Sung Y. Shin

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In most file systems, if a file is deleted, only the metadata of the file is deleted or modified and the file's data is still stored on the physical media. Some users require that deleted files no longer be accessible. This requirement is more important in embedded systems that employ flash memory as a storage medium. In this paper, we have designed a NAND(More)
The segmentation of breast Magnetic Resonance Imaging (MRI) has been a long term challenge due to the fuzzy boundaries among objects, small spots, and irregular object shapes in breast MRI. Even though intensity-based clustering algorithms such as K-means clustering and Fuzzy C-means clustering have been used widely for basic image segmentation, they(More)
Early stage breast cancer detection is a critical challenge to improve survive rate, and thus it is extremely important to perform breast tumor image classification. In this paper, we propose a new method based on Gaussian Mixture Model (GMM) to classify one input breast tumor image into two different classes (benign class and malignant class). The main(More)
JAEHEUNG LEE, SANGHO YI, JUNYOUNG HEO, HYUNGBAE PARK, SUNG Y. SHIN AND YOOKUN CHO School of Computer Science and Engineering Seoul National University Seoul, 151-172 Korea E-mail: {jhlee; shyi; ykcho} Department of Computer Science and Electrical Engineering University of Missouri at Kansas City Kansas City, MO 64110, U.S.A. E-mail:(More)
The breast mammogram image is one of the most important materials of the Computer-Aided Diagnosis (CAD) system to support diagnosis of breast cancer. In the CAD system, intensity value is a widely used feature for medical image processing. In this paper, we propose develop improved Harris Corner Detection with improved input training data set for Support(More)
Morphologic appearance plays a substantial role in presenting mass lesion in breast imaging. In this paper, we propose an innovative shape irregularity measurement based on roughness index - Enhance Roughness Index (ERI). This new irregularity measurement is taken as an input to Gaussian Mixture Model (GMM) classifier. By analyzing the similarity through(More)
Mobile Microwave Tomography (MMT) is a new alternative technique to detect breast cancer using smart phone based electronic healthcare system. In this paper, we propose a new solution to extract tumor information from MMT raw data for early breast cancer screening. MMT reflects water contents of breast tissue by measuring their electrical properties and(More)
Wireless cyber-mammography is potentially a convenient screening method to be comfortable and effective in community and rural area early detection of breast cancer, but their interpretation is difficult due to the noise and low quality of images. In this paper, we study the accuracy of a Cyber-aided diagnosis system to help physicians to classify the(More)
Computer Aided Diagnosis (CAD) system has been proven that it can be utilized as the secondary option for physicians for early breast cancer detection. A typical CAD system consists of several phases like image segmentation, feature extraction and selection, classification. Among those phases, the classification phase is one of the important phases that(More)
During the last several years, dynamic voltage scaling (DVS) algorithms are being used for energy consumption on real, fully functional battery supplied devices, adjusting the clock speed and supply voltage dynamically. Most DVS algorithms are investigated in interval-based and task-based strategies. Task-based algorithms consider task information,(More)