• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.939-948
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• 2004

In this paper. we Propose a robust and fast image registration technique for motion correction in brain CT-CT angiography obtained from same patient to be taken at different time. First, the feature points of two images are respectively extracted by 3D edge detection technique, and they are converted to locally weighted 3D distance map in reference image. Second, we search the optimal location whore the cross-correlation of two edges is maximized while floating image is transformed rigidly to reference image. This optimal location is determined when the maximum value of cross-correlation does't change any more and iterates over constant number. Finally, two images are registered at optimal location by transforming floating image. In the experiment, we evaluate an accuracy and robustness using artificial image and give a visual inspection using clinical brain CT-CT angiography dataset. Our proposed method shows that two images can be registered at optimal location without converging at local maximum location robustly and rapidly by using locally weighted 3D distance map, even though we use a few number of feature points in those images.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.469-473
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• 2010

본 논문에서는 조각 병리 영상을 강체 정합을 통해 하나의 영상으로 자동 스티칭하는 방법을 제안한다. 제안 방법은 영상의 위치 초기화, 위치 보정, 강체 정합의 세 단계로 이루어진다. 첫째, 영상의 위치 초기화 단계에서는 순서 없이 흩어진 부분 영상을 탬플릿 매칭 기법을 사용한 영상 내 문자 인식을 통해 위치를 초기화한다. 둘째, 강체 정합의 정확성을 높이기 위해 코너점을 이용해 부분 영상의 위치를 보정한다. 셋째, 조각 영상 간 거리를 최소화하는 강체 정합을 수행한다. 실험 결과, 부분 영상 간 간격이 최소화되어 하나의 영상으로 스티칭되는 것을 확인하였고, 최적화 반복 횟수와 변환 벡터에 따른 정확성, 견고성 평가를 통해 거리 차의 제곱 합이 최소화되어 수렴됨을 알 수 있었다. 본 논문의 제안 방법은 조각 영상을 하나의 영상으로 스티칭함으로써 병리 조직의 전체적인 구조 파악과 이를 이용한 전립선암 확진에 사용될 수 있다.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.700-704
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• 2009

In this paper, we propose a method for combining MR image with histopathology image of the prostate using image correction and multi-stage registration. Our method consists of four steps. First, the intensity of prostate bleeding area on T2-weighted MR image is substituted for that on T1-weighted MR image. And two or four tissue sections of the prostate in histopathology image are combined to produce a single prostate image by manual stitching. Second, rigid registration is performed to find the affine transformations that to optimize mutual information between MR and histopathology images. Third, the result of affine registration is deformed by the TPS warping. Finally, aligned images are visualized by the intensity intermixing. Experimental results show that the prostate tumor lesion can be properly located and clearly visualized within MR images for tissue characterization comparison and that the registration error between T2-weighted MR and histopathology image was 0.0815mm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.115-120
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• 2002

The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line may be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.9
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• pp.725-730
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• 2002

The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line nay be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.359-361
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• 2012

본 논문은 T2강조 MR 영상과 확산강조 MR 영상의 강체 정합을 통해 크기, 위치, 회전 변환 왜곡을 보정하여 자궁내막암의 위치를 자동으로 찾는 방법을 제안한다. 영상해상도와 밝기값 분포가 서로 다른 두 영상간 정합의 정확성을 향상시키기 위해 잡음을 제거하고 두 영상의 밝기값 신호 분포의 유사성을 강화시킨다. 유사성이 향상된 두 영상의 크기, 위치, 회전 변환 왜곡을 보정하기 위해 정규화 상호정보를 최대화 하는 강체 정합을 반복적으로 수행한다. 정합된 영상에서 악성 종양을 쉽게 판별 할 수 있도록 현상확상계수지도를 컬러맵으로 생성하여 T2강조 MR 영상에서 얻은 종양의 후보군에 매핑하여 T2강조 MR 영상과 융합한다. 실험을 위하여 최적화 반복 과정에 따른 정규화 상호정보 수치 수렴 과정을 확인하고, 융합 후 종양 영역이 매핑되는 것을 육안평가를 통해 분석하였다. 제안방법을 통하여 T2강조 MR 영상과 확산강조 MR 영상을 융합함으로써 종양의 위치를 자동으로 파악하고 자궁내막암의 병기를 확정하는 용도로 활용할 수 있다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.500-505
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• 2003

In this paper, the method to register multiple sets of skull CT images to absolute coordinate system is proposed. Contrary to correspondence paired mapping of previous techniques, four anatomical landmark points, three coplanar points and one non-coplanar point, compose three principal axes simple and unique for efficient registration by means of rigid body transformation. Throughout the numerical simulation with added random noises, the error performances in terms of different rotation and rounding-off of landmark points, and incorrect localization of anatomical landmark and target points are quantitatively analyzed to generalize the proposed technique. Experiments using real skull CT images demonstrate the feasibility for an efficient use in clinical practice.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.623-632
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• 2009

In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.193-199
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• 2011

It is necessary to register precisely Digital Elevation Model (DEM) generated from SPOT -5 stereo images in order to monitor the topographic and environmental changes of important topographic features such as Mt. Baekdu. The SPOT-5 DEM is registered taking SRTM DEM as a reference DEM. If SPOT-5 DEM is transformed with single 3D rigid equation, it has many errors. Therefore, this study extracted uniformly ground control points over study area and estimated locally adapted transformation equation. The accuracy of proposed method was evaluated with comparison to scale-based and GCP-based transformation method.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.258-268
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• 2021

Point cloud content is immersive content that represents real-world objects with three-dimensional (3D) points. In the process of acquiring point cloud data or encoding and decoding point cloud data, the resolution of point cloud content could be degraded. In this paper, we propose a method of progressively enhancing the resolution of sequential point cloud contents through inter-frame registration. To register a point cloud, the iterative closest point (ICP) algorithm is commonly used. Existing ICP algorithms can transform rigid bodies, but there is a disadvantage that transformation is not possible for non-rigid bodies having motion vectors in different directions locally, such as point cloud content. We overcome the limitations of the existing ICP-based method by registering regions with motion vectors in different directions locally between the point cloud content of the current frame and the previous frame. In this manner, the resolution of the point cloud content with geometric movement is enhanced through the process of registering points between frames. We provide four different point cloud content that has been enhanced with our method in the experiment.