AIMC Journal:
Medical physics

Showing 261 to 270 of 732 articles

Deep learning-based virtual noncalcium imaging in multiple myeloma using dual-energy CT.

Medical physics Aug 28, 2022
BACKGROUND: Dual-energy CT with virtual noncalcium (VNCa) images allows the evaluation of focal intramedullary bone marrow involvement in patients with multiple myeloma. However, current commercial VNCa techniques suffer from excessive image noise an...
Phantoms, Imaging Radiation Dosage Artificial Intelligence Multiple Myeloma Humans Tomography, X-Ray Computed Deep Learning
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Deep learning-based 4D-synthetic CTs from sparse-view CBCTs for dose calculations in adaptive proton therapy.

Medical physics Aug 27, 2022
BACKGROUND: Time-resolved 4D cone beam-computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton d...
Humans Protons Deep Learning Proton Therapy Heart
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C -GAN: Content-consistent generative adversarial networks for unsupervised domain adaptation in medical image segmentation.

Medical physics Aug 27, 2022
PURPOSE: In clinical practice, medical image analysis has played a key role in disease diagnosis. One of the important steps is to perform an accurate organ or tissue segmentation for assisting medical professionals in making correct diagnoses. Despi...
Image Processing, Computer-Assisted Neural Networks, Computer
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MSFR-Net: Multi-modality and single-modality feature recalibration network for brain tumor segmentation.

Medical physics Aug 23, 2022
BACKGROUND: Accurate and automated brain tumor segmentation from multi-modality MR images plays a significant role in tumor treatment. However, the existing approaches mainly focus on the fusion of multi-modality while ignoring the correlation betwee...
Image Processing, Computer-Assisted Deep Learning Magnetic Resonance Imaging Humans Brain Neoplasms
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Automatic detection of A-line in lung ultrasound images using deep learning and image processing.

Medical physics Aug 23, 2022
BACKGROUND: Auxiliary diagnosis and monitoring of lung diseases based on lung ultrasound (LUS) images is important clinical research. A-line is one of the most common indicators of LUS that can offer support for the assessment of lung diseases. A tra...
Humans Lung Diseases Image Processing, Computer-Assisted Deep Learning Ultrasonography Lung
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A reciprocal learning strategy for semisupervised medical image segmentation.

Medical physics Aug 23, 2022
BACKGROUND: Semisupervised strategy has been utilized to alleviate issues from segmentation applications due to challenges in collecting abundant annotated segmentation masks, which is an essential prerequisite for training high-performance 3D convol...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Tomography, X-Ray Computed Neural Networks, Computer Humans
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Hybrid U-Net-based deep learning model for volume segmentation of lung nodules in CT images.

Medical physics Aug 17, 2022
OBJECTIVE: Accurate segmentation of the lung nodule in computed tomography images is a critical component of a computer-assisted lung cancer detection/diagnosis system. However, lung nodule segmentation is a challenging task due to the heterogeneity ...
Deep Learning Solitary Pulmonary Nodule Humans
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Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.

Medical physics Aug 15, 2022
PURPOSE: To develop a novel multimodal data fusion model by incorporating computed tomography (CT) images and clinical variables based on deep learning for predicting the invasiveness risk of stage I lung adenocarcinoma that manifests as ground-glass...
Lung Neoplasms Adenocarcinoma Deep Learning Adenocarcinoma of Lung Neoplasm Invasiveness Retrospective Studies Humans Biomarkers, Tumor Tomography, X-Ray Computed
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Virtual high-count PET image generation using a deep learning method.

Medical physics Aug 13, 2022
PURPOSE: Recently, deep learning-based methods have been established to denoise the low-count positron emission tomography (PET) images and predict their standard-count image counterparts, which could achieve reduction of injected dosage and scan tim...
Humans Research Design Signal-To-Noise Ratio Image Processing, Computer-Assisted Deep Learning Positron-Emission Tomography
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Learning low-dose CT degradation from unpaired data with flow-based model.

Medical physics Aug 8, 2022
BACKGROUND: There has been growing interest in low-dose computed tomography (LDCT) for reducing the X-ray radiation to patients. However, LDCT always suffers from complex noise in reconstructed images. Although deep learning-based methods have shown ...
Image Processing, Computer-Assisted Abdomen Tomography, X-Ray Computed Humans Signal-To-Noise Ratio Computer Simulation Neural Networks, Computer
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