independent system to verify automatically generated contours.
Lymph Nodes Pelvis Female Deep Learning Radiotherapy Planning, Computer-Assisted Humans Algorithms Tomography, X-Ray Computed
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Development of an anthropomorphic multimodality pelvic phantom for quantitative evaluation of a deep-learning-based synthetic computed tomography generation technique.

Journal of applied clinical medical physics May 17, 2022
PURPOSE: The objective of this study was to fabricate an anthropomorphic multimodality pelvic phantom to evaluate a deep-learning-based synthetic computed tomography (CT) algorithm for magnetic resonance (MR)-only radiotherapy.
Tomography, X-Ray Computed Male Deep Learning Humans Phantoms, Imaging Radiotherapy Planning, Computer-Assisted Magnetic Resonance Imaging Radiotherapy Dosage Pelvis
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The auto segmentation for cardiac structures using a dual-input deep learning network based on vision saliency and transformer.

Journal of applied clinical medical physics Apr 1, 2022
PURPOSE: Accurate segmentation of cardiac structures on coronary CT angiography (CCTA) images is crucial for the morphological analysis, measurement, and functional evaluation. In this study, we achieve accurate automatic segmentation of cardiac stru...
Humans Tomography, X-Ray Computed Computed Tomography Angiography Heart Heart Ventricles Deep Learning Image Processing, Computer-Assisted
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Dosimetric assessment of patient dose calculation on a deep learning-based synthesized computed tomography image for adaptive radiotherapy.

Journal of applied clinical medical physics Mar 25, 2022
PURPOSE: Dose computation using cone beam computed tomography (CBCT) images is inaccurate for the purpose of adaptive treatment planning. The main goal of this study is to assess the dosimetric accuracy of synthetic computed tomography (CT)-based cal...
Tomography, X-Ray Computed Deep Learning Humans Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Cone-Beam Computed Tomography Image Processing, Computer-Assisted
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The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer.

Journal of applied clinical medical physics Mar 9, 2022
PURPOSE: To develop a 3D-Unet dose prediction model to predict the three-dimensional dose distribution of volumetric modulated arc therapy (VMAT) for cervical cancer and test the dose prediction performance of the model in endometrial cancer to explo...
Humans Female Uterine Cervical Neoplasms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Organs at Risk Endometrial Neoplasms Feasibility Studies Radiotherapy Planning, Computer-Assisted
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Deep learning-based auto segmentation using generative adversarial network on magnetic resonance images obtained for head and neck cancer patients.

Journal of applied clinical medical physics Mar 9, 2022
PURPOSE: Adaptive radiotherapy requires auto-segmentation in patients with head and neck (HN) cancer. In the current study, we propose an auto-segmentation model using a generative adversarial network (GAN) on magnetic resonance (MR) images of HN can...
Organs at Risk Humans Head and Neck Neoplasms Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted
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Predicting machine's performance record using the stacked long short-term memory (LSTM) neural networks.

Journal of applied clinical medical physics Feb 16, 2022
PURPOSE: The record of daily quality control (QC) items shows machine performance patterns and potentially provides warning messages for preventive actions. This study developed a neural network model that could predict the record and trend of data v...
Forecasting Humans Neural Networks, Computer
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An efficient magnetic resonance image data quality screening dashboard.

Journal of applied clinical medical physics Feb 11, 2022
PURPOSE: Complex data processing and curation for artificial intelligence applications rely on high-quality data sets for training and analysis. Manually reviewing images and their associated annotations is a very laborious task and existing quality ...
Data Accuracy Artificial Intelligence Humans Brain Neoplasms Image Processing, Computer-Assisted Magnetic Resonance Imaging
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