Joon Beom Seo

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The motivation is to introduce new shape features and optimize the classifier to improve performance of differentiating obstructive lung diseases, based on high-resolution computerized tomography (HRCT) images. Two hundred sixty-five HRCT images from 82 subjects were selected. On each image, two experienced radiologists selected regions of interest (ROIs)(More)
Automatic liver segmentation is difficult because of the wide range of human variations in the shapes of the liver. In addition, nearby organs and tissues have similar intensity distributions to the liver, making the liver's boundaries ambiguous. In this study, we propose a fast and accurate liver segmentation method from contrast-enhanced computed(More)
OBJECTIVE This study was designed to develop an automated system for quantification of various regional disease patterns of diffuse lung diseases as depicted on high-resolution computed tomography (HRCT) and to compare the performance of the automated system with human readers. MATERIALS AND METHODS A total of 600 circular regions-of-interest (ROIs), 10(More)
Novel influenza A (H1N1) virus is the pathogen of recent global outbreaks of febrile respiratory infection. We herein report the imaging findings of pulmonary complication in two patients with novel influenza A (H1N1) infection. The first patient without secondary infection showed the ill-defined ground-glass opacity nodules and patch areas of ground-glass(More)
PURPOSE Airway remodeling may be responsible for irreversible airway obstruction in asthma, and a low post-bronchodilator FEV1/FVC ratio can be used as a noninvasive marker of airway remodeling. We investigated correlations between airway wall indices on computed tomography (CT) and various clinical indices, including post-bronchodilator FEV1/FVC ratio, in(More)
Machine classifiers have been used to automate quantitative analysis and avoid intra-inter-reader variability in previous studies. The selection of an appropriate classification scheme is important for improving performance based on the characteristics of the data set. This paper investigated the performance of several machine classifiers for(More)
To improve time and accuracy in differentiating diffuse interstitial lung disease for computer-aided quantification, we introduce a hierarchical support vector machine which selects a class by training a binary classifier at each node in a hierarchy, thus allowing each classifier to use a class-specific quasi-optimal feature set. In addition, the(More)
We propose the use of a context-sensitive support vector machine (csSVM) to enhance the performance of a conventional support vector machine (SVM) for identifying diffuse interstitial lung disease (DILD) in high-resolution computerized tomography (HRCT) images. Nine hundred rectangular regions of interest (ROIs), each 20 × 20 pixels in size and consisting(More)
OBJECTIVE To compare observer performance using liquid-crystal display (LCD) and cathode-ray tube (CRT) monitors in the interpretation of soft-copy chest radiographs for the detection of small solitary pulmonary nodules. MATERIALS AND METHODS By reviewing our Medical Center's radiologic information system, the eight radiologists participating in this(More)
The purpose of this study is to demonstrate whether the signal intensity (SI) of myocardial infarction (MI) on contrast enhanced (CE)-cine MRI is useful for differentiating recently infarcted myocardium from chronic scar. This study included 24 patients with acute MI (36-84 years, mean age: 57) and 19 patients with chronic MI (44-80 years, mean age: 64).(More)