AIMC Journal:
IEEE transactions on medical imaging

Showing 631 to 640 of 699 articles

Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation.

IEEE transactions on medical imaging Sep 28, 2015
Automated computer-aided detection (CADe) has been an important tool in clinical practice and research. State-of-the-art methods often show high sensitivities at the cost of high false-positives (FP) per patient rates. We design a two-tiered coarse-t...
Neural Networks, Computer Machine Learning Databases, Factual Humans Young Adult Adult Male Tomography, X-Ray Computed Female Aged Lymph Nodes Radiographic Image Interpretation, Computer-Assisted Colonic Polyps Spinal Neoplasms Middle Aged Adolescent Child
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An Automatic Learning-Based Framework for Robust Nucleus Segmentation.

IEEE transactions on medical imaging Sep 23, 2015
Computer-aided image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of diseases such as brain tumor, pancreatic neuroendocrine tumor (NET), and breast cancer. Automated nucleus...
Breast Cell Nucleus Breast Neoplasms Brain Neoplasms Image Processing, Computer-Assisted Algorithms Humans Brain Neural Networks, Computer Female
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An Inversion Scheme for Hybrid Fluorescence Molecular Tomography Using a Fuzzy Inference System.

IEEE transactions on medical imaging Sep 1, 2015
The imaging performance of fluorescence molecular tomography (FMT) improves when information from the underlying anatomy is incorporated into the inversion scheme, in the form of priors. The requirement for incorporation of priors has recently driven...
Animals Mice, Nude Molecular Imaging Phantoms, Imaging Tomography, Optical Image Processing, Computer-Assisted Mice Fuzzy Logic
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Dictionary-Driven Ischemia Detection From Cardiac Phase-Resolved Myocardial BOLD MRI at Rest.

IEEE transactions on medical imaging Aug 19, 2015
Cardiac Phase-resolved Blood-Oxygen-Level Dependent (CP-BOLD) MRI provides a unique opportunity to image an ongoing ischemia at rest. However, it requires post-processing to evaluate the extent of ischemia. To address this, here we propose an unsuper...
Oxygen Myocardial Ischemia Humans Algorithms Image Processing, Computer-Assisted Support Vector Machine Magnetic Resonance Imaging Unsupervised Machine Learning
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Fast Computation of Hemodynamic Sensitivity to Lumen Segmentation Uncertainty.

IEEE transactions on medical imaging Jun 16, 2015
Patient-specific blood flow modeling combining imaging data and computational fluid dynamics can aid in the assessment of coronary artery disease. Accurate coronary segmentation and realistic physiologic modeling of boundary conditions are important ...
Humans Machine Learning Algorithms Tomography, X-Ray Computed Coronary Angiography Hemodynamics Coronary Artery Disease Imaging, Three-Dimensional Coronary Vessels
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Compressed Sensing Reconstruction of 3D Ultrasound Data Using Dictionary Learning and Line-Wise Subsampling.

IEEE transactions on medical imaging Jun 4, 2015
In this paper we present a compressed sensing (CS) method adapted to 3D ultrasound imaging (US). In contrast to previous work, we propose a new approach based on the use of learned overcomplete dictionaries that allow for much sparser representations...
Imaging, Three-Dimensional Humans Kidney Echocardiography Sheep Machine Learning Swine Algorithms Ultrasonography Computer Simulation Databases, Factual Animals Brain
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Polyp Detection via Imbalanced Learning and Discriminative Feature Learning.

IEEE transactions on medical imaging May 18, 2015
Recent achievement of the learning-based classification leads to the noticeable performance improvement in automatic polyp detection. Here, building large good datasets is very crucial for learning a reliable detector. However, it is practically chal...
Humans Least-Squares Analysis Machine Learning Algorithms Colonic Polyps Colon Image Interpretation, Computer-Assisted Colonoscopy
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Supervised dictionary learning for inferring concurrent brain networks.

IEEE transactions on medical imaging Apr 1, 2015
Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, G...
Nerve Net Humans Machine Learning Magnetic Resonance Imaging Algorithms Linear Models Brain Connectome
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Feature-Preserving Noise Removal.

IEEE transactions on medical imaging Mar 6, 2015
Conventional image restoration algorithms use transform-domain filters, which separate the noise from the sparse signal among the transform components or apply spatial smoothing filters in real space whose design relies on prior assumptions about the...
Signal-To-Noise Ratio Phantoms, Imaging Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Neural Networks, Computer Head Algorithms
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Learning structured models for segmentation of 2-D and 3-D imagery.

IEEE transactions on medical imaging Nov 26, 2014
Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal...
Mitochondria Microscopy, Electron CA1 Region, Hippocampal Imaging, Three-Dimensional Models, Theoretical Models, Statistical Machine Learning Algorithms Animals
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