• Title/Summary/Keyword: 3D-D registration

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Rapid Stitching Method of Digital X-ray Images Using Template-based Registration (템플릿 기반 정합 기법을 이용한 디지털 X-ray 영상의 고속 스티칭 기법)

  • Cho, Hyunji;Kye, Heewon;Lee, Jeongjin
    • Journal of Korea Multimedia Society
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    • v.18 no.6
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    • pp.701-709
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    • 2015
  • Image stitching method is a technique for obtaining an high-resolution image by combining two or more images. In X-ray image for clinical diagnosis, the size of the imaging region taken by one shot is limited due to the field-of-view of the equipment. Therefore, in order to obtain a high-resolution image including large regions such as a whole body, the synthesis of multiple X-ray images is required. In this paper, we propose a rapid stitching method of digital X-ray images using template-based registration. The proposed algorithm use principal component analysis(PCA) and k-nearest neighborhood(k-NN) to determine the location of input images before performing a template-based matching. After detecting the overlapping position using template-based matching, we synthesize input images by alpha blending. To improve the computational efficiency, reduced images are used for PCA and k-NN analysis. Experimental results showed that our method was more accurate comparing with the previous method with the improvement of the registration speed. Our stitching method could be usefully applied into the stitching of 2D or 3D multiple images.

Algorithm for Fabricating 3D Breast Implants by Using MRI and 3D Scan Data (MRI와 3D 스캔 데이터를 이용한 3D 프린팅 유방 인공보형물의 제작 알고리즘)

  • Jeong, Young Jin;Choi, Dong Hun;Kim, Ku-Jin
    • Journal of Korea Multimedia Society
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    • v.22 no.12
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    • pp.1385-1395
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    • 2019
  • In this paper, we propose a method to fabricate a patient-specific breast implant using MRI images and 3D scan data. Existing breast implants for breast reconstruction surgery are primarily fabricated products for shaping, and among the limited types of implants, products similar to the patient's breast have been used. In fact, the larger the difference between the shape of the breast and the implant, the more frequent the postoperative side effects and the lower the satisfaction. Previous researches on the fabrication of patient-specific breast implants have used limited information based on only MRI images or on only 3D scan data. In this paper, we propose an algorithm for the fabrication of patient-specific breast implants that combines MRI images with 3D scan data, considering anatomical suitability for external shape, volume, and pectoral muscle. Experimental results show that we can produce precise breast implants using the proposed algorithm.

Analysis of Skin Movements with Respect to Bone Motions using MR Images

  • Ryu, Jae-Hun;Miyata, Natsuki;Kouchi, Makiko;Mochimaru, Masaaki;Lee, Kwan H.
    • International Journal of CAD/CAM
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    • v.3 no.1_2
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    • pp.61-66
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    • 2003
  • This paper describes a novel experiment that measures skin movement with respect to the flexional motion of a hand. The study was based on MR images in conjunction with CAD techniques. The MR images of the hand were captured in 3 different postures with surface markers. The surface markers attached to the skin where employed to trace skin movement during the flexional motion of the hand. After reconstructing 3D isosurfaces from the segmented MR images, the global registration was applied to the 3D models based on the particular bone shape of different postures. Skin movement was interpreted by measuring the centers of the surface markers in the registered models.

Multi-modality MEdical Image Registration based on Moment Information and Surface Distance (모멘트 정보와 표면거리 기반 다중 모달리티 의료영상 정합)

  • 최유주;김민정;박지영;윤현주;정명진;홍승봉;김명희
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.3_4
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    • pp.224-238
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    • 2004
  • Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

VALIDITY OF SUPERIMPOSITION RANGE AT 3-DIMENSIONAL FACIAL IMAGES (안면 입체영상 중첩시 중첩 기준 범위 설정에 따른 적합도 차이)

  • Choi, Hak-Hee;Cho, Jin-Hyoung;Park, Hong-Ju;Oh, Hee-Kyun;Choi, Jin-Hugh;Hwang, Hyeon-Shik;Lee, Ki-Heon
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.31 no.2
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    • pp.149-157
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    • 2009
  • Purpose: This study was to evaluate the validity of superimposition range at facial images constructed with 3-dimensional (3D) surface laser scanning system. Materials and methods: For the present study, thirty adults, who had no severe skeletal discrepancy, were selected and scanned twice by a 3D laser scanner (VIVID 910, Minolta, Tokyo, Japan) with 12 markers placed on the face. Then, two 3D facial images (T1-baseline, T2-30 minutes later) were reconstructed respectably and superimposed in several manners with $RapidForm^{TM}2006$ (Inus, Seoul, Korea) software program. The distances between markers at the same place of face were measured in superimposed 3D facial images and measurement were done all the 12 makers respectably. Results: The average linear distances between the markers at the same place in the superimposed image constructed by upper 2/3 of the face was $0.92{\pm}0.23\;mm$, in the superimposed image constructed by upper 1/2 of the face was $0.98{\pm}0.26\;mm$, in the superimposed image constructed by upper 1/3 of the face and nose area was $0.99{\pm}0.24\;mm$, in the superimposed image constructed by upper 1/3 of the face was $1.41{\pm}0.48\;mm$, and in the superimposed image constructed by whole face was $0.83{\pm}0.13\;mm$. There were no statistically significant differences in the liner distances of the makers placed on the area included in superimposition range used for partial registration methods but there were significant differences in the linear distances of the markers placed on the areas not included in superimposition range between whole registration method and partial registration methods used in this study. Conclusion: The results of the present study suggest that the validity of superimposition is decreased as superimposition range is reduced in the superimposition of 3D images constructed with 3D laser scanner for the same subject.

Localization of Unmanned Ground Vehicle based on Matching of Ortho-edge Images of 3D Range Data and DSM (3차원 거리정보와 DSM의 정사윤곽선 영상 정합을 이용한 무인이동로봇의 위치인식)

  • Park, Soon-Yong;Choi, Sung-In
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.43-54
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    • 2012
  • This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

4-Dimensional dose evaluation using deformable image registration in respiratory gated radiotherapy for lung cancer (폐암의 호흡동조방사선치료 시 변형영상정합을 이용한 4차원 선량평가)

  • Um, Ki Cheon;Yoo, Soon Mi;Yoon, In Ha;Back, Geum Mun
    • The Journal of Korean Society for Radiation Therapy
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    • v.30 no.1_2
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    • pp.83-95
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    • 2018
  • Purpose : After planning the Respiratory Gated Radiotherapy for Lung cancer, the movement and volume change of sparing normal structures nearby target are not often considered during dose evaluation. This study carried out 4-D dose evaluation which reflects the movement of normal structures at certain phase of Respiratory Gated Radiotherapy, by using Deformable Image Registration that is well used for Adaptive Radiotherapy. Moreover, the study discussed the need of analysis and established some recommendations, regarding the normal structures's movement and volume change due to Patient's breathing pattern during evaluation of treatment plans. Materials and methods : The subjects were taken from 10 lung cancer patients who received Respiratory Gated Radiotherapy. Using Eclipse(Ver 13.6 Varian, USA), the structures seen in the top phase of CT image was equally set via Propagation or Segmentation Wizard menu, and the structure's movement and volume were analyzed by Center-to Center method. Also, image from each phase and the dose distribution were deformed into top phase CT image, for 4-dimensional dose evaluation, via VELOCITY Program. Also, Using $QUASAR^{TM}$ Phantom(Modus Medical Devices) and $GAFCHROMIC^{TM}$ EBT3 Film(Ashland, USA), verification carried out 4-D dose distribution for 4-D gamma pass rate. Result : The movement of the Inspiration and expiration phase was the most significant in axial direction of right lung, as $0.989{\pm}0.34cm$, and was the least significant in lateral direction of spinal cord, as -0.001 cm. The volume of right lung showed the greatest rate of change as 33.5 %. The maximal and minimal difference in PTV Conformity Index and Homogeneity Index between 3-dimensional dose evaluation and 4-dimensional dose evaluation, was 0.076, 0.021 and 0.011, 0.0 respectfully. The difference of 0.0045~2.76 % was determined in normal structures, using 4-D dose evaluation. 4-D gamma pass rate of every patients passed reference of 95 % gamma pass rate. Conclusion : PTV Conformity Index was more significant in all patients using 4-D dose evaluation, but no significant difference was observed between two dose evaluations for Homogeneity Index. 4-D dose distribution was shown more homogeneous dose compared to 3D dose distribution, by considering the movement from breathing which helps to fill out the PTV margin area. There was difference of 0.004~2.76 % in 4D evaluation of normal structure, and there was significant difference between two evaluation methods in all normal structures, except spinal cord. This study shows that normal structures could be underestimated by 3-D dose evaluation. Therefore, 4-D dose evaluation with Deformable Image Registration will be considered when the dose change is expected in normal structures due to patient's breathing pattern. 4-D dose evaluation with Deformable Image Registration is considered to be a more realistic dose evaluation method by reflecting the movement of normal structures from patient's breathing pattern.

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Robust Watermarking Algorithm for 3D Mesh Models (3차원 메쉬 모델을 위한 강인한 워터마킹 기법)

  • 송한새;조남익;김종원
    • Journal of Broadcast Engineering
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    • v.9 no.1
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    • pp.64-73
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    • 2004
  • A robust watermarking algorithm is proposed for 3D mesh models. Watermark is inserted into the 2D image which is extracted from the target 3D model. Each Pixel value of the extracted 2D image represents a distance from the predefined reference points to the face of the given 3D model. This extracted image is defined as “range image” in this paper. Watermark is embedded into the range image. Then, watermarked 3D mesh is obtained by modifying vertices using the watermarked range Image. In extraction procedure, the original model is needed. After registration between the original and the watermarked models, two range images are extracted from each 3D model. From these images. embedded watermark is extracted. Experimental results show that the proposed algorithm is robust against the attacks such as rotation, translation, uniform scaling, mesh simplification, AWGN and quantization of vertex coordinates.

Respiratory Motion Correction on PET Images Based on 3D Convolutional Neural Network

  • Hou, Yibo;He, Jianfeng;She, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.7
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    • pp.2191-2208
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    • 2022
  • Motion blur in PET (Positron emission tomography) images induced by respiratory motion will reduce the quality of imaging. Although exiting methods have positive performance for respiratory motion correction in medical practice, there are still many aspects that can be improved. In this paper, an improved 3D unsupervised framework, Res-Voxel based on U-Net network was proposed for the motion correction. The Res-Voxel with multiple residual structure may improve the ability of predicting deformation field, and use a smaller convolution kernel to reduce the parameters of the model and decrease the amount of computation required. The proposed is tested on the simulated PET imaging data and the clinical data. Experimental results demonstrate that the proposed achieved Dice indices 93.81%, 81.75% and 75.10% on the simulated geometric phantom data, voxel phantom data and the clinical data respectively. It is demonstrated that the proposed method can improve the registration and correction performance of PET image.

Fast Structure Recovery and Integration using Scaled Orthographic Factorization (개선된 직교분해기법을 사용한 구조의 빠른 복원 및 융합)

  • Yoon, Jong-Hyun;Park, Jong-Seung;Lee, Sang-Rak;Noh, Sung-Ryul
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.486-492
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    • 2006
  • 본 논문에서는 비디오에서의 특징점 추적을 통해 얻은 2D 좌표를 이용한 3D 구조를 추정하는 방법과 네 점 이상의 공통점을 이용한 융합 방법을 제안한다. 영상의 각 프레임에서 공통되는 특징점을 이용하여 형상을 추정한다. 영상의 각 프레임에 대한 특징점의 추적은 Lucas-Kanade 방법을 사용하였다. 3D 좌표 추정 방법으로 개선된 직교분해기법을 사용하였다. 개선된 직교분해기법에서는 3D 좌표를 복원함과 동시에 카메라의 위치와 방향을 계산할 수 있다. 복원된 부분 데이터들은 전체를 이루는 일부분이므로, 융합을 통해 완성된 모습을 만들 수 있다. 복원된 부분 데이터들의 서로 다른 좌표계를 기준 좌표계로 변환함으로써 융합할 수 있다. 융합은 카메라의 모션에 해당하는 카메라의 위치와 방향에 의존된다. 융합 과정은 모두 선형으로 평균 0.5초 이하의 수행 속도를 보이며 융합의 오차는 평균 0.1cm 이하의 오차를 보였다.

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