• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2697-2700
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• 2003

이 논문에서는 3 차원 CT/CTA 영상 데이터에 대하여 고속 자동 정합 기법을 제안한다. 제안하는 기법은 다해상도 (multi-resolution) 구조의 정규 상호 정보량(normalized mutual information) 을 최대화하는 정합 방식에서, 정합 유사도를 계산하는 볼륨 영역을 효율적으로 줄여 정합 속도를 증가시키는 방법이다. 제안된 정합방식을 CT/CTA (CT angiography) 팬텀 데이터와 7 세트의 실제 CT/CTA 임상 데이터에 적용하여 테스트하였다. 이로부터 제안하는 방식이, 정합 정확도를 유지하는 동시에 정합 속도를 10 ∼ 60％ 로 감소시킴을 확인 할 수 있었다. 또한 제안된 정합 방식을 DS-CTA (digital subtraction CT angiography) 에 적용하여, CT/CTA 영상으로부터 혈관 영상을 성공적으로 추출하였다.

• Journal of the Korean Society of Radiology
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• v.85 no.2
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• pp.297-307
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• 2024

Coronary artery disease (CAD) narrows vessel lumens at the sites of atherosclerosis, increasing the risk of myocardial ischemia or infarction. Early and accurate diagnosis of CAD is crucial to significantly improve prognosis and management. CT angiography (CTA) is a noninvasive imaging technique that enables assessment of vascular structure and stenosis with high resolution and contrast. Coronary CTA is useful in the diagnosis of CAD. Recently, the CAD-reporting and data system (CAD-RADS), a diagnostic classification system based on coronary CTA, has been developed to improve intervention efficacy in patients suspected of CAD. While the CADRAD is based on CTA, it includes borderline categories where interpreting the coronary artery status solely based on CTA findings may be challenging. This review introduces CTA findings that fall within the CAD-RADS categories that necessitate additional tests to decide to perform invasive coronary angiography and discusses appropriate management strategies.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.637-645
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• 2017

The objective of this study was to find the optimum test device for the cerebral blood vessels by comparing and analyzing the SNR and CNR methods for images of three devices (i.e., MRA, CTA, and DSA). The study targeted 90 patients who underwent cerebral angiography from November 2016 to May 2017. The measuring parts were measured by using Rt MCA, Lt MCA, and ACA Image J. The results of quantitative analysis showed that the mean SNR of MRA, the CNR of MRA, the signal strength of MRA, the mean SNR of CTA, the CNR of CTA, the signal strength of CTA, the SNR of DSA, the CNR of DSA, and the signal strength of DSA were evaluated as 254.87, 178.13, 326.81, 74.75, 62.2, 356.66, 26.85, 25.89, and 4400.69, respectively (p<0.05). As a result, both SNR and CNR methods measured it in the order of MRA>CTA>DSA. Statistical significance was determined by using ANOVA analysis at p<0.05 and Bonferroni method was used as a post-hoc analysis SPSS. In conclusion, the results of this study revealed that the optimum imaging devices were MRA, CTA, and DSA after evaluating randomly selected patients with cerebrovascular disease.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.445-449
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• 2009

In this paper, we propose a computationally efficient multi GPU accelerated image registration technique to correct the motion difference between the pre-contrast CT image and post-contrast CTA image. Our method consists of two steps: multi GPU based image registration and a cerebrovascular visualization. At first, it computes a similarity measure considering the parallelism between both GPUs as well as the parallelism inside GPU for performing the voxel-based registration. Then, it subtracts a CT image transformed by optimal transformation matrix from CTA image, and visualizes the subtracted volume using GPU based volume rendering technique. In this paper, we compare our proposed method with existing methods using 5 pairs of pre-contrast brain CT image and post-contrast brain CTA image in order to prove the superiority of our method in regard to visual quality and computational time. Experimental results show that our method well visualizes a brain vessel, so it well diagnose a vessel disease. Our multi GPU based approach is 11.6 times faster than CPU based approach and 1.4 times faster than single GPU based approach for total processing.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1454-1464
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• 2013

In this paper, we propose a rapid rigid registration method for the fusion visualization of intra-operative 2D XA and pre-operative 3D CTA images. In this paper, we propose a global movement estimation based on a trilateration for the fast and robust initial registration. In addition, the principal axis of each image is generated and aligned, and the bounding box of the vascular shape is compared for more accurate initial registration. For the fine registration, two images are registered where the distance between two vascular structures is minimized by selective distance measure. In the experiment, we evaluate a speed, accuracy and robustness using five patients' data by comparing the previous registration method. Our proposed method shows that two volumes can be registered at optimal location rapidly, and robustly comparing with the previous method.

• Journal of the Korean Society of Radiology
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• v.11 no.6
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• pp.493-500
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• 2017

In this study, data analysis has been conducted by INFINITT program to analyze the effect of signal to noise ratio(SNR) and contrast to noise ratio(CNR) of flow related enhancement(FRE) and computed tomography Angiography(CTA) on cerebrovascular diseases for qualitative evaluations. Based on the cerebrovascular image results achieved from 63 patients (January to April, 2017, at C University Hospital), we have selected 19 patients that performed both FRE-MRA and CTA. From the 19 patients, 2 were excluded due to artifacts from movements in the cerebrovascular image results. For the analysis conditions, we have set the 5 part (anterior cerebral artery, right and left Middle cerebral artery, right and left Posterior cerebral artery) as the interest area to evaluate the SNR and CNR, and the results were validated through Independence t Test. As a result, by averaging the SNR, and CNR values, the corresponding FRE-MRA achieved were: anterior cerebral artery ($1500.73{\pm}12.23/970.43{\pm}14.55$), right middle cerebral artery ($1470.16{\pm}11.46/919.44{\pm}13.29$), left middle cerebral artery ($1457.48{\pm}17.11/903.96{\pm}14.53$), right posterior cerebral artery ($1385.83{\pm}16.52/852.11{\pm}14.58$), left posterior cerebral artery ($1318.52{\pm}13.49/756.21{\pm}10.88$). by averaging the SNR, and CNR values, the corresponding CTA achieved were: anterior cerebral artery ($159.95{\pm}12.23/123.36{\pm}11.78$), right middle cerebral artery ($236.66{\pm}17.52/202.37{\pm}15.20$), left middle cerebral artery ($224.85{\pm}13.45/193.14{\pm}11.88$), right posterior cerebral artery ($183.65{\pm}13.47/151.44{\pm}11.48$), left posterior cerebral artery ($177.7{\pm}16.72/144.71{\pm}11.43$) (p < 0.05). In conclusion, MRA had high SNR and CNR value regardless of the cerebral infarction or cerebral hemorrhage observed in the 5 part of the brain. Although FRE-MRA consumed longer time, it proved to have less side effect of contrast media when compared to the CTA.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.196-204
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• 2016

World Health Organization reported that heart-related diseases such as coronary artery stenoses show the highest occurrence rate which may cause heart attack. Using Computed Tomography angiography images will allow radiologists to detect and have intervention by creating 3D roadmapping of the vessels. However, it is often complex and difficult do reconstruct 3D vessel which causes very large amount of time and previous researches were studied to segment vessels more accurate automatically. Therefore, in this paper, Region Competition, Geodesic Active Contour (GAC), Multi-atlas based segmentation and Active Shape Model algorithms were applied to segment aortic root from CTA images and the results were analyzed by using mean Hausdorff distance, volume to volume measure, computational time, user-interaction and coronary ostium detection rate. As a result, Extracted 3D aortic model using GAC showed the highest accuracy but also showed highest user-interaction results. Therefore, it is important to improve automatic segmentation algorithm in future

• Korean Journal of Digital Imaging in Medicine
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• v.3 no.1
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• pp.206-210
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• 1997

• Korean Journal of Digital Imaging in Medicine
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• v.3 no.1
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• pp.198-205
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• 1997

• Korean Journal of Digital Imaging in Medicine
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• v.3 no.1
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• pp.188-196
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• 1997