Abstract
Detection of myocardial borders on sequences of electron beam CT images is carried out using an adaptive segmentation algorithm developed to enhance dynamic analysis of cardiac function. Adaptivity is based on description of the myocardial borders from the mean and standard deviation of the grey level and gradient distributions on each image of the sequence. Comparison of segmentations from five experimentators with automatically determined borders on a set of 416 endocardial and epicardial contours indicated differences between automatic and manual tracing very close to differences due to inter-observer reproducibility.
Publication types
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Comparative Study
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms*
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Cardiac Output, Low / diagnostic imaging
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Cardiac Output, Low / physiopathology
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Cardiomyopathy, Dilated / diagnostic imaging
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Cardiomyopathy, Dilated / physiopathology
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Cardiomyopathy, Hypertrophic / diagnostic imaging
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Cardiomyopathy, Hypertrophic / physiopathology
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Contrast Media / administration & dosage
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Endocardium / diagnostic imaging
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Heart Ventricles / diagnostic imaging*
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Humans
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Image Processing, Computer-Assisted / methods*
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Observer Variation
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Pericardium / diagnostic imaging
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Radiographic Image Enhancement
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Reproducibility of Results
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Tomography, X-Ray Computed*
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Ventricular Dysfunction, Left / diagnostic imaging
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Ventricular Dysfunction, Left / physiopathology
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Ventricular Function / physiology