• Title/Summary/Keyword: 3D model reconstruction

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3D building modeling from airborne Lidar data by building model regularization (건물모델 정규화를 적용한 항공라이다의 3차원 건물 모델링)

  • Lee, Jeong Ho;Ga, Chill Ol;Kim, Yong Il;Lee, Byung Gil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.4
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    • pp.353-362
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    • 2012
  • 3D building modeling from airborne Lidar without model regularization may cause positional errors or topological inconsistency in building models. Regularization of 3D building models, on the other hand, restricts the types of models which can be reconstructed. To resolve these issues, this paper modelled 3D buildings from airborne Lidar by building model regularization which considers more various types of buildings. Building points are first segmented into roof planes by clustering in feature space and segmentation in object space. Then, 3D building models are reconstructed by consecutive adjustment of planes, lines, and points to satisfy parallelism, symmetry, and consistency between model components. The experimental results demonstrated that the method could make more various types of 3d building models with regularity. The effects of regularization on the positional accuracies of models were also analyzed quantitatively.

The effect of fixation plate use on bone healing during the reconstruction of mandibular defects

  • Hong, Khang Do Gia;Kim, Seong-Gon;Park, Young-Wook
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.45 no.5
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    • pp.276-284
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    • 2019
  • Objectives: This study sought to compare efficiency results between the use of a customized implant (CI) and a reconstruction plate (RP) in mandibular defect reconstruction in an animal model. Materials and Methods: Fifteen rabbits underwent surgery to create a defect in the right side of the mandible and were randomly divided into two groups. For reconstruction of the mandibular defect, the RP group (n=5) received five-hole mini-plates without bone grafting and the CI group (n=10) received fabricated CIs based on the cone-beam computed tomography (CBCT) data taken preoperatively. The CI group was further divided into two subgroups depending on the time of CBCT performance preoperatively, as follows: a six-week CI (6WCI) group (n=5) and a one-week CI (1WCI) group (n=5). Daily food intake amount (DFIA) was measured to assess the recovery rate. Radiographic images were acquired to evaluate screw quantity. CBCT and histological examination were performed in the CI subgroup after sacrifice. Results: The 1WCI group showed the highest value in peak average recovery rate and the fastest average recovery rate. In terms of reaching a 50% recovery rate, the 1WCI group required the least number of days as compared with the other groups ($2.6{\pm}1.3days$), while the RP group required the least number of days to reach an 80% recovery rate ($7.8{\pm}2.2days$). The 1WCI group showed the highest percentage of intact screws (94.3%). New bone formation was observed in the CI group during histological examination. Conclusion: Rabbits with mandibular defects treated with CI showed higher and faster recovery rates and more favorable screw status as compared with those treated with a five-hole mini-plate without bone graft.

Automatic Local Update of Triangular Mesh Models Based on Measurement Point Clouds (측정된 점데이터 기반 삼각형망 곡면 메쉬 모델의 국부적 자동 수정)

  • Woo, Hyuck-Je;Lee, Jong-Dae;Lee, Kwan-H.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.5
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    • pp.335-343
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    • 2006
  • Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

Influence of threshold value of computed tomography on the accuracy of 3-dimensional medical model (전산화단층 촬영상의 임계치가 3차원 의학모델 정확도에 미치는 영향에 대한 연구)

  • Lee Byeong-Do;Lee Wan
    • Imaging Science in Dentistry
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    • v.32 no.1
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    • pp.27-33
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    • 2002
  • Purpose: To evaluate the influence of threshold value of computed tomography on the accuracy of rapid prototyping (RP) medical model Material and Methods : CT datas of a human dry skull were transferred from CT scanner via compact disk to a personal computer (PC). 3-dimensional image reconstruction on PC by V-works/sup TM/ 3.0 (CyberMed. Inc.) software and RP models fabrication were followed. 2-RP models were produced by threshold value of 500 and 800 selected in surface rendering process. Linear measurements between arbitrary 12 anatomical landmarks on dry skull, 3-D image model, and 2-RP models were done and compared. Thus, the accuracy of 500 RP and 800RP models was respectively evaluated. Results: There was mean difference (% difference) in absolute value of 2.27 mm (2.73%) between linear measurements of dry skull and 500 RP model. There was mean difference (% difference) in absolute value of 1.94 mm (2.52%) between linear measurements of dry skull and 800 RP model. Conclusion: Slight difference of threshold value in rendering process of 3-D modelling made a influence on the accuracy of RP medical model.

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A Digital Bathymetric Model combining Multi Beam Echo Sounder and Sidescan Sonar

  • Park, Jo-Seph;Kim, Hik-Il
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.330-330
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    • 2002
  • The combination of Multi-Beam Echo Sounder swath bathymetry and high-resolution towed Sidescan sonar provides a powerful method of examination about hydrographic survey results. In this paper, we investigate the fast method of 3D bathymetric reconstruction with the Digital Sidescan sonar(Benthos SIS 1500) and Shallow Multi-Beam Echo Sounder(Reson Seabat 8125). The Seabat 8125 is a 455KHz high resolution focused Multibeam echo sounder(MBES) system which measures the relative water depth across a wide swath perpendicular to a vessel's track. The Benthos SIS1500 is a chirp(nominal fq. 200KHz) sonar which map the topographical features & sediment texture of ocean bottom using backscattered amplitude. We generates the very large 3D bathymetric texture mapping model with the Helical System's HHViewer and describes additional benefits of combining MBES and Sidescan Sonar imagery, the removal of geometric distortions in the model and a deterministic sounding noise.

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A 3D Face Reconstruction and Tracking Method using the Estimated Depth Information (얼굴 깊이 추정을 이용한 3차원 얼굴 생성 및 추적 방법)

  • Ju, Myung-Ho;Kang, Hang-Bong
    • The KIPS Transactions:PartB
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    • v.18B no.1
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    • pp.21-28
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    • 2011
  • A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

Single Image-Based 3D Tree and Growth Models Reconstruction

  • Kim, Jaehwan;Jeong, Il-Kwon
    • ETRI Journal
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    • v.36 no.3
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    • pp.450-459
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    • 2014
  • In this paper, we present a new, easy-to-generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton-based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider tree-growing attributes, such as branching orders, branch width, tree size, and branch self-bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local self-similarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease.

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

  • Chenggong Yan;Jie Lin;Haixia Li;Jun Xu;Tianjing Zhang;Hao Chen;Henry C. Woodruff;Guangyao Wu;Siqi Zhang;Yikai Xu;Philippe Lambin
    • Korean Journal of Radiology
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    • v.22 no.6
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    • pp.983-993
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    • 2021
  • Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

Composite Endoscope Image Construction based on Massive Inner Intestine Photos (다량의 내장 사진에 의한 화상 구성)

  • Kim, Eun-Joung;Yoo, Kwan-Hee;Yoo, Young-Gap
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.1
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    • pp.108-114
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    • 2007
  • This paper presented an image reconstruction method based on the original capsule endoscopy photos yielding a 2-D image for faster diagnosis proposes. The proposed method constructed a 3-D intestine model using the massive images obtained from the capsule endoscope. It merged all images and completed a 3-D model of an intestine. This 3-D model was reformed as a 2-D plane image showing the inner side of the entire intestine. The proposed image composition was evaluated by the 3-D simulator, OpenGL. This approach was demonstrated successfully. A physician can find the location of a disease at a glance because the composite image provided an easy-to-understand view to show the patient's intestine and thereby shorten diagnosis time.

Generation Method of 3D Human Body Level-of-Detail Model for Virtual Reality Device using Tomographic Image (가상현실 장비를 위한 단층 촬영 영상 기반 3차원 인체 상세단계 모델 생성 기법)

  • Wi, Woochan;Heo, Yeonjin;Lee, Seongjun;Kim, Jion;Shin, Byeong-Seok;Kwon, Koojoo
    • The Journal of Korean Institute of Next Generation Computing
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    • v.15 no.4
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    • pp.40-50
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    • 2019
  • In recent years, it is important to visualize an accurate human body model for the low-end system in the medical imaging field where augmented reality technology and virtual reality technology are used. Decreasing the geometry of a model causes a difference from the original shape and considers the difference as an error. So, the error should be minimized while reducing geometry. In this study, the organ areas of a human body in the tomographic images such as CT or MRI is segmented and 3D geometric model is generated, thereby implementing the reconstruction method of multiple resolution level-of-detail model. In the experiment, a virtual reality platform was constructed to verify the shape of the reconstructed model, targeting the spine area. The 3D human body model and patient information can be verified using the virtual reality platform.