Jeong Ki Pack

Effects of 837 and 1950 MHz radiofrequency radiation exposure alone or combined on oxidative stress in MCF10A cells

The aim of this study was to determine whether the exposure to either single or multiple radio-frequency (RF) radiation frequencies could induce oxidative stress in cell cultures. Exposures of human MCF10A mammary epithelial cells to either a single frequency (837 MHz alone or 1950 MHz alone) or multiple frequencies (837 and 1950 MHz) were conducted at specific absorption rate (SAR) values of 4 W/kg for 2 h. During the exposure period, the temperature in the exposure chamber was maintained isothermally. Intracellular levels of reactive oxygen species (ROS), the antioxidant enzyme activity of superoxide dismutase (SOD), and the ratio of reduced/oxidized glutathione (GSH/GSSG) showed no statistically significant alterations as the result of either single or multiple RF radiation exposures. In contrast, ionizing radiation-exposed cells, used as a positive control, showed evident changes in all measured biological endpoints. These results indicate that single or multiple RF radiation exposure did not elicit oxidative stress in MCF10A cells under our exposure conditions.

A review of breast tissue classification in mammograms

For women in the U.S. breast cancer is the most commonly diagnosed cancer besides skin cancer and has become one of the major health issues in recent decades. Early detection through screening is one of key factors to reduce the death rates. The strong correlation between abnormality of breast tissues presented in mammograms and breast cancer shows that radiologists could benefit from Computer-Aided Diagnosis (CAD) systems with abilities of automated breast tissueclassification. This paper reviews recent advances in classification technologies of breast tissues. The major contribution of this paper is that we extensivelydiscuss recent breast tissue classification technologie sand compare three different types of approaches. According to our survey, we found that machine learning approaches could be chosen as anappropriate classification technology for a CAD system, considering efficiency and compatibility.

Acute radio frequency irradiation does not affect cell cycle, cellular migration, and invasion†

Although in vitro studies have been previously conducted to determine the biological effects of radio frequency (RF) radiation, it has not yet been determined whether or not RF radiation poses a potential hazard. This study was conducted to determine whether RF radiation exposure exerts detectable effects on cell cycle distribution, cellular invasion, and migration. NIH3T3 mouse fibroblasts were exposed to 849 MHz of RF radiation at average SAR values of 2 or 10 W/kg for either 1 h, or for 1 h per day for 3 days. During the exposure period, the temperature in the exposure chamber was maintained isothermally by circulating water throughout the cavity. Cell cycle distribution was analyzed at 24 and 48 h after exposure, by flow cytometry. We detected no statistically significant differences between the sham-exposed and RF radiation-exposed cells. Cellular invasion and migration were assessed by in vitro Matrigel invasion and Transwell migration assays. The RF radiation-exposed groups evidenced no significant changes in motility and invasiveness compared to the sham-exposed group. However, the ionizing radiation-exposed cells, used as a positive control group, manifested dramatic alterations in their cell cycle distribution, cellular invasiveness, and migration characteristics. Our results show that 849 MHz RF radiation exposure exerts no detectable effects on cell cycle distribution, cellular migration, or invasion at average SAR values of 2 or 10 W/kg.

A new histogram-based breast cancer image classifier using Gaussian mixture model

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 contribution of our proposed approach is to innovatively design the breast tumor image classifier using histogram-based GMM. This paper also represents extensive experimental results using this new method. The results show that this new histogram-GMM-based method is effective and accurate to classify breast tumor images into different classes.

Similar MRI object retrieval based on modified contour to centroid triangulation with arc difference rate

In this paper, we propose a new image retrieval method based on Sectored Contour to Centroid Triangulation (SCTCT) using distinctive shape feature, named Arc Difference Rate (ADR). We utilized Support Vector Machine (SVM) method as an extraction tool to extract suspicious tumor area as binary object image from the breast MRI. Therefore extracted 100 binary object images are used as test cases in the experimental study. The results from proposed method show the improvement in finding correct matches compare to the traditional SCTCT.

Magnetic resonance image retrieval based on contour to centroid triangulation with shape feature similarity

In this paper, we present an image retrieval method based on contour to centroid triangulation with shape feature similarity. We assume test images and database images used in this paper are all single objects that are segmented by known algorithms such as SVM and K-means algorithms. From these classified binary images, we propose novel Shape based image retrieval method integrating sectored characteristic points to the Contour to Centroid Triangulation (CTCT) method using Unique Representation Grid (URG) as shape feature that can perform as the filtering process. The experimental result shows proposed method has improved conventional CTCT in retrieving medical object image compared to conventional CTCT method with 79 percent match rate while CTCT showed 33 percent match.

Shape based medical image retrieval method using irregularity chain code similarity

In this paper, we present a shape based image retrieval method based on chain code representing irregularity of an object. A distinctive chain code is introduced as a main extracted feature of the object. All objects used in this paper are binary object images extracted by well-known classification algorithm, Support Vector Machine (SVM). From these classified binary images, we propose a modified shape based image retrieval method with the unique chain code interpreting irregularity of object. Proposed method is experimented along with known shape based image retrieval method using characteristic point features. The experimental result shows that proposed method exceed matching rate that of conventional contour to centroid triangulation (CTCT) method showing proposed method has higher matching rate.

Analysis of MIMO Channel Characteristics Considering the Building Density in the Urban Area at the 700 MHz Frequency Band

Urban area is a representative environment of wireless channels in the mobile communication, building density has a different distribution depending on the location. Building density has affect to propagation prediction For this reason, building density is expected to affect to the channel characteristics, we need to analyze it. We measured channel characteristics in urban areas of Jeju island by channel sounder and 4×4 antenna. Channel characteristics considering the building density were derived based on the measured data in the urban area. In this paper, the measurement data is analyzed and channel characteristics are derived through MIMO Channel measurements at 700 MHz considering the building density in the urban area.