AIMC Journal:
Medical physics

Showing 601 to 610 of 759 articles

Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

Medical physics Apr 29, 2019
PURPOSE: Accurate segmentation of rectal tumors is a basic and crucial task for diagnosis and treatment of rectal cancer. To avoid tedious manual delineation, an automatic rectal tumor segmentation model is proposed.
Humans Neural Networks, Computer Magnetic Resonance Imaging Rectal Neoplasms Reproducibility of Results Image Processing, Computer-Assisted
View on PubMed DOI

Attention-aware fully convolutional neural network with convolutional long short-term memory network for ultrasound-based motion tracking.

Medical physics Apr 22, 2019
PURPOSE: One of the promising options for motion management in radiation therapy (RT) is the use of LINAC-compatible robotic-arm-mounted ultrasound imaging system due to its high soft tissue contrast, real-time capability, absence of ionizing radiati...
Movement Radiotherapy, Image-Guided Neural Networks, Computer Ultrasonography Image Processing, Computer-Assisted
View on PubMed DOI

Temporal stability assessment in shear wave elasticity images validated by deep learning neural network for chronic liver disease fibrosis stage assessment.

Medical physics Apr 15, 2019
PURPOSE: To automatically detect and isolate areas of low and high stiffness temporal stability in shear wave elastography (SWE) image sequences and define their impact in chronic liver disease (CLD) diagnosis improvement by means of clinical examina...
Fibrosis Elasticity Imaging Techniques Liver Chronic Disease Humans Time Factors Image Processing, Computer-Assisted Liver Cirrhosis Reproducibility of Results Case-Control Studies Deep Learning
View on PubMed DOI

A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.

Medical physics Apr 15, 2019
PURPOSE: Real-time image-guided adaptive radiation therapy (IGART) requires accurate marker segmentation to resolve three-dimensional (3D) motion based on two-dimensional (2D) fluoroscopic images. Most common marker segmentation methods require prior...
Male Deep Learning Prostatic Neoplasms Fluoroscopy Automation Dose Fractionation, Radiation Humans Radiotherapy, Image-Guided Fiducial Markers
View on PubMed DOI

Dense networks with relative location awareness for thorax disease identification.

Medical physics Apr 14, 2019
PURPOSE: Chest X-ray is one of the most common examinations for diagnosing heart and lung diseases. Due to the existing of a large number of clinical cases, many automated diagnosis algorithms based on chest X-ray images have been proposed. To our kn...
Databases, Factual Radiography, Thoracic Diagnosis, Computer-Assisted Thoracic Diseases Humans Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Lung Diseases Algorithms Pattern Recognition, Automated
View on PubMed DOI

Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.

Medical physics Apr 8, 2019
PURPOSE: There has been burgeoning interest in applying machine learning methods for predicting radiotherapy outcomes. However, the imbalanced ratio of a large number of variables to a limited sample size in radiation oncology constitutes a major cha...
Treatment Outcome Carcinoma, Non-Small-Cell Lung Humans Machine Learning Lung Neoplasms Computational Biology
View on PubMed DOI

A convolutional neural network algorithm for automatic segmentation of head and neck organs at risk using deep lifelong learning.

Medical physics Apr 4, 2019
PURPOSE: This study suggests a lifelong learning-based convolutional neural network (LL-CNN) algorithm as a superior alternative to single-task learning approaches for automatic segmentation of head and neck (OARs) organs at risk.
Risk Radiotherapy, Image-Guided Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Squamous Cell Carcinoma of Head and Neck Organs at Risk Automation Humans
View on PubMed DOI

A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.

Medical physics Apr 1, 2019
PURPOSE: This work aims to develop a new framework of image quality assessment using deep learning-based model observer (DL-MO) and to validate it in a low-contrast lesion detection task that involves CT images with patient anatomical background.
Humans Neural Networks, Computer Algorithms Liver Neoplasms Image Processing, Computer-Assisted Models, Statistical Retrospective Studies Tomography, X-Ray Computed Deep Learning Observer Variation Least-Squares Analysis Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted
View on PubMed DOI

Image domain dual material decomposition for dual-energy CT using butterfly network.

Medical physics Apr 1, 2019
PURPOSE: Dual-energy CT (DECT) has been increasingly used in imaging applications because of its capability for material differentiation. However, material decomposition suffers from magnified noise from two CT images of independent scans, leading to...
Humans Neural Networks, Computer Algorithms Head Tomography, X-Ray Computed Bone and Bones Phantoms, Imaging Image Processing, Computer-Assisted Abdomen
View on PubMed DOI

A deep learning method for prediction of three-dimensional dose distribution of helical tomotherapy.

Medical physics Mar 30, 2019
PURPOSE: To develop a deep learning method for prediction of three-dimensional (3D) voxel-by-voxel dose distributions of helical tomotherapy (HT).
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Deep Learning Humans Image Processing, Computer-Assisted Tomography, X-Ray Computed Organs at Risk
View on PubMed DOI
Popular Topics
Popular Journals