AIMC Journal:
Medical physics

Showing 281 to 290 of 732 articles

Predicting the outcome of radiotherapy in brain metastasis by integrating the clinical and MRI-based deep learning features.

Medical physics Jul 6, 2022
BACKGROUND: A considerable proportion of metastatic brain tumors progress locally despite stereotactic radiation treatment, and it can take months before such local progression is evident on follow-up imaging. Prediction of radiotherapy outcome in te...
Deep Learning Magnetic Resonance Imaging Humans Brain Neoplasms
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Real time volumetric MRI for 3D motion tracking via geometry-informed deep learning.

Medical physics Jul 6, 2022
PURPOSE: To develop a geometry-informed deep learning framework for volumetric MRI with sub-second acquisition time in support of 3D motion tracking, which is highly desirable for improved radiotherapy precision but hindered by the long image acquisi...
Motion Radiotherapy, Image-Guided Imaging, Three-Dimensional Magnetic Resonance Imaging Humans Deep Learning
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Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.

Medical physics Jun 24, 2022
BACKGROUND: Recently, computed tomography (CT) manufacturers have developed deep-learning-based reconstruction algorithms to compensate for the limitations of iterative reconstruction (IR) algorithms, such as image smoothing and the spatial resolutio...
Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Phantoms, Imaging Humans Drug Tapering Algorithms Tomography, X-Ray Computed Artificial Intelligence
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Bayesian statistics-guided label refurbishment mechanism: Mitigating label noise in medical image classification.

Medical physics Jun 22, 2022
PURPOSE: Deep neural networks (DNNs) have been widely applied in medical image classification, benefiting from its powerful mapping capability among medical images. However, these existing deep learning-based methods depend on an enormous amount of c...
Signal-To-Noise Ratio Neural Networks, Computer Animals Bayes Theorem
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CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.

Medical physics Jun 21, 2022
BACKGROUND: The morbidity of pulmonary embolism (PE) is only lower than that of coronary heart disease and hypertension. Early detection, early diagnosis, and timely treatment are the keys to effectively reduce the risk of death. Nevertheless, PE seg...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Pulmonary Embolism Tomography, X-Ray Computed Lung
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Size-adaptive mediastinal multilesion detection in chest CT images via deep learning and a benchmark dataset.

Medical physics Jun 20, 2022
PURPOSE: Many deep learning methods have been developed for pulmonary lesion detection in chest computed tomography (CT) images. However, these methods generally target one particular lesion type, that is, pulmonary nodules. In this work, we intend t...
Deep Learning Tomography Research Design Tomography, X-Ray Computed Humans
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Simultaneously optimizing sampling pattern for joint acceleration of multi-contrast MRI using model-based deep learning.

Medical physics Jun 20, 2022
BACKGROUND: Acceleration of MR imaging (MRI) is a popular research area, and usage of deep learning for acceleration has become highly widespread in the MR community. Joint acceleration of multiple-acquisition MRI was proven to be effective over a si...
Acceleration Magnetic Resonance Imaging Knee Joint Image Processing, Computer-Assisted Brain Deep Learning
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A metric learning-based method using graph neural network for pancreatic cystic neoplasm classification from CTs.

Medical physics Jun 1, 2022
PURPOSE: Pancreatic cystic neoplasms (PCNs) are relatively rare neoplasms and difficult to be classified preoperatively. Ordinary deep learning methods have great potential to provide support for doctors in PCNs classification but require a quantity ...
Neoplasms Diagnosis, Computer-Assisted Algorithms Tomography, X-Ray Computed Neural Networks, Computer
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Efficient fetal ultrasound image segmentation for automatic head circumference measurement using a lightweight deep convolutional neural network.

Medical physics May 24, 2022
PURPOSE: Fetal head circumference (HC) is an important biometric parameter that can be used to assess fetal development in obstetric clinical practice. Most of the existing methods use deep neural network to accomplish the task of automatic fetal HC ...
Female Image Processing, Computer-Assisted Head Neural Networks, Computer Humans Pregnancy
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Deep learning-based 3D MRI contrast-enhanced synthesis from a 2D noncontrast T2Flair sequence.

Medical physics May 20, 2022
PURPOSE: Gadolinium-based contrast agents (GBCAs) have been successfully applied in magnetic resonance (MR) imaging to facilitate better lesion visualization. However, gadolinium deposition in the human brain raised widespread concerns recently. On t...
Imaging, Three-Dimensional Gadolinium Humans Image Processing, Computer-Assisted Contrast Media Deep Learning Magnetic Resonance Imaging
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