• 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.

• Annual Conference of KIPS
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• 2019.05a
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• pp.508-510
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• 2019

본 연구에서는 딥 러닝을 이용하여 완전 자동화된 다중 클래스 전체 심장 분할 알고리즘을 제안하였다. 제안된 방법은 recurrent convolutional block과 residual multi-dilated block을 삽입하여 기존 U-Net을 개선한 인공신경망 모델을 사용하였다. 평가는 자동화 분석 결과와 수동 평가를 비교하였다. 그 결과 96.88%의 평균 DSC, 95.60%의 정확도, 97.00%의 recall을 얻었다. 이 실험 결과는 제안된 방법이 다양한 심장 구조에서 효과적으로 구분되어 수행되었음을 알 수 있다. 본 연구에서 제안된 알고리즘이 의사와 방사선 의사가 영상을 판독하거나 임상 결정을 내리는데 보조적 역할을 할 것을 기대한다.

• 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.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.145-148
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• 2002

본 논문에서는 관상동맥 질환의 객관적 분석을 위해, 혈관단면영상에서의 ROI(Lumen, Media, Plaque)에 대한 정확한 분할과 분할한 영역에서 질병을 유발시키는 요소들에 대한 정량적 분석을 위한 소프트웨어를 개발하였다. 본 시스템은 Visual C++ 6.0을 이용하여 개발하였으며, 현미경으로부터 획득한 관상동맥 단면영상에 적용하여 Lumen, Media와 Plaque를 분할하고, 각 영역의 형태학적 특징을 추출하여 분석 결과를 파일로 저장할 수 있도록 구현하였다. 분석된 결과는 심장질환의 객관적 진단을 위한 보조판단근거로써 사용될 것으로 기대한다.

• 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 the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.597-605
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• 1999

In this paper, we propose a cardioangiography sequence image coding scheme which use a subtraction between initial image and current frame inserted contrast dye. Stable regions are obtained by the multithreshold and meaningful region is extracted by the images with stable region. The image with meaningful region is classified into contour and texture information. Contour information is coded by contour coding. And texture information is approximated by two-dimensional polynomial function and each coefficients is coded. Experimental results confirm that the sequence of cardioangiography are well reconstructed at the low bit rate (0.02∼0.04 bpp) and high compression ratio.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

• 대한핵의학회:학술대회논문집
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• 1990.04a
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• pp.197-197
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• 1990

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.215-222
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• 2006

People health improvement is becoming new subject through the combining with the oriental medicine diagnosis theory and IT technology. To do this, firstly, it needs sicked data that supply the visualization, objectification and quantification method. Especially, if an ocular inspection can be more objective and visual expression in oriental medicine, it seems to offer the biggest opportunity in diagnosis field. In this study, I propose a diagnosis to check the symptoms of heart diagnosis. Our research aim is on the visualization of diagnosis using image processing system which it can be actual analysis about the symptom of heart. To catch up this study, through the color support assistance by face image processing, I devide the face area and analyze the face form and also extract face characteristic point in heart disease diagnosis using oriental medicine based on an ocular inspection method. I would like to prove the usefulness of the method that proposed by an experiment.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.291-292
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• 2008