• 한국측량학회:학술대회논문집
• /
• 한국측량학회 2007년도 춘계학술발표회 논문집
• /
• pp.463-466
• /
• 2007

In this study, 3D building reconstruction and road design were performed using LiDAR data, digital map and airborne digital image. Information for tourism was extracted from digital maps (scale: 1/5,000) of Jeju Island, and then route of the road was determined for road design. Reconstructed buildings, aerial image and designed road were overlayed with tourism information for 3D simulation. In addition, landscape analysis was performed and result of the road design was visualized.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.150-152
• /
• 2003

Laser scanned lidar data record 3D surface information in detail. Exploring valuable spatial information from lidar data is a prerequisite task for its applications, such as DEM generation and 3D building model reconstruction. However, the inherent spatial information is implicit in the abundant, densely and randomly distributed point cloud. This paper proposes a novel method to organize point cloud data, so that further analysis or feature extraction can proceed based on a well organized data model. The principle of the proposed algorithm is to segment point cloud into 3D planes. A split and merge segmentation based on the octree structure is developed for the implementation. Some practical airborne and ground lidar data are tested for demonstration and discussion. We expect this data organization could provide a stepping stone for extracting spatial information from lidar data.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2015년도 춘계학술발표대회
• /
• pp.896-897
• /
• 2015

본 연구는 3D 이미지 스캔 데이터 기반으로, SWEEPING 형상을 효과적으로 역설계하는 기술에 관한 것이다. 사용자가 미리 정의한 형상 단면 모델 데이터베이스를 이용해, 3차원 SWEEPING 형상을 자동으로 역설계하는 알고리즘을 제안한다. 이를 위해, 3D 이미지 스캔 데이터인 포인트 클라우드에서 자동으로 추출한 단면 포인트들을 처리해, 파라메터 정보를 추출하고, 미리 정의된 형상 단면들과 상호간 유사도를 비교한 후, 가장 유사한 형상 단면을 획득한다. 이러한 기술은 SWEEPING 형상 모델의 역설계 과정을 자동화하는 데 도움을 줄 것이다.

• Archives of Plastic Surgery
• /
• 제47권5호
• /
• pp.428-434
• /
• 2020

Background Three-dimensional (3D) model printing improves visualization of anatomical structures in space compared to two-dimensional (2D) data and creates an exact model of the surgical site that can be used for reference during surgery. There is limited evidence on the effects of using 3D models in microsurgical reconstruction on improving clinical outcomes. Methods A retrospective review of patients undergoing reconstructive breast microsurgery procedures from 2017 to 2019 who received computed tomography angiography (CTA) scans only or with 3D models for preoperative surgical planning were performed. Preoperative decision-making to undergo a deep inferior epigastric perforator (DIEP) versus muscle-sparing transverse rectus abdominis myocutaneous (MS-TRAM) flap, as well as whether the decision changed during flap harvest and postoperative complications were tracked based on the preoperative imaging used. In addition, we describe three example cases showing direct application of 3D mold as an accurate model to guide intraoperative dissection in complex microsurgical reconstruction. Results Fifty-eight abdominal-based breast free-flaps performed using conventional CTA were compared with a matched cohort of 58 breast free-flaps performed with 3D model print. There was no flap loss in either group. There was a significant reduction in flap harvest time with use of 3D model (CTA vs. 3D, 117.7±14.2 minutes vs. 109.8±11.6 minutes; P=0.001). In addition, there was no change in preoperative decision on type of flap harvested in all cases in 3D print group (0%), compared with 24.1% change in conventional CTA group. Conclusions Use of 3D print model improves accuracy of preoperative planning and reduces flap harvest time with similar postoperative complications in complex microsurgical reconstruction.

• Imaging Science in Dentistry
• /
• 제50권4호
• /
• pp.331-337
• /
• 2020

Purpose: As cone-beam computed tomography (CBCT) has become the most widely used 3-dimensional (3D) imaging modality in the dental field, storage space and costs for large-capacity data have become an important issue. Therefore, if 3D data can be stored at a clinically acceptable compression rate, the burden in terms of storage space and cost can be reduced and data can be managed more efficiently. In this study, a deep learning network for super-resolution was tested to restore compressed virtual CBCT images. Materials and Methods: Virtual CBCT image data were created with a publicly available online dataset (CQ500) of multidetector computed tomography images using CBCT reconstruction software (TIGRE). A very deep super-resolution (VDSR) network was trained to restore high-resolution virtual CBCT images from the low-resolution virtual CBCT images. Results: The images reconstructed by VDSR showed better image quality than bicubic interpolation in restored images at various scale ratios. The highest scale ratio with clinically acceptable reconstruction accuracy using VDSR was 2.1. Conclusion: VDSR showed promising restoration accuracy in this study. In the future, it will be necessary to experiment with new deep learning algorithms and large-scale data for clinical application of this technology.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• 제23권3호
• /
• pp.203-210
• /
• 2019

We present the three-dimensional volume reconstruction model using the modified Cahn-Hilliard equation with a fractional Laplacian. From two-dimensional cross section images such as computed tomography, magnetic resonance imaging slice data, we suggest an algorithm to reconstruct three-dimensional volume surface. By using Laplacian operator with the fractional one, the dynamics is changed to the macroscopic limit of Levy process. We initialize between the two cross section with linear interpolation and then smooth and reconstruct the surface by solving modified Cahn-Hilliard equation. We perform various numerical experiments to compare with the previous research.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2007년도 추계학술발표대회
• /
• pp.101-103
• /
• 2007

혈관 구조는 사람의 가장 복잡한 구조 중 하나이다. 혈관 분석에는 Morphology and Topology 가 있다. 우리는 목표는 위 분석 기법과는 달리 3D 영상 재구성이다. 본 논문은 Raw CT data 을 세그먼트하고 Skeleton line 을 인용하여 복잡한 트리 형태의 혈관 3D 재구성을 하였다.

• 한국멀티미디어학회논문지
• /
• 제22권12호
• /
• pp.1385-1395
• /
• 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.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제4권4호
• /
• pp.187-194
• /
• 2015

본 논문에서는 RGB-D 입력 영상들로부터 3차원 공간을 움직이는 카메라의 실시간 포즈를 효과적으로 추적할 수 있는 시각 주행 거리측정기를 제안한다. 본 논문에서 제안하는 시각 주행 거리 측정기에서는 컬러 영상과 깊이 영상의 풍부한 정보를 충분히 활용하면서도 실시간 계산량을 줄이기 위해, 특징 기반의 저밀도 주행 거리 계산 방법을 사용한다. 본 시스템에서는 보다 정확한 주행 거리 추정치를 얻기 위해, 카메라 이동 이전과 이동 이후의 영상에서 추출한 특징들을 정합한 뒤, 정합된 특징들에 대한 추가적인 정상 집합 정제 과정과 주행 거리 정제 작업을 반복한다. 또한, 정제 후 잔여 정상 집합의 크기가 충분치 않은 경우에도 잔여 정상 집합의 크기에 비례해 최종 주행 거리를 결정함으로써, 추적 성공률을 크게 향상시켰다. TUM 대학의 벤치마크 데이터 집합을 이용한 실험과 3차원 장면 복원 응용 시스템의 구현을 통해, 본 논문에서 제안하는 시각 주행 거리 측정 방법의 높은 성능을 확인할 수 있었다.

• IEIE Transactions on Smart Processing and Computing
• /
• 제5권4호
• /
• pp.294-301
• /
• 2016

In this paper, we present methods to efficiently parallelize iterative 3D image reconstruction by exploiting trigeneous devices (three different types of device) at the same time: a CPU, an integrated GPU, and a discrete GPU. We first present a technique that exploits single instruction multiple data (SIMD) architectures in GPUs. Then, we propose a performance estimation model, based on which we can easily find the optimal data partitioning on trigeneous devices. We found that the performance significantly varies by up to 6.23 times, depending on how SIMD units in GPUs are accessed. Then, by using trigeneous devices and the proposed estimation models, we achieve optimal partitioning and throughput, which corresponds to a 9.4% further improvement, compared to discrete GPU-only execution.