AIMC Topic: Subtraction Technique

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Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System.

Computational intelligence and neuroscience Jun 9, 2016
This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. W...
Sensitivity and Specificity Robotics Video Recording Image Interpretation, Computer-Assisted Humans Artificial Intelligence Algorithms Reproducibility of Results Pattern Recognition, Automated Locomotion Subtraction Technique
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Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI.

IEEE transactions on bio-medical engineering May 12, 2016
OBJECTIVE: To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic re...
Humans Algorithms Image Enhancement Reproducibility of Results Radiation Dosage Sensitivity and Specificity Radiation Exposure Magnetic Resonance Imaging Subtraction Technique Radiation Protection Multimodal Imaging Supervised Machine Learning Positron-Emission Tomography Pattern Recognition, Automated
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Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease.

IEEE transactions on bio-medical engineering Apr 13, 2016
Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment. However, most existing sparse learning-based studies only adopt cross-s...
Magnetic Resonance Imaging Alzheimer Disease Image Interpretation, Computer-Assisted Subtraction Technique Humans Machine Learning Aging Reproducibility of Results Algorithms Cognitive Dysfunction Brain Sensitivity and Specificity Longitudinal Studies
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A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

Medical image analysis Feb 6, 2016
Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms...
Machine Learning Algorithms Computer Simulation Reproducibility of Results Sensitivity and Specificity Humans Image Enhancement Models, Cardiovascular Subtraction Technique Magnetic Resonance Imaging, Cine Heart Ventricles Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Pattern Recognition, Automated
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Fast Multiclass Dictionaries Learning With Geometrical Directions in MRI Reconstruction.

IEEE transactions on bio-medical engineering Nov 25, 2015
OBJECTIVE: Improve the reconstructed image with fast and multiclass dictionaries learning when magnetic resonance imaging is accelerated by undersampling the k-space data.
Sensitivity and Specificity Magnetic Resonance Imaging Sample Size Artifacts Phantoms, Imaging Data Compression Humans Subtraction Technique Machine Learning Algorithms Pattern Recognition, Automated Brain Image Enhancement Reproducibility of Results
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Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

Pediatric radiology Nov 6, 2015
BACKGROUND: CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT.
Child, Preschool Models, Statistical Knowledge Bases Radiation Dosage Radiation Exposure Subtraction Technique Radiation Protection Phantoms, Imaging Radiographic Image Enhancement Female Reproducibility of Results Sensitivity and Specificity Male Humans Machine Learning Computer Simulation Tomography, X-Ray Computed
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Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box.

Medical image analysis Sep 8, 2015
In this paper, we tackle the problem of automatic classification of pulmonary peri-fissural nodules (PFNs). The classification problem is formulated as a machine learning approach, where detected nodule candidates are classified as PFNs or non-PFNs. ...
Neural Networks, Computer Software Algorithms Tomography, X-Ray Computed Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule Reproducibility of Results Sensitivity and Specificity Humans Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Radiographic Image Enhancement Subtraction Technique
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Retinal vessel segmentation using multi-scale textons derived from keypoints.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 22, 2015
This paper presents a retinal vessel segmentation algorithm which uses a texton dictionary to classify vessel/non-vessel pixels. However, in contrast to previous work where filter parameters are learnt from manually labelled image pixels our filter p...
Image Interpretation, Computer-Assisted Retinal Vessels Humans Reproducibility of Results Machine Learning Retinoscopy Neural Networks, Computer Sensitivity and Specificity Pattern Recognition, Automated Algorithms Anatomic Landmarks Image Enhancement Subtraction Technique
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Exploring multifractal-based features for mild Alzheimer's disease classification.

Magnetic resonance in medicine Jul 20, 2015
PURPOSE: Multifractal applications to resting state functional MRI (rs-fMRI) time series for diagnosing Alzheimer's disease (AD) are still limited. We aim to address two issues: (I) if and what multifractal features are sufficiently discriminative to...
Image Enhancement Fractals Subtraction Technique Diagnosis, Differential Alzheimer Disease Sensitivity and Specificity Humans Image Interpretation, Computer-Assisted Brain Severity of Illness Index Male Pattern Recognition, Automated Algorithms Female Support Vector Machine Magnetic Resonance Imaging Reproducibility of Results Aged
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Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step.

Medical image analysis Jul 17, 2015
Medical ultrasound (US) image segmentation and quantification can be challenging due to signal dropouts, missing boundaries, and presence of speckle, which gives images of similar objects quite different appearance. Typically, purely intensity-based ...
Image Enhancement Subtraction Technique Humans Ultrasonography Algorithms Fuzzy Logic Reproducibility of Results Image Interpretation, Computer-Assisted Sensitivity and Specificity Pattern Recognition, Automated
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