AIMC Journal:
Medical physics

Showing 221 to 230 of 732 articles

Image-based scatter correction for cone-beam CT using flip swin transformer U-shape network.

Medical physics Feb 14, 2023
BACKGROUND: Cone beam computed tomography (CBCT) plays an increasingly important role in image-guided radiation therapy. However, the image quality of CBCT is severely degraded by excessive scatter contamination, especially in the abdominal region, h...
Algorithms Cone-Beam Computed Tomography Neural Networks, Computer Scattering, Radiation Phantoms, Imaging
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Utilization of an attentive map to preserve anatomical features for training convolutional neural-network-based low-dose CT denoiser.

Medical physics Feb 14, 2023
BACKGROUND: The purpose of a convolutional neural network (CNN)-based denoiser is to increase the diagnostic accuracy of low-dose computed tomography (LDCT) imaging. To increase diagnostic accuracy, there is a need for a method that reflects the feat...
Image Processing, Computer-Assisted Neural Networks, Computer Tomography, X-Ray Computed
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LGEANet: LSTM-global temporal convolution-external attention network for respiratory motion prediction.

Medical physics Feb 13, 2023
PURPOSE: To develop a deep learning network that treats the three-dimensional respiratory motion signals as a whole and considers the inter-dimensional correlation between signals of different directions for accurate respiratory tumor motion predicti...
Humans Motion Linear Models Neural Networks, Computer Neoplasms
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Deep compressed sensing MRI via a gradient-enhanced fusion model.

Medical physics Feb 6, 2023
BACKGROUND: Compressed sensing has been employed to accelerate magnetic resonance imaging by sampling fewer measurements. However, conventional iterative optimization-based CS-MRI are time-consuming for iterative calculations and often share poor gen...
Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Magnetic Resonance Imaging Deep Learning
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A novel mathematical model to generate semi-automated optimal IMRT treatment plan based on predicted 3D dose distribution and prescribed dose.

Medical physics Feb 2, 2023
BACKGROUND: In recent years, with the development of artificial intelligence and deep learning techniques, it has become possible to predict the three-dimensional distribution dose (3D ) of a new patient based on the treatment plans of similar recent...
Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Artificial Intelligence Models, Theoretical Organs at Risk
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Detector shifting and deep learning based ring artifact correction method for low-dose CT.

Medical physics Jan 25, 2023
BACKGROUND: In x-ray computed tomography (CT), the gain inconsistency of detector units leads to ring artifacts in the reconstructed images, seriously destroys the image structure, and is not conducive to image recognition. In addition, to reduce rad...
Deep Learning Computer Simulation Algorithms Artifacts Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Synthetic-to-real domain adaptation with deep learning for fitting the intravoxel incoherent motion model of diffusion-weighted imaging.

Medical physics Jan 14, 2023
BACKGROUND: Intravoxel incoherent motion (IVIM) is a type of diffusion-weighted imaging (DWI), and IVIM model parameters (water molecule diffusion rate D , pseudo-diffusion coefficient D , and tissue perfusion fraction F ) have been widely used in th...
Motion Diffusion Magnetic Resonance Imaging Liver Neoplasms Magnetic Resonance Imaging Deep Learning Humans
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Centralized contrastive loss with weakly supervised progressive feature extraction for fine-grained common thorax disease retrieval in chest x-ray.

Medical physics Jan 11, 2023
BACKGROUND: Medical images have already become an essential tool for the diagnosis of many diseases. Thus a large number of medical images are being generated due to the daily routine inspection. An efficient image-based disease retrieval system will...
Radiography Neural Networks, Computer Thorax Algorithms X-Rays
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Towards optimal deep fusion of imaging and clinical data via a model-based description of fusion quality.

Medical physics Jan 7, 2023
BACKGROUND: Due to intrinsic differences in data formatting, data structure, and underlying semantic information, the integration of imaging data with clinical data can be non-trivial. Optimal integration requires robust data fusion, that is, the pro...
Humans Neural Networks, Computer Tomography, X-Ray Computed Hypertension Liver Radiography, Abdominal
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Deep learning for x-ray scatter correction in dedicated breast CT.

Medical physics Jan 7, 2023
BACKGROUND: Accurate correction of x-ray scatter in dedicated breast computed tomography (bCT) imaging may result in improved visual interpretation and is crucial to achieve quantitative accuracy during image reconstruction and analysis.
Computer Simulation Humans Phantoms, Imaging Tomography, X-Ray Computed Scattering, Radiation Algorithms Deep Learning Image Processing, Computer-Assisted X-Rays Cone-Beam Computed Tomography Breast
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