AIMC Journal:
Medical physics

Showing 371 to 380 of 732 articles

Deep learning-based reconstruction of interventional tools and devices from four X-ray projections for tomographic interventional guidance.

Medical physics Aug 30, 2021
PURPOSE: Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a monoplanar or a biplanar C-arm system. However, the projective data provide only limited information about the spatial structur...
Image Processing, Computer-Assisted Fluoroscopy Deep Learning Cone-Beam Computed Tomography Phantoms, Imaging X-Rays Humans Tomography, X-Ray Computed
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Automatic breast lesion detection in ultrafast DCE-MRI using deep learning.

Medical physics Aug 30, 2021
PURPOSE: We propose a deep learning-based computer-aided detection (CADe) method to detect breast lesions in ultrafast DCE-MRI sequences. This method uses both the 3D spatial information and temporal information obtained from the early-phase of the d...
Deep Learning Contrast Media Magnetic Resonance Imaging Breast Female Breast Neoplasms Motion Humans
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SCU-Net: A deep learning method for segmentation and quantification of breast arterial calcifications on mammograms.

Medical physics Aug 28, 2021
PURPOSE: Measurements of breast arterial calcifications (BAC) can offer a personalized, non-invasive approach to risk-stratify women for cardiovascular diseases such as heart attack and stroke. We aim to detect and segment breast arterial calcificati...
Breast Diseases Female Deep Learning Retrospective Studies Mammography Image Processing, Computer-Assisted Humans Tomography, X-Ray Computed Breast
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Low-dose CT denoising via convolutional neural network with an observer loss function.

Medical physics Aug 25, 2021
PURPOSE: Convolutional neural network (CNN)-based denoising is an effective method for reducing complex computed tomography (CT) noise. However, the image blur induced by denoising processes is a major concern. The main source of image blur is the pi...
Signal-To-Noise Ratio Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted
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A deep learning-based dual-omics prediction model for radiation pneumonitis.

Medical physics Aug 25, 2021
PURPOSE: Radiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This study proposed a deep learning-based dual-omics model, which aims to improve the RP prediction performance by integrating more data points and exploring...
Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Radiation Pneumonitis Four-Dimensional Computed Tomography
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MRI pulse sequence integration for deep-learning-based brain metastases segmentation.

Medical physics Aug 18, 2021
PURPOSE: Magnetic resonance (MR) imaging is an essential diagnostic tool in clinical medicine. Recently, a variety of deep-learning methods have been applied to segmentation tasks in medical images, with promising results for computer-aided diagnosis...
Image Processing, Computer-Assisted Brain Neoplasms Humans Magnetic Resonance Imaging Deep Learning Neural Networks, Computer
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Deep learning-based forward and cross-scatter correction in dual-source CT.

Medical physics Aug 13, 2021
PURPOSE: Dual-source computed tomography (DSCT) uses two source-detector pairs offset by about 90°. In addition to the well-known forward scatter, a special issue in DSCT is cross-scattered radiation from X-ray tube A detected in the detector of syst...
Phantoms, Imaging Cone-Beam Computed Tomography Image Processing, Computer-Assisted Artifacts Scattering, Radiation Tomography, X-Ray Computed Deep Learning Algorithms
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Managing tumor changes during radiotherapy using a deep learning model.

Medical physics Aug 11, 2021
PURPOSE: We propose a treatment planning framework that accounts for weekly lung tumor shrinkage using cone beam computed tomography (CBCT) images with a deep learning-based model.
Deep Learning Radiotherapy Planning, Computer-Assisted Cone-Beam Computed Tomography Humans Radiotherapy Dosage Male Lung Neoplasms Radiotherapy, Intensity-Modulated Carcinoma, Non-Small-Cell Lung
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Attention-based deep learning system for automated diagnoses of age-related macular degeneration in optical coherence tomography images.

Medical physics Aug 9, 2021
PURPOSE: The progression of age-related macular degeneration (AMD) is critical to treatment decisions in clinical practice. The disease can be classified into four categories namely, drusen, inactive choroidal neovascularization (CNV), active CNV, an...
Area Under Curve Humans Tomography, Optical Coherence Deep Learning Retina Macular Degeneration
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Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation.

Medical physics Aug 4, 2021
PURPOSE: We propose a deep learning method that classifies focal liver lesions (FLLs) into cysts, hemangiomas, and metastases from portal phase abdominal CT images. We propose a synthetic data augmentation process to alleviate the class imbalance and...
Neural Networks, Computer Tomography, X-Ray Computed Humans Liver Neoplasms
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