• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1341-1347
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• 2007

The displacement field (Optical flow) has been calculated by bottom-up approaches based on local processing. In contrast with them, in this paper, a top-down approach based on expanding in turn from the lowest order mode the whole motion in an image pair of sequential images is proposed. The intensity of medical images usually represents a quantity which is conserved during the motion. Hence sequential images are ideally related by a coordinate transformation. The displacement field can be determined from the generalized moments of the two images. The equations which transform arbitrary generalized moments from a source image to a target image are expressed as a function of the displacement field. The appareent displacement field is then computed iteratively by a projection method which utilizes the functional derivatives of the linearized moment equations. This method is demonstrated using a pair of sequential heart images. For comparative evaluation, we applied Horn and Schunck's method, a standard multigrid method, and our proposed algorithm to sequential image.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.2
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• pp.37-44
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• 2020

In this paper, we proposed that a fully automatic multi-class whole heart segmentation algorithm using deep learning. The proposed method is based on U-Net architecture which consist of recurrent convolutional block, residual multi-dilated convolutional block. The evaluation was accomplished by comparing automated analysis results of the test dataset to the manual assessment. We obtained the average DSC of 96.88%, precision of 95.60%, and recall of 97.00% with CT images. We were able to observe and analyze after visualizing segmented images using three-dimensional volume rendering method. Our experiment results show that proposed method effectively performed to segment in various heart structures. We expected that our method can help doctors and radiologist to make image reading and clinical decision.

• Progress in Medical Physics
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• v.13 no.4
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• pp.224-228
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• 2002

Myocardial tagging technique such as spatial modulation of magnetization (SPAMM) allows the study of myocardial motion with high accuracy. However, the accuracy of the estimation of tag intersection can be affected by tagline spacing. The aim of this study was to investigate the relationship between tagline spacing of SPAMM image and tagging contrast-to-noise ratio (CNR) in in-vivo study. Two healthy volunteers were undergone electrocardiographically triggered MR imaging with SPAMM-based tagging pulse sequence at a 1.5T MR scanner. Horizontally modulated stripe patterns were imposed with a range from 3.6 to 9.6 mm of tagline spacing. Images of the left ventricle(LV) wall were acquired at the mid-ventricle level during cardiac cycle with FE-EPI (TR/TE = 5.8/2.2 msec, FA= 10$^{\circ}$. Tagging CNR for each image was calculated with a software which developed in our group. During contraction, tagging CNR was more rapidly decreased in case of narrow tagline spacing than in case of wide tagline spacing. In the same heart phase, CNR was increased corresponding with tagline spacing. Especially, at the fully contracted heart phase, CNR was more rapidly increased than the other heart phases as a function of tagline spacing. The results indicated that the optimization of tagline spacing provides better tagging CNR in order to analyze the myocardial motion more accurately.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.297-303
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• 2014

Purpose : The purpose of this study is reproducibility evaluation of deep inspiration breath-hold(DIBH) technique by respiration data and heart position analysis in radiation therapy for Left Breast cancer patients. Materials and Methods : Free breathing(FB) Computed Tomography(CT) images and DIBH CT images of three left breast cancer patients were used to evaluate the heart volume and dose during treatment planing system( Eclipse version 10.0, Varian, USA ). The signal of RPM (Real-time Position Management) Respiratory Gating System (version 1.7.5, Varian, USA) was used to evaluate respiration stability of DIBH during breast radiation therapy. The images for measurement of heart position were acquired by the Electronic portal imaging device(EPID) cine acquisition mode. The distance of heart at the three measuring points(A, B, C) on each image was measured by Offline Review (ARIA 10, Varian, USA). Results : Significant differences were found between the FB and DIBH plans for mean heart dose (6.82 vs. 1.91 Gy), heart $V_{30}$ (68.57 vs. $8.26cm^3$), $V_{20}$ (76.43 vs. $11.34cm^3$). The standard deviation of DIBH signal of each patient was ${\pm}0.07cm$, ${\pm}0.04cm$, ${\pm}0.13cm$, respectively. The Maximum and Minimum heart distance on EPID images were measured as 0.32 cm and 0.00 cm. Conclusion : Consequently, using the DIBH technique with radiation therapy for left breast cancer patients is very useful to establish the treatment plan and to reduce the heart dose. In addition, it is beneficial to using the Cine acquisition mode of EPID for the reproducibility evaluation of DIBH.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.149-156
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• 2016

Measurement of cardiac blood flow using the magnetic resonance imaging has been limited due to breathing and involuntary movements of the heart. The present study attempted to improve the accuracy of cardiac blood flow testing through phase contrast magnetic resonance imaging by presenting the adequate breathing method and imaging variables by comparing the measurement values of cardiac blood flow. Each was evaluated by comparing the breath hold retrospective 1NEX and non breath hold retrospective 1-3NEX in the ascending aorta and descending aorta. As a result, the average blood flow amount/velocity of the breath hold retrosepctive 1NEX method in the ascending aorta were $96.17{\pm}19.12ml/sec$, $17.04{\pm}4.12cm/sec$ respectively, which demonstrates a statistically significant difference(p<0.05) with the non-breath hold retrospective method 1NEX of $72.31{\pm}13.27ml$ and $12.32{\pm}3.85$. On the other hand, the average 2NEX blood flow and mean flow velocity is $101.90{\pm}24.09$, $16.84{\pm}4.32$, 3NEX $103.06{\pm}25.49$, $16.88{\pm}4.19$ did not show statistically significant differences(p>0.05).The average blood flow amount/ velocity of the breath hold retrospective 1NEX method in the descending aorta were $76.68{\pm}19.72ml/s$, and $22.23{\pm}4.8$, which did not demonstrate a significant difference in comparison to non-breath hold retrospective method 1-3 NEX. Therefore, the non breath hold retrospective method does not significantly differ in terms of cardiac blood flow in comparison with the breath hold retrospective method in accordance with the increase of NEX, so pediatric patients or patients who are not able to breathe well must have the diagnostic value of their cardiac blood flow tests improved.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.283-289
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• 2012

Web-based physiological signal monitoring system can provide appropriate healthcare services to transmit bio-signal processing, analysis of bulk in medical centers. Therefore, we constructed a design of system to analyze effect of cardiac associated auricular acupuncture reflexology based on physiological signals. System to analyze effect cardiac associated auricular acupuncture reflexology, which carried out analysis and measurement of bio-signal to apply cardiac-related biometrics input in biometric image and voice signal. In addition, we also confirmed through statistical analysis actual home healthcare system to performance evaluation of system on subjects 20.

• Journal of the Korean Society of Radiology
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• v.9 no.5
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• pp.307-314
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• 2015

This study was conducted in reducing the involuntary motion artifacts because of lungs and heart movements as well as the aliasing artifacts generated during the use of the reduced-FOV EPI technique while performing breast MRI. Performed on a total of 38 obesity female subjects who visited the clinic for pre-examination before surgery within the period from August 1 to November 30, 2014. The 3.0T MRI scanner equipped with a breast scanning coil. Qualitative and quantitative analyses were each used for the evaluation of the acquired images while an Paired T-test and Wilcoxon rank test were performed to check the statistical significance. The variation ratio rose by 15.69% with the additional application of a pre-saturation pulse in the lesion, by 13.72% near the lesion, and 20.63% in the fat and the contrast-to-noise ratio rose by 10.58% in and near the lesion and by 12.03% in the lesion and fat, respectively. there were increases of 22.05% and 21.42% at 0 and 1000 respectively in qulitative evaluation and growth of 16.10% in apparent diffusion coefficient. it showed a statistically significant result(p<0.05) in signal to noise ratio, contrast to noise ratio, diffusion slope coefficient and apparent diffusion coefficient. The involuntary movements artifacts that occur in the phase encoding direction and the aliasing artifacts are considered to be reduced to obtain the best image in the additional use of the pre-saturation pulse as DWI is acquired.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.197-203
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• 2017

The purpose of this study was to measure signal to noise ratio (SNR) according to change of equalization from region of interest (ROI) of heart shadow in chest image. We examined images of chest image of 87 patients in a University-affiliated hospital, Seoul, Korea. Chest images of each patient were calculated by using ImageJ. We have analysis socio-demographical variables, SNR according to images, 95% confidence according to SNR of difference in a mean of SNR. Differences of SNR among change of equalization were tested by SPSS Statistics21 ANOVA test for there was statistical significance 95%(p < 0.05). In SNR results, with the quality of distributions in the order of original chest image, original chest image heart shadow and equalization chest image, equalization chest image heart shadow(p < 0.001). In conclusion, this study would be that quantitative evaluation of heart shadow on chest image can be used as an adjunct to the histogram equalization chest image.