• Nuclear Medicine and Molecular Imaging
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• v.42 no.1
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• pp.81-81
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• 2008

A 69-year old male with cholangiocellular carcinoma (CCC) was assigned to our department for whole body PET/CT scan. $^{18}F$-FDG PET/CT images showed an intense hypermetabolic lobulating mass(SUVmax = 8.7 / size : 11.4 mm) in the right hepatic lobe with multiple metastatic lung nodules. We made three dimensional volume rendering fusion images by using advantage workstation 4.3 (GE health care) which provide quick anatomic overview and improve the planning process significantly.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.634-637
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• 2002

오늘날 CT나 MR등을 통한 의학 영상 기술과 컴퓨터 성능의 향상으로 인체 내부 장기의 영상을 비교적 용이하게 얻을 수 있으며 얻어진 영상 정보는 컴퓨터로 수치와 되므로 데이터의 조작 및 가공이 용이하다. 그러나, 이 데이터는 2D 슬라이스들의 연속으로 표현되므로 이것을 보다 편리하게 가시화. 조작, 분석이 용이한 상태로 바꾸기 위해서는 3차원 구조로의 재구성이 필요하게 된다. 이것을 위하여 무엇보다도 먼저 CT나 MR을 통하여 얻어진 영상을 분석하여 특정 장기의 영상 부분를 다른 조직의 영상부분으로부터 분리(segmentation)할 필요가 있다. 이러한 Segmentation방법에는 여러가지가 있는데, 수작업의 결합 등으로 인해서 비효율적인 문제점을 가지고 있다. 이에 본 논문은 보다 효율적인 segmentation의 처리를 위하여 region-based 기법을 응용하여 새로운 segmentation 방법을 개발하였다. 그리하여, 본 논문이 제안한 알고리즘을 슬라이스 간격이 큰 2차원 복부 CT 영상에 적용시켜 간(liver)의 추출을 시도하였고 향상된 성능을 확인할 수 있었다.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.991-999
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• 2013

Lower limbs deformity is a congenital disease and can also be occurred by an acquired factor. This paper suggests a new technique for surgical planning of Corrective Osteotomy for Lower Limbs (COLL) using 2D-3D medical image registration. Converting to a 3D modeling data of lower limb based on CT (computed tomography) scan, and divide it into femur, tibia and fibula; which composing the lower limb. By rearranging the model based on the biplane 2D images of X-ray data, a 3D upright bone structure was acquired. There are two ways to array the 3D data on the 2D image: Intensity-based registration and feature-based registration. Even though registering Intensity-based method takes more time, this method will provide more precise results, and will improve the accuracy of surgical planning.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.35-42
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• 2018

Direct volume rendering (DVR) is an important 3D visualization method for medical images as it depicts the full volumetric data. However, because DVR renders the whole volume, regions of interests (ROIs) such as a tumor that are embedded within the volume maybe occluded from view. Thus, conventional 2D cross-sectional views are still widely used, while the advantages of the DVR are often neglected. In this study, we propose a new visualization algorithm where we augment the 2D slice of interest (SOI) from an image volume with volumetric information derived from the DVR of the same volume. Our occlusion-based DVR augmentation for SOI (ODAS) uses the occlusion information derived from the voxels in front of the SOI to calculate a depth parameter that controls the amount of DVR visibility which is used to provide 3D spatial cues while not impairing the visibility of the SOI. We outline the capabilities of our ODAS and through a variety of computer tomography (CT) medical image examples, compare it to a conventional fusion of the SOI and the clipped DVR.

• Clinics in Shoulder and Elbow
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• v.23 no.3
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• pp.119-124
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• 2020

Background: This study was performed to compare glenoid version and inclination measured using two-dimensional (2D) images from computed tomography (CT) scans or three-dimensional (3D) reconstructed bone models. Methods: Thirty patients who had undergone conventional CT scans were included. Two orthopedic surgeons measured glenoid version and inclination three times on 2D images from CT scans (2D measurement), and two other orthopedic surgeons performed the same measurements using 3D reconstructed bone models (3D measurement). The 3D-reconstructed bone models were acquired and measured with Mimics and 3-Matics (Materialise). Results: Mean glenoid version and inclination in 2D measurements were -1.705° and 9.08°, respectively, while those in 3D measurements were 2.635° and 7.23°. The intra-observer reliability in 2D measurements was 0.605 and 0.698, respectively, while that in 3D measurements was 0.883 and 0.892. The inter-observer reliability in 2D measurements was 0.456 and 0.374, respectively, while that in 3D measurements was 0.853 and 0.845. Conclusions: The difference between 2D and 3D measurements is not due to differences in image data but to the use of different tools. However, more consistent results were obtained in 3D measurement. Therefore, 3D measurement can be a good alternative for measuring glenoid version and inclination.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1523-1528
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• 2020

Partial anomalous pulmonary venous return (PAPVR) is a rare congenital cardiac anomaly that can be difficult to detect and often remains undiagnosed. PAPVR is diagnosed using non-invasive imaging techniques such as echocardiography, CT, and MRI. Image data are reviewed on a 2-dimensional (D) monitor, which may not facilitate a good understanding of the complex 3D heart structure. In recent years, 3D printing technology, which allows the creation of physical cardiac models using source image datasets obtained from cardiac CT or MRI, has been increasingly used in the medical field. We report a case involving a 3D-printed model of PAPVR with a biatrial connection. This model demonstrated separate drainages of the right upper and middle pulmonary veins into the lower superior vena cava (SVC) and the junction between the SVC and the right atrium, respectively, with biatrial communication through the right middle pulmonary vein.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.673-680
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• 2022

In this study, based on PLA, we analyzed the Hounsfield Unit (HU) of materials containing 20% each of aluminum, wood, copper, carbon, and marble, and tried to analyze how they affect the image. A cylindrical phantom of 5×30×30 ㎣ (thickness×diameter×height) was fabricated using a entry-level 3D printer. The kV was changed to 80, 100 and 120, and the mAs was changed to 100 and 200 mAs, and the phantom in the center of the table was cross-scanned under a total of six conditions. A circular ROI was set using image J program and the quantification value of the material part HU and the quantification value of the peripheral part CNR were obtained. The HU average of the material part increased in the order of [PLA - wood 20%], [PLA - marble 20%], [PLA - carbon 20%], [PLA 100%], [PLA - aluminum 20%], [PLA - copper 20%] (p<0.05) a negative correlation was confirmed with the HU by increasing kV. It was confirmed that the CNR value in the peripheral area increased in the order of [PLA - marble 20%], [PLA - copper 20%], [PLA - carbon 20%], [PLA - wood 20%], [PLA - aluminum 20%], and [PLA - 100%] (p<0.05). Human organs with similar HU values for each material are [PLA - copper 20%] compact bone, [PLA - aluminum 20%] cancellous bone, [PLA 100%] coagulated blood, [PLA - carbon 20%] and [PLA - marble 20%] liver, muscle, spleen and [PLA - wood 20%] had similar values to fat. In addition, we confirmed the blur phenomenon that blurs the image around the filament with all materials, and confirmed that [PLA 100%] especially has the most blur around the filament. Therefore, it is considered desirable to reflect the HU value of the target organ and consider cloudiness around the phantom when selecting materials for medical phantom fabrication, and this research can provide basic data.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.188-194
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• 2013

In this paper, we proposed a new method for pulmonary vessels image segmentation and refinement from pulmonary image. Proposed method consist of following five steps. First, threshold estimation is performed by polynomial regression analysis of histogram variation rate of the pulmonary image. Second, segmentation of pulmonary vessels object is performed by density-based segmentation method based on estimated threshold in first step. Third, 2D connected component labeling method is applied to segmented pulmonary vessels. The seed point of both side diaphragms is determined by eccentricity and size of component. Fourth step is diaphragm extraction by 3D region growing method at the determined seed point. Finally, noise cancelation of pulmonary vessels image is performed by 3D connected component labeling method. The experimental result is showed accurately pulmonary vessels image segmentation, the diaphragm extraction and the noise cancelation of the pulmonary vessels image.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.457-460
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• 2002

The image quality of three-dimensional (3D) images has been widely investigated by the qualitative analysis method. A need remains for an objective and quantitative method to assess the image quality of 3D volume-rendered images. The purpose of this study was to evaluate the quantitative accuracy of distance measurements on 3D volume-rendered images of a dry human skull by using multi-detector computed tomography (MDCT). A radiologist measured five times the twenty-one direct measurement line items composed among twelve reference points on the skull surface with a digital vernier caliper. The water filled skull specimen was scanned with a MDCT according to the section thicknesses of 1.25, 2.50, 3.75, and 5.00 mm for helical (high quality; pitch 3:1) scan mode. MDCT data were reconstructed with its acquisition section thickness and with 1.25 mm section thickness for all scans. An observer also measured seven times the corresponding items on 3D volume-rendered images with measuring tools provided by volumetric analysis software. The quantitative accuracy of distance measurements on the 3D volume-rendered images was statistically evaluated (p-value < 0.05) by comparatively analyzing these measurements with the direct distance measurements. The accuracy of distance measurements on the 3D volume-rendered MDCT images acquired with 1.25, 2.50, 3,75 and 5.00 mm section thickness and reconstructed with its section thickness were 48%, 33%, 23%, and 14%, respectively. Meanwhile, there were insignificant statistical differences in accuracy of distance measurements among 3D volume-rendered images reconstructed with 1.25 mm section thickness for the each acquisition section thickness. MDCT images acquired with thick section thickness and reconstructed with thin section thickness in helical scan mode should be effectively used in medical planning of 3D volume-rendered images. The quantitative analysis of distance measurement may be a useful tool for evaluating the quantitative accuracy and the defining optimal parameters of 3D volume-rendered CT images.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.119-126
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• 2023

Sarcopenia is not well known enough to be classified as a disease in 2021 in Korea, but it is recognized as a social problem in developed countries that have entered an aging society. The diagnosis of sarcopenia follows the international standard guidelines presented by the European Working Group for Sarcopenia in Older People (EWGSOP) and the d Asian Working Group for Sarcopenia (AWGS). Recently, it is recommended to evaluate muscle function by using physical performance evaluation, walking speed measurement, and standing test in addition to absolute muscle mass as a diagnostic method. As a representative method for measuring muscle mass, the body composition analysis method using DEXA has been formally implemented in clinical practice. In addition, various studies for measuring muscle mass using abdominal images of MRI or CT are being actively conducted. In this paper, we develop an AI image segmentation model based on abdominal images of CT with a relatively short imaging time for the diagnosis of sarcopenia and describe the multicenter validation. We developed an artificial intelligence model using U-Net that can automatically segment muscle, subcutaneous fat, and visceral fat by selecting the L3 region from the CT image. Also, to evaluate the performance of the model, internal verification was performed by calculating the intersection over union (IOU) of the partitioned area, and the results of external verification using data from other hospitals are shown. Based on the verification results, we tried to review and supplement the problems and solutions.