AIMC Journal:
Medical physics

Showing 511 to 520 of 740 articles

Multimodality image registration in the head-and-neck using a deep learning-derived synthetic CT as a bridge.

Medical physics Jan 2, 2020
PURPOSE: To develop and demonstrate the efficacy of a novel head-and-neck multimodality image registration technique using deep-learning-based cross-modality synthesis.
Humans Multimodal Imaging Image Processing, Computer-Assisted Head and Neck Neoplasms Tomography, X-Ray Computed Magnetic Resonance Imaging Deep Learning
View on PubMed DOI

Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.

Medical physics Jan 1, 2020
PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissue...
Abdomen Models, Theoretical Liver Image Processing, Computer-Assisted Kidney Thorax Dose-Response Relationship, Radiation Radiography, Dual-Energy Scanned Projection Signal-To-Noise Ratio Spleen Humans Lung Deep Learning Tomography, X-Ray Computed
View on PubMed DOI

Breast tumor classification through learning from noisy labeled ultrasound images.

Medical physics Dec 30, 2019
PURPOSE: To train deep learning models to differentiate benign and malignant breast tumors in ultrasound images, we need to collect many training samples with clear labels. In general, biopsy results can be used as benign/malignant labels. However, m...
Signal-To-Noise Ratio Humans Machine Learning Image Processing, Computer-Assisted Ultrasonography, Mammary Breast Neoplasms
View on PubMed DOI

Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose-volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy.

Medical physics Dec 29, 2019
PURPOSE: We propose a novel domain-specific loss, which is a differentiable loss function based on the dose-volume histogram (DVH), and combine it with an adversarial loss for the training of deep neural networks. In this study, we trained a neural n...
Male Deep Learning Prostatic Neoplasms Humans Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiation Dosage
View on PubMed DOI

Cardiac substructure segmentation with deep learning for improved cardiac sparing.

Medical physics Dec 29, 2019
PURPOSE: Radiation dose to cardiac substructures is related to radiation-induced heart disease. However, substructures are not considered in radiation therapy planning (RTP) due to poor visualization on CT. Therefore, we developed a novel deep learni...
Humans Deep Learning Feasibility Studies Radiation Dosage Phantoms, Imaging Image Processing, Computer-Assisted Heart
View on PubMed DOI

Synthesizing images from multiple kernels using a deep convolutional neural network.

Medical physics Dec 29, 2019
PURPOSE: Filtering measured projections with a particular convolutional kernel is an essential step in analytic reconstruction of computed tomography (CT) images. A tradeoff between noise and spatial resolution exists for different choices of reconst...
Tomography, X-Ray Computed Radiation Dosage Signal-To-Noise Ratio Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation.

Medical physics Dec 25, 2019
PURPOSE: Various dose calculation algorithms are available for radiation therapy for cancer patients. However, these algorithms are faced with the tradeoff between efficiency and accuracy. The fast algorithms are generally less accurate, while the ac...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Phantoms, Imaging Prostate Feasibility Studies Radiotherapy Planning, Computer-Assisted Deep Learning Models, Theoretical Humans Male
View on PubMed DOI

CT prostate segmentation based on synthetic MRI-aided deep attention fully convolution network.

Medical physics Dec 3, 2019
PURPOSE: Accurate segmentation of the prostate on computed tomography (CT) for treatment planning is challenging due to CT's poor soft tissue contrast. Magnetic resonance imaging (MRI) has been used to aid prostate delineation, but its final accuracy...
Magnetic Resonance Imaging Prostate Humans Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Male
View on PubMed DOI

Deep learning-based virtual noncontrast CT for volumetric modulated arc therapy planning: Comparison with a dual-energy CT-based approach.

Medical physics Dec 3, 2019
PURPOSE: The aim of this study was to develop a deep learning (DL) method for generating virtual noncontrast (VNC) computed tomography (CT) images from contrast-enhanced (CE) CT images (VNC ) and to evaluate its performance in dose calculations for h...
Radiographic Image Enhancement Radiography, Dual-Energy Scanned Projection Head Radiotherapy, Intensity-Modulated Deep Learning Iodine Neck Contrast Media Time Factors Humans Tomography, X-Ray Computed Reproducibility of Results
View on PubMed DOI

Knowledge-based automated planning with three-dimensional generative adversarial networks.

Medical physics Nov 29, 2019
PURPOSE: To develop a knowledge-based automated planning pipeline that generates treatment plans without feature engineering, using deep neural network architectures for predicting three-dimensional (3D) dose.
Radiotherapy Planning, Computer-Assisted Automation Radiotherapy Dosage Tomography, X-Ray Computed Knowledge Bases
View on PubMed DOI
Popular Topics
Popular Journals