• Archives of Plastic Surgery
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• v.43 no.5
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• pp.430-437
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• 2016

Background Accurate breast volume assessment is a prerequisite to preoperative planning, as well as intraoperative decision making in breast reconstruction surgery. The use of three-dimensional surface imaging (3D scanning) to assess breast volume has many advantages. However, before employing 3D scanning in the field, the tool's validity should be demonstrated. The purpose of this study was to confirm the validity of 3D-scanning technology for evaluating breast volume. Methods We reviewed the charts of 25 patients who underwent breast reconstruction surgery immediately after total mastectomy. Breast volumes using the Axis Three 3D scanner, water-displacement technique, and magnetic resonance imaging (MRI) were obtained bilaterally in the preoperative period. During the operation, the tissue removed during total mastectomy was weighed and the specimen volume was calculated from the weight. Then, we compared the volume obtained from 3D scanning with those obtained using the water-displacement technique, MRI, and the calculated volume of the tissue removed. Results The intraclass correlation coefficient (ICC) of breast volumes obtained from 3D scanning, as compared to the volumes obtained using the water-displacement technique and specimen weight, demonstrated excellent reliability. The ICC of breast volumes obtained using 3D scanning, as compared to those obtained by MRI, demonstrated substantial reliability. Passing-Bablok regression showed agreement between 3D scanning and the water-displacement technique, and showed a linear association of 3D scanning with MRI and specimen volume, respectively. Conclusions When compared with the classical water-displacement technique and MRI-based volumetry, 3D scanning showed significant reliability and a linear association with the other two methods.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.599-606
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• 2013

The purpose of this study is to know a clinical usefulness for delineation of articular cartilage compared with 2D TSE-SPIR and 3D FFE-PROSET technique. From January 2013 to september 2013, a total of 30 normal volunteers(12 men and 18 women aged between 35 and 55 years; mean 49.48 years) were studied on a philips 3.0T MRI scanner. As a quantitative analysis, SNRs and CNRs were evaluated by using two methods for delineation of articular cartilage. As a qualitative analysis, image quality was evaluated by special radiological technologist of MRI for image delineation on a three grade. As a results, SNRs and CNRs for articular cartilage were significantly greater for the 3D FFE-PROSET(SNRs: 8.40, 114.02, 9.53, CNRs: 104.49, 139.49) technique compared to 2D TSE-SPIR(SNRs: 4.41, 71.63, 7.34, CNRs: 64.30, 58.41) technique, image quality also was higher for evaluation of 3D FFE-PROSET(2.40) technique(p=0.0021). In conclusion, this study showed that a 3D FFE-PROSET MRI has improved SNRs and CNRs for evaluating of the articular cartilage, these conclusions in the future will be provided useful information in diagnosis of articular cartilage.

• Journal of radiological science and technology
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• v.41 no.5
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• pp.451-456
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• 2018

During last a decade, there has been increased demand for 3D-printed medical devices with significant improvement of 3D-Printer (also known as Additive. Manufacturing AM), which depend upon human body features. Especially, demand for personalized medical material is highly growing with being super-aged society. In this study, 3D-reconstructed 3D mesh image from CT/MRI-images is demonstrated to analyse each patients' personalized anatomical features by using in house, then to be able to manufacture its counterpart. Developed software is distributed free of charge, letting various researcher identify biological feature for each areas.

• Investigative Magnetic Resonance Imaging
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• v.16 no.1
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• pp.55-66
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• 2012

Purpose : During brain MRI scanning, subject's head motion can adversely affect MRI images. To minimize MR image distortion by head movement, we developed an optical tracking system to detect the 3-D movement of subjects. Materials and Methods: The system consisted of 2 CCD cameras, two infrared illuminators, reflective sphere-type markers, and frame grabber with desktop PC. Using calibration which is the procedure to calculate intrinsic/extrinsic parameters of each camera and triangulation, the system was desiged to detect 3-D coordinates of subject's head movement. We evaluated the accuracy of 3-D position of reflective markers on both test board and the real MRI scans. Results: The stereo system computed the 3-D position of markers accurately for the test board and for the subject with glasses with attached optical reflective marker, required to make regular head motion during MRI scanning. This head motion tracking didn't affect the resulting MR images even in the environment varying magnetic gradient and several RF pulses. Conclusion: This system has an advantage to detect subject's head motion in real-time. Using the developed system, MRI operator is able to determine whether he/she should stop or intervene in MRI acquisition to prevent more image distortions.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1168-1177
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• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.251-254
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• 2004

환자의 체동은 MRl에 의해 제공된 화질을 저하시키는 주된 원인이 되고 있다. 본 연구에서는 MRI에 있어서 3차원 강체운동에 기인한 아티팩트를 수정하는 기법을 제안한다. 이러한 목표를 달성하기위해 MR 화상 데이터를 얻기위한 2차원 다-슬라이스 기법(a multiple 2-D slice technique)이 사용되어왔다. 대상물체의 운동에 해당하는 수집된 MRI 데이터는 불균일 표본화와 위상오차에 의해 영향을 받게된다. 3차원 운동에 대해 주어진 운동 파라메타와 장면간의 영향이라는 가정하에 양선형보간법과 중첩법으로 다-슬라이스 데이터를 사용하는 방법에 기반한 재구성 알고리즘을 MRI 아티팩트를 수정하는데 사용한다. 미지의 체동 파라메타들을 추정하기위해 3차원 강체운동은 다-슬라이스 취득기법의 각 영상과 결합된 관심영역 바깥쪽에서의 측정된 에너지를 증가시킨다는 사실을 이용하는 최소에너지법을 적용한다.

• Investigative Magnetic Resonance Imaging
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• v.13 no.2
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• pp.161-170
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• 2009

Purpose : A parallel imaging method provides us to improve temporal resolution to obtain three-dimensional (3D) MR images. The objective of this study was to optimize three 3D MRI techniques by adjusting 2D SESNE factors of the parallel imaging method in phantom and human brain. Materials and Methods : With a 3 Tesla MRI system and an 8-channel phase-array sensitivity-encoding (SENSE) coil, three 3D MRI techniques of 3D T1-weighted imaging (3D T1WI), 3D T2-weighted imaging (3D T2WI) and 3D fluid attenuated inversion recovery (3D FLAIR) imaging were optimized with adjusting SESNE factors in a water phantom and three human brains. The 2D SENSE factor was applied on the phase-encoding and the slice-encoding directions. Signal-to-noise ratio(SNR), percent signal reduction rate(%R), and contrast-to-noise ratio(CNR) were calculated by using signal intensities obtained in specific regions-of-interest (ROI). Results : In the phantom study, SENSE factor = 3 was provided in 0.2% reduction of signals against without using SENSE with imaging within 5 minutes for 3D T1WI. SENSE factor = 2 was provided in 0.98% signal reduction against without using SENSE with imaging within 5 minutes for 3D T2WI. SENSE factor = 4 was provided in 0.2% signal reduction against without using SENSE with imaging around 6 minutes for 3D FLAIR. In the human brain study, SNR and CNR were higher with SENSE factors = 3 than 4 for all three imaging techniques. Conclusion : This study was performed to optimize 2D SENSE factors in the three 3D MRI techniques that can be scanned in clinical time limitations with minimizing SNR reductions. Without compromising SNR and CNR, the optimum 2D SENSE factors were 3 and 4, yielding the scan time of about 5 to 6 minutes. Further studies are necessary to optimize 3D MRI techniques in other areas in human body.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.227-234
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• 2002

This study was conducted to nondestructively estimate the volumetric information of peach and pit and to visualize the 3D information of internal structure from magnetic resonance imaging(MRI) data. Bruker Biospec 7T spectrometer operating at a proton reosonant frequency of 300 MHz was used for acquisition of MRI data of peach. Image processing algorithms and visualization techniques were implemented by using MATLAB (Mathworks) and Visualization Toolkit(Kitware), respectively. Thresholding algorithm and Kohonen's self organizing map(SOM) were applied to MRI data fur region segmentation. Volumetric information were estimated from segemented images and compared to the actual measurements. The average prediction errors of peach and pit volumes were 4.5%, 26.1%, respectively for the thresholding algorithm. and were 2.1%, 19.9%. respectively for the SOM. Although we couldn't get the statistically meaningful results with the limited number of samples, the average prediction errors were lower when the region segmentation was done by SOM rather than thresholding. The 3D visualization techniques such as isosurface construction and volume rendering were successfully implemented, by which we could nondestructively obtain the useful information of internal structures of peach.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.50-50
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• 2003

World Wide Web (WWW)에서 Virtual Reality Modeling Language (VRML)를 이용하는 3 차원 (3D) 디스플레이는 사용자에게 직관적인 정보를 더 효과적으로 제공해 준다. 웹을 기반으로 하는 해부학적 영상과 융합되는 기능적 영상의 3D 가시화는 아직까지 체계적인 방식으로 연구가 활발히 진행되지 않았다. 이 연구의 목적은 2D 영상들과 함께 웹에서 VRML을 이용하여 구현되는 3D 해부학적 표면 영상들과 기능적 표면 영상들을 동시적으로 관찰할 수 있게 하고 VRML을 통해 만들어진 거리 측정 도구를 가지고 관심영역의 공간적인 위치 정보를 제공하는 것이다. 본 연구에서는 한 명의 간질 환자로부터 Magnetic Resonance (MR) 축면 영상과 발작기 및 발작간기 Single Photon Emission Computed Tomo graphy (SPECT) 축면 영상들을 각각 획득하였다. 발작 진원지의 확인을 향상시키기 위해서 subtraction ictal SPECT co registered to MRI (SISCOM) 을 수행하였다. SISCOM 결과로 나타난 각 2D 영상들은 모든 voxel 들의 평균 값 위로 1 표준편차와 2 표준편차에 해당하는 문턱 이상의 영상 값을 갖도록 하였다. SISCOM으로 나타나는 간질 발작 진원지들과 MRI 영상에서 회색질, 백색질 및 뇌척수액의 경계들을 각각 분할하고 marching cube 알고리즘에 의해 VRML 표면 영상들로 나타내었다. 축면 영상에서 실제 거리를 나타내는 x, y 축의 길이를 측정하고 z 축선의 길이를 계산하였다. VRML을 이용한 거리 측정 도구를 만들어 이전의 VRML 표면 영상들과 융합하였다. MRI 영상을 이용하여 3D 표면 영상들의 단면을 나타내고 3D 표면 영상들의 투명도를 설정하기 위해 Java Script 루틴을 사용자 인터페이스 도구로서 삽입하였다. 웹 페이지에서 구현되는 3D 표면 영상들의 투명도와 관찰 위치를 조절함에 따라 모델들 사이의 공간적인 정보를 직관적으로 알 수 있었다. 간질 발작 진원지에 대응하는 해부학적 구조를 3D 표면 영상들을 가로지르는 MRI 평면 영상들을 통해서 확인하였다. 결론적으로 본 연구에서 제시하는 웹에 근거한 3D 융합 영상의 가시화와 위치 측정은 진단 및 치료 방사선학과 외과학 등의 분야에서 온라인 방식의 연구와 교육에 있어 많은 도움을 줄 것이다.

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.22-22
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• 2003

The purpose of this study was to compare the detection rate of brain metastasis according to size of nodule between 1.5T and 3.0T MRI 대상 및 방법： We reviewed 44 patients with primary tumors and clinical symptoms suggesting brain metastasis. After administration of double dose gadolinium-DTPA, MR imaging was performed with 3D SPGR sequence by 3.0T MRI and then with T1 SE sequence by 1.5T MRI. Consequently, comparison was done in 1.5T T1 SE sequence and 3.0T 3D SPGR sequence. With use of the signal intensity (SI) measurements in the metastatic nodules and adjacent tissue, metastatic nodule-to-adjacent tissue SI ratio were calculated. In each patient, the number of metastatic lesions detected in 1.5T and 3.0T, and their size were assessed qualitatively by three blinded readers.