• 대한의용생체공학회:의공학회지
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• 제37권2호
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• pp.68-74
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• 2016

In this study, we investigated the rotational characteristics which were comprised of directionality and linearity of target registration error (TRE) as a study in advance to enhance the accuracy of contour-based registration in neuronavigation. For the experiment, two rigid head phantoms that have different faces with specially designed target frame fixed inside of the phantoms were used. Three-dimensional coordinates of facial surface point cloud and target point of the phantoms were acquired using computed tomography (CT) and 3D scanner. Iterative closest point (ICP) method was used for registration of two different point cloud and the directionality and linearity of TRE in overall head were calculated by using 3D position of targets after registration. As a result, it was represented that TRE had consistent direction in overall head region and was increased in linear fashion as distance from facial surface, but did not show high linearity. These results indicated that it is possible for decrease TRE by controlling orientation of facial surface point cloud acquired from scanner, and the prediction of TRE from surface registration error can decrease the registration accuracy in lesion. In the further studies, we have to develop the contour-based registration method for improvement of accuracy by considering rotational characteristics of TRE.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1830-1835
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• 2015

In this paper, we propose an algorithm for the automatic registration of two rigid parts using multiple 3D sensor systems on a robot. Four sets of structured laser stripe system consisted of a camera and a visible laser stripe is used for the acquisition of 3D information. Detailed procedures including extrinsic calibration among four 3D sensor systems and hand/eye calibration of 3D sensing system on robot arm are presented. We find a best pose using search-based pose estimation algorithm where cost function is proposed by reflecting geometric constraints between sensor systems and target objects. A pose with minimum gap and height difference is found by greedy search. Experimental result using demo system shows the robustness and feasibility of the proposed algorithm.

• International Journal of CAD/CAM
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• 제9권1호
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• pp.103-109
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• 2010

Recently, various conformal geometric methods have been presented for non-rigid surface matching and registration. This work proposes to improve the robustness of conformal geometric methods to the boundaries by incorporating the symmetric information of the input surface. We presented two symmetric conformal mapping methods, which are based on solving Riemann-Cauchy equation and curvature flow respectively. Experimental results on geometric data acquired from real life demonstrate that the symmetric conformal mapping is insensitive to the boundary occlusions. The method outperforms all the others in terms of robustness. The method has the potential to be generalized to high genus surfaces using hyperbolic curvature flow.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2005년도 GIS/RS 공동 춘계학술대회
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• pp.345-349
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• 2005

Massive amount of satellite image processing such asglobal/continental-level analysis and monitoring requires automated and speedy georegistration. There could be two major automated approaches: (1) rigid mathematical modeling using sensor model and ephemeris data; (2) heuristic co-registration approach with respect to existing reference image. In case of ETM+, the accuracy of the first approach is known as RMSE 250m, which is far below requested accuracy level for most of satellite image processing. On the other hands, the second approach is to find identical points between new image and reference image and use heuristic regression model for registration. The latter shows better accuracy but has problems with expensive computation. To improve efficiency of the coregistration approach, the author proposed a pre-qualified matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with correlation coefficient. Throughout the pre-qualification approach, the computation time was significantly improved and make the registration accuracy is improved. A prototype was implemented and tested with the proposed algorithm. The performance test of 14 TM/ETM+ images in the U.S. showed: (1) average RMSE error of the approach was 0.47 dependent upon terrain and features; (2) the number average matching points were over 15,000; (3) the time complexity was 12 min per image with 3.2GHz Intel Pentium 4 and 1G Ram.

• IEIE Transactions on Smart Processing and Computing
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• 제4권5호
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• 대한의용생체공학회:의공학회지
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• 제32권3호
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• pp.237-244
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• 2011

In this paper, a feature-based registration technique is proposed for pre-contrast and post-contrast lung CT images. It utilizes three dimensional(3-D) features with their descriptors and estimates feature correspondences by nearest neighborhood matching in the feature space. We design a transformation model between the input image pairs using a free form deformation(FFD) which is based on B-splines. Registration is achieved by minimizing an energy function incorporating the smoothness of FFD and the correspondence information through a non-linear gradient conjugate method. To deal with outliers in feature matching, our energy model integrates a robust estimator which discards outliers effectively by iteratively reducing a radius of confidence in the minimization process. Performance evaluation was carried out in terms of accuracy and efficiency using seven pairs of lung CT images of clinical practice. For a quantitative assessment, a radiologist specialized in thorax manually placed landmarks on each CT image pair. In comparative evaluation to a conventional feature-based registration method, our algorithm showed improved performances in both accuracy and efficiency.

• Korean Journal of Radiology
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• 제19권6호
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• pp.1053-1065
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• 2018

Objective: To evaluate the clinical impact of using registration software for ablative margin assessment on pre-radiofrequency ablation (RFA) magnetic resonance imaging (MRI) and post-RFA computed tomography (CT) compared with the conventional side-by-side MR-CT visual comparison. Materials and Methods: In this Institutional Review Board-approved prospective study, 68 patients with 88 hepatocellulcar carcinomas (HCCs) who had undergone pre-RFA MRI were enrolled. Informed consent was obtained from all patients. Pre-RFA MRI and post-RFA CT images were analyzed to evaluate the presence of a sufficient safety margin (${\geq}3mm$) in two separate sessions using either side-by-side visual comparison or non-rigid registration software. Patients with an insufficient ablative margin on either one or both methods underwent additional treatment depending on the technical feasibility and patient's condition. Then, ablative margins were re-assessed using both methods. Local tumor progression (LTP) rates were compared between the sufficient and insufficient margin groups in each method. Results: The two methods showed 14.8% (13/88) discordance in estimating sufficient ablative margins. On registration software-assisted inspection, patients with insufficient ablative margins showed a significantly higher 5-year LTP rate than those with sufficient ablative margins (66.7% vs. 27.0%, p = 0.004). However, classification by visual inspection alone did not reveal a significant difference in 5-year LTP between the two groups (28.6% vs. 30.5%, p = 0.79). Conclusion: Registration software provided better ablative margin assessment than did visual inspection in patients with HCCs who had undergone pre-RFA MRI and post-RFA CT for prediction of LTP after RFA and may provide more precise risk stratification of those who are treated with RFA.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권12호
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• pp.967-976
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• 2009

본 논문에서는 CT 및 CT 혈관 조영 영상에서 강체 정합 및 뼈 소거법을 이용한 하지 혈관 자동 추출 방법을 제안한다. 첫째, 뼈의 부분적인 움직임을 반영하기 위하여 해부학 정보를 바탕으로 하지를 자동 구역화하고, 둘째, CT와 CTA 영상간 움직임을 산정하기 위하여 거리지도 기반의 강체 정합을 수행한다. 셋째, CTA 영상에서 복잡한 구조를 갖는 뼈를 제거하고 뼈에 인접한 혈관이 깎이는 것을 방지하기 위하여 뼈 소거법과 혈관 마스킹 기법을 제안한다. 넷째, 정합오차 및 연골 등의 잡음을 줄이기 위하여 혈관 추적 기반의 후 처리 과정을 통하여 보정한다. 제안 방법의 평가를 위해 육안 평가와 정확성 평가 그리고 수행시간을 측정하였다. 육안 평가를 위해 차감 기법, 정합 후 차감 기법, 제안 방법을 적용한 결과를 볼륨렌더링과 최대 강도 투영영상을 사용하여 비교하였다. 정확성 평가를 위해 CTA 영상과 차감 기반 기법 및 제안 방법을 적용한 결과의 밝기값 분포도를 분석하였다. 실험 결과 뼈는 제거되고 가는 혈관 및 다른 조직의 손실 없이 혈관이 정확하게 추출되었음을 볼 수 있었고, 13명의 환자 데이터 전채에 대한 전체 수행시간은 약 40포 정도로 측정되었다.

• 한국컴퓨터정보학회논문지
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• 제12권2호
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• pp.123-130
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• 2007

본 논문에서는 소동물 생체내 실험시 서로 다른 장비에서 획득된 영상의 융합 및 정합을 위한 방법을 제안한다. 마우스의 꼬리 정맥에 $[[^{18}F]FDG$를 주사하여 60분 섭취후 서로 다른 장비에서 동일한 위치의 영상을 획득하기 위하여 아크릴 재질의 소동물 가이드에 기준마크를 설정하고 microPET과 CT 영상을 획득하였다. MicroPET으로 획득된 리스트모드(list-mode) 데이터는 Fourier Rebinning(FRB) 방법을 사용하여 사이노그램(Sinogram)으로 변환 후 4 번의 반복횟수를 가지는 Ordered Subset Expectation Maximization(OSEM) 알고리즘으로 재구성하였다. MicroPET 영상획득후 PET/CT의 CT를 이용하여 CT영상을 획득하였다. MicroPET 영상에서 폐영역을 정확히 찾아내는 어려움이 있어. 해부학적 정보를 제공하는 CT 영상을 이용하여 폐 영역을 구분하였다. 영상 융합을 위한 불일치 부분을 해결하기 위하여 기준마크의 정보와 폐 영역의 정보를 이용하여 회전과 이동정보를 가지는 어파인 (affine) 변환 행렬 구하여 영상 정합에 사용하였다. 이 방법은 정량적 정확성과 영상 해석의 정확성을 개선할 것으로 기대된다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권1호
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• pp.41-49
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• 2005

본 논문에서는 동일 환자에 대하여 시간차론 두고 촬영한 복부 CT 영상에서 환자의 움직임에 따른 두 영상 간 차이를 보정하기 위하여 지역적 거리전파를 이용한 자동 폐 정합 방법을 제안한다. 본 제안방법은 다음과 같은 세 단계로 구성된다 첫 번째, 일련의 두 볼륨데이타에서 폐 경계를 추출한 후, 폐를 포함하는 최적경계볼륨을 생성하여 초기정합을 수행한다 두 번째, 초기에 촬영한 볼륨데이타에서 지역적 거리전파를 이용하여 폐 경계로부터 3차원 거리맵을 생성한다. 세 번째, 선택적 거리 측정을 통해 두 경계간에 거리차이가 최소인 위치로 영상을 정합한다. 실험으로 3명의 환자 데이타에 대하여 영상정합을 하였고, 기존의 챔퍼매칭 정합 방법과 수행속도와 견고성 측면에서 비교 평가하였다. 본 제안방법은 지역적 거리전파를 사용하여 생성된 3차원 거리맵을 이용한 선택적 거리측정을 통하여 최적의 위치로 빠르고 견고하게 정합된다.