AIMC Journal:
Medical physics

Showing 351 to 360 of 732 articles

Deep learning-based motion tracking using ultrasound images.

Medical physics Nov 13, 2021
PURPOSE: Ultrasound (US) imaging is an established imaging modality capable of offering video-rate volumetric images without ionizing radiation. It has the potential for intra-fraction motion tracking in radiation therapy. In this study, a deep learn...
Humans Radiotherapy, Image-Guided Imaging, Three-Dimensional Motion Deep Learning Ultrasonography
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Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Medical physics Nov 7, 2021
PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.
Humans Retrospective Studies Mutation ErbB Receptors Adenocarcinoma of Lung Deep Learning Lung Neoplasms
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Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.

Medical physics Nov 1, 2021
PURPOSE: To investigate multiple deep learning methods for automated segmentation (auto-segmentation) of the parotid glands, submandibular glands, and level II and level III lymph nodes on magnetic resonance imaging (MRI). Outlining radiosensitive or...
Magnetic Resonance Imaging Humans Organs at Risk Image Processing, Computer-Assisted Head and Neck Neoplasms Deep Learning
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A nested parallel multiscale convolution for cerebrovascular segmentation.

Medical physics Oct 31, 2021
PURPOSE: Cerebrovascular segmentation in magnetic resonance imaging (MRI) plays an important role in the diagnosis and treatment of cerebrovascular diseases. Many segmentation frameworks based on convolutional neural networks (CNNs) or U-Net-like str...
Magnetic Resonance Angiography Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging
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A deep learning- and CT image-based prognostic model for the prediction of survival in non-small cell lung cancer.

Medical physics Oct 28, 2021
OBJECTIVE: To assist clinicians in arranging personalized treatment, planning follow-up programs and extending survival times for non-small cell lung cancer (NSCLC) patients, a method of deep learning combined with computed tomography (CT) imaging fo...
Prognosis Retrospective Studies Deep Learning Lung Neoplasms Tomography, X-Ray Computed Humans Carcinoma, Non-Small-Cell Lung
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Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks.

Medical physics Oct 26, 2021
PURPOSE: To enable real-time adaptive magnetic resonance imaging-guided radiotherapy (MRIgRT) by obtaining time-resolved three-dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (  ms). Theory and M...
Respiration Phantoms, Imaging Neural Networks, Computer Retrospective Studies Magnetic Resonance Imaging Motion Imaging, Three-Dimensional Humans
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A deep-learning-based prediction model for the biodistribution of Y microspheres in liver radioembolization.

Medical physics Oct 21, 2021
BACKGROUND: Radioembolization with Y microspheres is a treatment approach for liver cancer. Currently, employed dosimetric calculations exhibit low accuracy, lacking consideration of individual patient, and tissue characteristics.
Technetium Tc 99m Aggregated Albumin Liver Positron Emission Tomography Computed Tomography Tomography, Emission-Computed, Single-Photon Microspheres Yttrium Radioisotopes Tissue Distribution Embolization, Therapeutic Deep Learning Liver Neoplasms Humans
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Deep learning-augmented radioluminescence imaging for radiotherapy dose verification.

Medical physics Oct 5, 2021
PURPOSE: We developed a novel dose verification method using a camera-based radioluminescence imaging system (CRIS) combined with a deep learning-based signal processing technique.
Deep Learning Radiotherapy Planning, Computer-Assisted Phantoms, Imaging Radiometry Radiotherapy Dosage Radiotherapy, Intensity-Modulated
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Robustness of deep learning segmentation of cardiac substructures in noncontrast computed tomography for breast cancer radiotherapy.

Medical physics Sep 30, 2021
PURPOSE: To develop and evaluate deep learning-based autosegmentation of cardiac substructures from noncontrast planning computed tomography (CT) images in patients undergoing breast cancer radiotherapy and to investigate the algorithm sensitivity to...
Deep Learning Female Humans Heart Image Processing, Computer-Assisted Tomography, X-Ray Computed Breast Neoplasms Breast
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Deep learning-enabled EPID-based 3D dosimetry for dose verification of step-and-shoot radiotherapy.

Medical physics Sep 24, 2021
PURPOSE: The study aims at a novel dosimetry methodology to reconstruct a 3D dose distribution as imparted to a virtual cylindrical phantom using an electronic portal imaging device (EPID).
Deep Learning Phantoms, Imaging Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiometry Humans Radiotherapy, Intensity-Modulated Algorithms
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