• Journal of Oral Medicine and Pain
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• v.38 no.1
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• pp.35-51
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• 2013

The aims of this study was to observed an effect of antioxidative in cardiac muscle of high fat diet induced obesity rat by treadmill exercise with intensity and time. Thirty-two Sprauge-Dawley rats which were divided into four group. Normal, Control(high fat diet induced obesity rat), Experimental I(high intensity intermittent exercise in high fat diet induced obesity rat), Experimental II(moderate intensity endurance exercise in high fat diet induced obesity rat). The results of this study were as follows: 1. In change of body weight, the outcome of each group significantly difference compared with control. Also, 1 to 3 weeks significantly different compared with pre valu experimental I and II(p<0.001). 2. In change of lipid profile, the outcome of each group significantly difference compared with control(p<0.001). Difference between experimental I and II is not significantly. 3. In change of antioxidative enzymes(SOD, CAT, GPx) in myocardium, there are significant difference between control and experimental II, and also between control and experimental I(p<0.001). 4. In change of antioxidative protein MCR-1, the outcome of each group significantly difference compared with control(p<0.01). Experimental II was most significantly difference than the other group(p<0.001). The above results suggest that treadmill exercise effectively reduced in fat. It would be considered that moderate intensity endurance exercise has an effects on improved antioxidative enzyme in cardiac muscle of high fat diet induced obesity rat.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.507-516
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• 2008

Cardiac disease is the leading cause of death in the world. Quantification of cardiac function is performed by manually calculating blood volume and ejection fraction in routine clinical practice, but it requires high computational costs. In this study, an automatic left ventricle (LV) segmentation algorithm using short-axis cine cardiac MRI is presented. We compensate coil sensitivity of magnitude images depending on coil location, classify edge information after extracting edges, and segment LV by applying region-growing segmentation. We design a weighting function for intensity signal and calculate a blood volume of LV considering partial voxel effects. Using cardiac cine SSFP of 38 subjects with Cornell University IRB approval, we compared our algorithm to manual contour tracing and MASS software. Without partial volume effects, we achieved segmentation accuracy of $3.3mL{\pm}5.8$ (standard deviation) and $3.2mL{\pm}4.3$ in diastolic and systolic phases, respectively. With partial volume effects, the accuracy was $19.1mL{\pm}8.8$ and $10.3mL{\pm}6.1$ in diastolic and systolic phases, respectively. Also in ejection fraction, the accuracy was $-1.3%{\pm}2.6$ and $-2.1%{\pm}2.4$ without and with partial volume effects, respectively. Results support that the proposed algorithm is exact and useful for clinical practice.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.101-107
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• 2002

This paper presents a segmentation algorithm to extract endocardial contour and epicardial contour of left ventricle in MR Cardiac images. The algorithm is based on a generalized gradient vector flow(GGVF) snake and a prediction of initial contour(PIC). Especially. the proposed algorithm uses physical characteristics of endocardial and epicardial contours, cross profile correlation matching(CPCM), and a mixed interpolation model. In the experiment, the proposed method is applied to short axis MR cardiac image set, which are obtained by Siemens, Medinus, and GE MRI Systems. The experimental results show that the proposed algorithm can extract acceptable epicardial and endocardial walls. We calculate quantitative parameters from the segmented results, which are displayed graphically. The segmented left vents role is visualized volumetrically by surface rendering. The proposed algorithm is implemented on Windows environment using Visual C ++.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.873-876
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• 2001

관상 동맥 질환은 관상 동맥 내벽에 플라크(Plaque)가 침착된 결과 혈관이 좁아져서 생기는 질환으로, 혈관이 좁아져 심장으로의 혈류가 감소하고, 혈전이 동맥을 막아 심장 발작을 일으킨다. 본 논문에서는 관상동맥 질환의 객관적 분석을 위한 분할 방법론과 분할된 영역으로부터 정량적 분석 방법을 제안한다. 동맥 단면영상으로부터 정량 분석을 위해 획득한 단면영상을 현미경으로부터 12.5배 배율로 얻었으며, 정량 분석을 위해 혈관의 각 영역을 분할하여 분할영역의 크기, 최대 장축 등의 정보를 추출하였다. 본 논문에서 제시한 알고리즘을 사용하여 수 작업에 의한 혈관 단면 분석을 자동화하면, 3차원적 변화량에 따른 정량분석 결과를 얻을 수 있을 것이다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.32-43
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• 2009

In this paper, we improve the performance of cardiac disorder classification by continuous heart sound signals using automatic segmentation and extreme learning machine (ELM). The accuracy of the conventional cardiac disorder classification systems degrades because murmurs and click sounds contained in the abnormal heart sound signals cause incorrect or missing starting points of the first (S1) and the second heart pulses (S2) in the automatic segmentation stage, In order to reduce the performance degradation due to segmentation errors, we find the positions of the S1 and S2 pulses, modify them using the time difference of S1 or S2, and extract a single period of heart sound signals. We then obtain a feature vector consisting of the mel-scaled filter bank energy coefficients and the envelope of uniform-sized sub-segments from the single-period heart sound signals. To classify the heart disorders, we use ELM with a single hidden layer. In cardiac disorder classification experiments with 9 cardiac disorder categories, the proposed method shows the classification accuracy of 81.6% and achieves the highest classification accuracy among ELM, multi-layer perceptron (MLP), support vector machine (SVM), and hidden Markov model (HMM).

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.57-66
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• 2011

To prevent cardiac diseases, quantifying cardiac function is important in routine clinical practice by analyzing blood volume and ejection fraction. These works have been manually performed and hence it requires computational costs and varies depending on the operator. In this paper, an automatic left ventricle segmentation algorithm is presented to segment left ventricle on cardiac magnetic resonance images. After coil sensitivity of MRI images is compensated, a K-mean clustering scheme is applied to segment blood area. A graph searching scheme is employed to correct the segmentation error from coil distortions and noises. Using cardiac MRI images from 38 subjects, the presented algorithm is performed to calculate blood volume and ejection fraction and compared with those of manual contouring by experts and GE MASS software. Based on the results, the presented algorithm achieves the average accuracy of 6.2mL${\pm}$5.6, 2.9mL${\pm}$3.0 and 2.1%${\pm}$1.5 in diastolic phase, systolic phase and ejection fraction, respectively. Moreover, the presented algorithm minimizes user intervention rates which was critical to automatize algorithms in previous researches.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.592-601
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• 2019

For coronary procedures, X-ray angiogram images are useful for diagnosing and assisting procedures. It is challenging to accurately segment a coronary artery using only a single segmentation model in 2D X-ray images due to a complex structure of three-dimensional coronary artery, especially from phenomenon of vessels being broken in the middle or end of coronary artery. In order to solve these problems, the initial segmentation is performed using an existing single model, and the candidate regions for the sophisticate correction is estimated based on the initial segment, and the local patch-based correction is performed in the candidate regions. Through this research, not only the broken coronary arteries are re-connected, but also the distal part of coronary artery that is very thin is additionally correctly found. Further, the performance can be much improved by combining the proposed correction method with any existing coronary artery segmentation method. In this paper, the U-net, a fully convolutional network was chosen as a segmentation method and the proposed correction method was combined with U-net to demonstrate a significant improvement in performance through X-ray images from several patients.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.149-157
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• 2011

In this paper, we propose a new cardiac disorder classification method using an support vector machine (SVM) to combine hidden Markov model (HMM) and murmur existence information. Using cepstral features and the HMM Viterbi algorithm, we segment input heart sound signals into HMM states for each cardiac disorder model and compute log-likelihood (score) for every state in the model. To exploit the temporal position characteristics of murmur signals, we divide the input signals into two subbands and compute murmur probability of every subband of each frame, and obtain the murmur score for each state by using the state segmentation information obtained from the Viterbi algorithm. With an input vector containing the HMM state scores and the murmur scores for all cardiac disorder models, SVM finally decides the cardiac disorder category. In cardiac disorder classification experimental results, the proposed method shows the relatively improvement rate of 20.4 % compared to the HMM-based classifier with the conventional cepstral features.

• Journal of Chest Surgery
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• v.29 no.8
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• pp.807-815
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• 1996

The protective effect of'ischemic preconditioning'on ischemid-reperfusion injury of heart has been reported in various animal species. but without known mechAnism in detail, In An attempt to investigate the cardioprotective mechanism of ischemic preconditioning, we examined the effects of nitric oxide(UO) synthesis in preconditioned heart of rat The isolated hearts perfused by Langendorfr's method were ex- posed to 30min global ischemia followed by 30min reperfusion with oxygenated Krebs-Henseleit(K-H) sol- ution. Ischemic preconditioning was performed with three episodes of Sm n ischemia and Smin repeyfusion before the induction of prolong ischemia(30min)-reperfusion(30min). Ischemic preconditioning prevented the depression of cardiac function(left ventricular pressure .K heart rate) observed in the ischemia- reperfusion hearts and reduced the release of lactate dehydrogenase during the reperfusion period. On electromicroscopic pictures, myocardial ultrastructures wore relatively well preserved in isthemic preconditioned hearts. N6_nitro-L-arginine methyl ester(L-NAME) an inhibitor of L-arginine citric oxide pathway, was infused at a rate O.Smllmin In a dose of 10mg kg-1 before the initial ischemic preconditioning. neither the protection of cardiac function nor the reduction of LDH releAse in ischemic preconditioning hearts was altered in the presence of added L-NAME On ultrastructural finding, the preservation of morphology in ischemic preconditioning heart was not change by the pretreatment of L-UAME. The failure of the WO synthesis inhibitor to reduce t e effect of ischemic preconditioning may be related to be species specific in that NO may allot be the trigger for ischemic preconditioning in rats.

• The Korean Journal of Pharmacology
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• v.32 no.1
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• pp.31-37
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• 1996

The protective effect of 'ischemic preconditioning (IP)'on ischemia-reperfusion injury of heart has been reported in various animal species, but the mechanism is unclear. In an attempt to elucidate the mechanism of IP, we examined the effects of blockers against adenosine and protein kinase C in preconditioned heart of rat. The hearts perfused with oxygen-saturated Krebs-Henseleit solution by Langendorff method were exposed to 30 min global ischemia followed by 20 min reperfusion. IP was performed with three episodes of 5 min ischcmia and 5 min reperfusion just before ischemia-reperfusion. IP prevented the depression of contractile function and the myocardial contracture in the ischemic-reperfused heart and reduced the release of lactate dehydrogenase during the reperfusion period. Polymyxin B, chelerythrine and colchicine, PKC inhibitors, attenuated almost completely the anti-ischemic effect of IP, while adenosine receptor antagonists did not. These results indicate that PKC may be a crucial intracellular mediator in anti-ischemic action of IP in ischemic-reperfused rat heart, while adenosine may not be involved in the mechanism of IP.