AIMC Topic: Image Enhancement

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Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging.

Journal of biomedical optics Dec 1, 2015
Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately represen...
Sensitivity and Specificity Animals Swine Skin Algorithms Dermoscopy Reproducibility of Results Pattern Recognition, Automated Image Enhancement Optical Imaging Subtraction Technique Burns Image Interpretation, Computer-Assisted Artifacts Spectrum Analysis Machine Learning
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Cramér-Rao lower bound calculations for image registration using simulated phenomenology.

Journal of the Optical Society of America. A, Optics, image science, and vision Aug 1, 2015
The Cramér-Rao lower bound (CRLB) is a valuable tool to quantify fundamental limits to estimation problems associated with imaging systems, and has been used previously to study image registration performance bounds. Most existing work, however, assu...
Reproducibility of Results Machine Learning Pattern Recognition, Automated Sensitivity and Specificity Algorithms Image Enhancement Imaging, Three-Dimensional Subtraction Technique Image Interpretation, Computer-Assisted
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Fetal thymus volume estimation by virtual organ computer-aided analysis in normal pregnancies.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine May 1, 2015
OBJECTIVES: The thymus has a pyramidal shape, which is best shown in coronal planes. The aim of this study was to evaluate the potential of virtual organ computer-aided analysis to estimate fetal thymus volume in normal pregnancies.
Humans Machine Learning Sensitivity and Specificity Male Ultrasonography, Prenatal User-Computer Interface Algorithms Pregnancy Female Reproducibility of Results Image Enhancement Imaging, Three-Dimensional Organ Size Thymus Gland Image Interpretation, Computer-Assisted
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Machine learning in medical imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 1, 2015
Pattern Recognition, Automated Image Enhancement Reproducibility of Results Sensitivity and Specificity Image Interpretation, Computer-Assisted Machine Learning Algorithms
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Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

Bio-medical materials and engineering Jan 1, 2015
This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangio...
Pattern Recognition, Automated Algorithms Image Enhancement Adult Humans Middle Aged Sensitivity and Specificity Female Neural Networks, Computer Reproducibility of Results Male Ultrasonography Machine Learning Aged Liver Neoplasms Image Interpretation, Computer-Assisted
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Automatic segmentation in image stacks based on multi-constraint level-set evolution.

Bio-medical materials and engineering Jan 1, 2015
Contour extraction of image stacks is a basic task in medical modeling. The existing level-set methods usually suffer from some problems (e.g. serious errors around sharp features, incorrect split of topology and contour occlusions). This paper propo...
Algorithms Reproducibility of Results Sensitivity and Specificity Image Interpretation, Computer-Assisted Machine Learning Pattern Recognition, Automated Image Enhancement Subtraction Technique
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Image manifold revealing for breast lesion segmentation in DCE-MRI.

Bio-medical materials and engineering Jan 1, 2015
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used for breast lesion differentiation. Manual segmentation in DCE-MRI is difficult and open to viewer interpretation. In this paper, an automatic segmentation method based on i...
Image Interpretation, Computer-Assisted Pattern Recognition, Automated Image Enhancement Machine Learning Sensitivity and Specificity Algorithms Breast Neoplasms Female Magnetic Resonance Imaging Humans Reproducibility of Results
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Automatic brain MR image denoising based on texture feature-based artificial neural networks.

Bio-medical materials and engineering Jan 1, 2015
Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, no...
Neural Networks, Computer Brain Reproducibility of Results Sensitivity and Specificity Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Artifacts Pattern Recognition, Automated Humans Image Enhancement Signal-To-Noise Ratio
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Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration.

Information processing in medical imaging : proceedings of the ... conference Jan 1, 2015
This paper presents a dictionary learning-based method to segment the brain surface in post-surgical CT images of epilepsy patients following surgical implantation of electrodes. Using the electrodes identified in the post-implantation CT, surgeons r...
Image Enhancement Tomography, X-Ray Computed Reproducibility of Results Sensitivity and Specificity Magnetic Resonance Imaging Multimodal Imaging Epilepsy Humans Image Interpretation, Computer-Assisted Artificial Intelligence Pattern Recognition, Automated Algorithms Brain
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Finding a Path for Segmentation Through Sequential Learning.

Information processing in medical imaging : proceedings of the ... conference Jan 1, 2015
Sequential learning techniques, such as auto-context, that applies the output of an intermediate classifier as contextual features for its subsequent classifier has shown impressive performance for semantic segmentation. We show that these methods ca...
Muscle, Skeletal Dogs Image Interpretation, Computer-Assisted Pattern Recognition, Automated Image Enhancement Reproducibility of Results Sensitivity and Specificity Animals Magnetic Resonance Imaging Artificial Intelligence Algorithms
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