AIMC Journal:
Medical physics

Showing 441 to 450 of 732 articles

Thyroid nodules risk stratification through deep learning based on ultrasound images.

Medical physics Nov 14, 2020
PURPOSE: Clinically, the risk stratification of thyroid nodules is usually used to formulate the next treatment plan. The American College of Radiology (ACR) thyroid imaging reporting and data system (TI-RADS) is a type of medical standard widely use...
Humans Retrospective Studies Ultrasonography Thyroid Nodule Risk Assessment Deep Learning
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Evaluation of multislice inputs to convolutional neural networks for medical image segmentation.

Medical physics Nov 10, 2020
PURPOSE: When using convolutional neural networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with inputs and outputs either as single slice [two-dimensional (2D)] or whole volumes [three-dime...
Neural Networks, Computer Imaging, Three-Dimensional Image Processing, Computer-Assisted
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Generating anthropomorphic phantoms using fully unsupervised deformable image registration with convolutional neural networks.

Medical physics Nov 9, 2020
PURPOSE: Computerized phantoms have been widely used in nuclear medicine imaging for imaging system optimization and validation. Although the existing computerized phantoms can model anatomical variations through organ and phantom scaling, they do no...
Phantoms, Imaging Humans Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Artificial intelligence-based radiotherapy machine parameter optimization using reinforcement learning.

Medical physics Nov 5, 2020
PURPOSE: To develop and evaluate a volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) approach based on deep-Q reinforcement learning (RL) capable of finding an optimal machine control policy using previous prostate cancer p...
Artificial Intelligence Radiotherapy Dosage Retrospective Studies Radiotherapy, Intensity-Modulated Male Humans Radiotherapy Planning, Computer-Assisted
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Deep-learning-based direct inversion for material decomposition.

Medical physics Oct 30, 2020
PURPOSE: To develop a convolutional neural network (CNN) that can directly estimate material density distribution from multi-energy computed tomography (CT) images without performing conventional material decomposition.
Phantoms, Imaging Animals Deep Learning Swine Algorithms Neural Networks, Computer Image Processing, Computer-Assisted Tomography, X-Ray Computed
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Deep learning-based digitization of prostate brachytherapy needles in ultrasound images.

Medical physics Oct 27, 2020
PURPOSE: To develop, and evaluate the performance of, a deep learning-based three-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) algorithm aimed at finding needles in ultrasound images used in prostate brachytherapy.
Humans Ultrasonography Brachytherapy Artificial Intelligence Male Imaging, Three-Dimensional Prostatic Neoplasms Deep Learning Needles
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Using deep learning to model the biological dose prediction on bulky lung cancer patients of partial stereotactic ablation radiotherapy.

Medical physics Oct 26, 2020
PURPOSE: To develop a biological dose prediction model considering tissue bio-reactions in addition to patient anatomy for achieving a more comprehensive evaluation of tumor control and promoting the automatic planning of bulky lung cancer.
Deep Learning Radiosurgery Radiotherapy Dosage Lung Neoplasms Radiotherapy, Intensity-Modulated Humans Organs at Risk Radiotherapy Planning, Computer-Assisted
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Targeted transfer learning to improve performance in small medical physics datasets.

Medical physics Oct 25, 2020
PURPOSE: To perform an in-depth evaluation of current state of the art techniques in training neural networks to identify appropriate approaches in small datasets.
Physics Deep Learning X-Rays Humans Neural Networks, Computer
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Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.

Medical physics Oct 24, 2020
PURPOSE: Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmen...
Prostatic Neoplasms Diffusion Magnetic Resonance Imaging Deep Learning Humans Magnetic Resonance Imaging Male
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Breast ultrasound lesion classification based on image decomposition and transfer learning.

Medical physics Oct 20, 2020
PURPOSE: In medical image analysis, deep learning has great application potential. Discovering a method for extracting valuable information from medical images and integrating that information closely with medical treatment has recently become a majo...
Ultrasonography Ultrasonography, Mammary Machine Learning Female Neural Networks, Computer
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