AIMC Journal:
Medical physics

Showing 671 to 680 of 759 articles

Fast segmentation of kidney components using random forests and ferns.

Medical physics Nov 7, 2017
PURPOSE: This paper studies the feasibility of developing a fast and accurate automatic kidney component segmentation method. The proposed method segments the kidney into four components: renal cortex, renal column, renal medulla, and renal pelvis.
Humans Time Factors Image Processing, Computer-Assisted Kidney Machine Learning Tomography, X-Ray Computed
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Neural network dose models for knowledge-based planning in pancreatic SBRT.

Medical physics Nov 1, 2017
PURPOSE: Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop knowledge-b...
Radiosurgery Humans Normal Distribution Pancreatic Neoplasms Radiation Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Neural Networks, Computer
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Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.

Medical physics Oct 28, 2017
PURPOSE: Delineation of the clinical target volume (CTV) and organs at risk (OARs) is very important for radiotherapy but is time-consuming and prone to inter-observer variation. Here, we proposed a novel deep dilated convolutional neural network (DD...
Radiotherapy Planning, Computer-Assisted Humans Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Automation Rectal Neoplasms Time Factors Machine Learning Organs at Risk
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Automatic labeling of MR brain images through extensible learning and atlas forests.

Medical physics Oct 24, 2017
PURPOSE: Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about n...
Machine Learning Brain Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Automation
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A parallel MR imaging method using multilayer perceptron.

Medical physics Oct 23, 2017
PURPOSE: To reconstruct MR images from subsampled data, we propose a fast reconstruction method using the multilayer perceptron (MLP) algorithm.
Magnetic Resonance Imaging Male Image Processing, Computer-Assisted Young Adult Adult Neural Networks, Computer Female Humans
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Esophagus segmentation in CT via 3D fully convolutional neural network and random walk.

Medical physics Oct 23, 2017
PURPOSE: Precise delineation of organs at risk is a crucial task in radiotherapy treatment planning for delivering high doses to the tumor while sparing healthy tissues. In recent years, automated segmentation methods have shown an increasingly high ...
Esophagus Neural Networks, Computer Tomography, X-Ray Computed Imaging, Three-Dimensional Machine Learning
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Learning-based deformable registration for infant MRI by integrating random forest with auto-context model.

Medical physics Oct 19, 2017
PURPOSE: Accurately analyzing the rapid structural evolution of human brain in the first year of life is a key step in early brain development studies, which requires accurate deformable image registration. However, due to (a) dynamic appearance and ...
Humans Machine Learning Infant, Newborn Hippocampus Models, Theoretical Magnetic Resonance Imaging Regression Analysis Infant Image Processing, Computer-Assisted
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A combined learning algorithm for prostate segmentation on 3D CT images.

Medical physics Sep 22, 2017
PURPOSE: Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentati...
Humans Imaging, Three-Dimensional Machine Learning Tomography, X-Ray Computed Prostate Male Reference Standards
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Urinary bladder cancer staging in CT urography using machine learning.

Medical physics Sep 5, 2017
PURPOSE: To evaluate the feasibility of using an objective computer-aided system to assess bladder cancer stage in CT Urography (CTU).
Neoplasm Staging Urography Tomography, X-Ray Computed Image Processing, Computer-Assisted Urinary Bladder Neoplasms Humans Machine Learning
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Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.

Medical physics Aug 31, 2017
PURPOSE: As part of a program to implement automatic lesion detection methods for whole body magnetic resonance imaging (MRI) in oncology, we have developed, evaluated, and compared three algorithms for fully automatic, multiorgan segmentation in hea...
Whole Body Imaging Young Adult Magnetic Resonance Imaging Female Adult Humans Middle Aged Automation Aged Male Neural Networks, Computer Image Processing, Computer-Assisted
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