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Sung Min Kim  - - - 
Top co-authors
Sung Yun Park

29 shared publications

Department of Medical Bio Technology, Dongguk University-Seoul Seoul, Republic of Korea

SangJoon Lee

4 shared publications

Dongguk University-Seoul

Eun Byeol Jo

3 shared publications

Department of Medical Bio Technology, Dongguk University, Seoul, Korea

107
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Publication Record
Distribution of Articles published per year 
(2002 - 2019)
Total number of journals
published in
 
33
 
Publications See all
Article 0 Reads 0 Citations Solid-state fermentation of black rice bran with Aspergillus awamori and Aspergillus oryzae: Effects on phenolic acid co... Hye-Young Shin, Sung-Min Kim, Ju Hun Lee, Seung-Taik Lim Published: 01 January 2019
Food Chemistry, doi: 10.1016/j.foodchem.2018.07.174
DOI See at publisher website
Article 0 Reads 0 Citations Numerical Study of Thermal Performance of Phase Change Material-based Heat Sinks with Three-dimensional Transient Coolin... Ju-Ho Jeong, Jin Hyun Lee, Sung-Min Kim Published: 07 November 2018
Sensors and Materials, doi: 10.18494/sam.2018.1974
DOI See at publisher website
Article 0 Reads 0 Citations Association of Blood Pressure Classification in Korean Young Adults According to the 2017 American College of Cardiology... Joung Sik Son, Seulggie Choi, Kyuwoong Kim, Sung Min Kim, Da... Published: 06 November 2018
JAMA, doi: 10.1001/jama.2018.16501
DOI See at publisher website
Article 0 Reads 0 Citations Association of Blood Pressure Classification in Korean Young Adults According to the 2017 American College of Cardiology... Joung Sik Son, Seulggie Choi, Kyuwoong Kim, Sung Min Kim, Da... Published: 06 November 2018
JAMA,
PubMed View at PubMed
Article 0 Reads 0 Citations A novel intensity-based multi-level classification approach for coronary plaque characterization in intravascular ultras... Ga Young Kim, Ju Hwan Lee, Yoo Na Hwang, Sung Min Kim Published: 01 November 2018
BioMedical Engineering OnLine, doi: 10.1186/s12938-018-0586-1
DOI See at publisher website ABS Show/hide abstract
Intravascular ultrasound (IVUS) is a commonly used diagnostic imaging method for coronary artery disease. Virtual histology (VH) characterizes the plaque components into fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), or dense calcium (DC). However, VH can obtain only a single-frame image in one cardiac cycle, and specific software is needed to obtain the radio frequency data. This study proposed a novel intensity-based multi-level classification model for plaque characterization. The plaque-containing regions between the intima and the media-adventitia were segmented manually for all IVUS frames. A total of 54 features including first order statistics, grey level co-occurrence matrix, Law’s energy measures, extended grey level run length matrix, intensity, and local binary pattern were estimated from the plaque-containing regions. After feature extraction, optimal features were selected using principle component analysis (PCA), and these were utilized as the input for the classification models. Plaque components were classified into FT, FFT, NC, or DC using an intensity-based multi-level classification model consisting of three different nets. Net 1 differentiated low-intensity components into FT/FFT and NC/DC groups. Then, net 2 subsequently divided FT/FFT into FT or FFT, whereas the remainder and high-intensity components were classified into NC or DC via net 3. To improve classification accuracy, each net utilized three different input features obtained by PCA. Classification performance was evaluated in terms of sensitivity, specificity, accuracy, and receiver operating characteristic curve. Quantitative results indicated that the proposed method showed significantly high classification accuracy for all tissue types. The classifiers had classification accuracies of 85.1%, 71.9%, and 77.2%, respectively, and the areas under the curve were 0.845, 0.704, and 0.783. In particular, the proposed method achieved relatively high sensitivity (82.0%) and specificity (87.1%) for differentiating between the FT/FFT and NC/DC groups. These results confirmed the clinical applicability of the proposed approach for IVUS-based tissue characterization.
Article 0 Reads 0 Citations Automatic Detection of Dense Calcium and Acoustic Shadow in Intravascular Ultrasound Images by Dual-threshold-based Segm... Ju Hwan Lee, Ga Young Kim, Yoo Na Hwang, Sung Min Kim Published: 31 August 2018
Sensors and Materials, doi: 10.18494/sam.2018.1905
DOI See at publisher website
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