• 제목/요약/키워드: quantitative reconstruction

검색결과 203건 처리시간 0.026초

Quantitative Application of TM Data in Shallow Geological Structure Reconstruction

  • Yang, Liu;Liqun, Zou;Mingxin, Liu
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1313-1315
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    • 2003
  • This paper is dedicated to studying the quantitative analysis method with remote-sensing data in shallow geological structure reconstruction by the example of TM data in western China. A new method of computing attitude of geological contacts from remote-sensing data is developed and assessed. We generate several geological profiles with remotely derived measurements to constrain the shallow geological structure reconstruction in three dimensions.

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Biomedical Applications of Stereoscopy for Three-Dimensional Surface Reconstruction in Scanning Electron Microscopes

  • Kim, Ki Woo
    • Applied Microscopy
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    • 제46권2호
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    • pp.71-75
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    • 2016
  • The scanning electron microscope (SEM) offers two-dimensional (2D) micrographs of three-dimensional (3D) objects due to its inherent operating mechanisms. To overcome this limitation, other devices have been used for quantitative morphological analysis. Many efforts have been made on the applications of software-based approaches to 3D reconstruction and measurements by SEM. Based on the acquisition of two stereo images, a multi-view technique consists of two parts: (i) geometric calibration and (ii) image matching. Quantitative morphological parameters such as height and depth could be nondestructively measured by SEM combined with special software programs. It is also possible to obtain conventional surface parameters such as roughness and volume of biomedical specimens through 3D SEM surface reconstruction. There is growing evidence that conventional 2D SEM without special electron detectors can be transformed to 3D SEM for quantitative measurements in biomedical research.

Quantitative Analysis of Bayesian SPECT Reconstruction : Effects of Using Higher-Order Gibbs Priors

  • S. J. Lee
    • 대한의용생체공학회:의공학회지
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    • 제19권2호
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    • pp.133-142
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    • 1998
  • Bayesian SPECT 영상재구성에 있어서 정교한 형태의 사전정보를 사용할 경우 bias 및 variance와 같은 통계적 차원에서의 정량적 성능을 향상시킬 수 있다. 특히, "thin plate" 와 같은 고차의 smoothing 사전정보는 "membrane"과 같은 일반적인 다른 사전 정보에 비해 bias를 개선시키는 것으로 알려져 있다. 그러나, 이와 같은 장점은 영상재구성 알고리즘에 내재하는 hyperparameters의 값을 최적으로 선택하였을 경우에만 적용된다. 본 연구에서는 thin plate와 membrane의 두가지 대표적인 사전정보를 포함하는 영상재구성 알고리즘의 정량적 성능에 대해 집중 고찰한다. 즉, 알고리즘에 내재하는 hyperparameters 가 통계적 차원에서 bias와 variance에 어떠한 영향을 미치는지 관찰한다. 실험에서 Monte Carlo noise trials를 사용하여 bias와 variance를 계산하며, 각 결과를 ML-EM 및 filtered backprojection으로부터 얻어진 bias 및 variance와 비교한다. 결론적으로 thin plate와 같은 고차의 사전정보는 hyperparameters의 선택에 민감하지 않으며, hyperparameters 값의 전 범위에 걸쳐 bias를 개선시킴을 보인다. 걸쳐 bias를 개선시킴을 보인다.

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유방 MRI의 최대강도투사 기법에 의한 3차원 재구성 영상의 유용성 (The Value of Three-Dimensional Reconstructions of MRI Imaging using Maximum Intensity Projection Technique)

  • 조재환;이해각;홍인식;김현주;장현철;박철수;박태남
    • 디지털콘텐츠학회 논문지
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    • 제12권2호
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    • pp.157-164
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    • 2011
  • 유방암중 관상피내암으로 진단 받은 환자를 대상으로 조영제 주입전, 후의 감산된 영상과 3차원 재구성된 영상을 정량적으로 비교 분석하여 재구성된 영상의 효과와 유용성을 고찰 해보고자 한다. 조직학적으로 관상피 내암으로 진단 받은 환자 20명을 대상으로 3.0T MR scanner를 이용하여 감산된 영상과 3차원 재구성한 영상을 획득하였다. 분석 결과 감산 영상과 재구성한 영상에서 신호대 잡음비는 병변, 유관조직, 지방조직에서 재구성한 영상에서 높은 신호대 잡음비를 보였으며 두 영상에서의 대조 도대 잡음비는 차이를 보이지 않았다.

Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction

  • June Park;Jaeseung Shin;In Kyung Min;Heejin Bae;Yeo-Eun Kim;Yong Eun Chung
    • Korean Journal of Radiology
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    • 제23권4호
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    • pp.402-412
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    • 2022
  • Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

Hann 필터의 Cut-off 주파수 변화에 따른 CT 영상의 Artifact 제거효과에 대한 정량적 평가 (Quantitative Evaluation of CT Artifact Elimination with various Cut-off Frequency of Hann Filter)

  • 강보선
    • 한국방사선학회논문지
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    • 제2권3호
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    • pp.5-9
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    • 2008
  • 전산화단층촬영(CT)에 있어서 생기는 artifact를 제거하기 위해서 영상재구성 과정에 다양한 필터를 사용하고 있다. 이러한 artifact는 영상재구성 과정에 사용되는 수학적 오차와, 투영이미지와 실제 해부학적 구조간의 오차, 혹은 데이터 획득과정에서의 오차 등으로 인해 필연적으로 생길 수 밖에 없다. 본 연구에서는 Hann필터를 사용하였을 때 CT 영상에서의 artifact 제거효과를 정량적으로 분석하였다. Cut-off 주파수가 0.1인 경우에서 0.2씩 증가시키며 0.9까지에 대한 다양한 cut-off 주파수의 Hann필터에 대한 artifact제거 효과에 대한 결과를 보였다. 재구성 영상에서의 artifact에 대한 정량적 분석을 위해서 white image에 대한 CT 영상의 Noise Power Spectrum을 비교하였다.

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Tomographic Reconstruction of a Three-Dimensional Flow Field with Limited Interferometric Data

  • Cha, Dong-Jin
    • International Journal of Air-Conditioning and Refrigeration
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    • 제8권2호
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    • pp.11-22
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    • 2000
  • Holographic interferometric tomography can provide reconstruction of instantaneous three-dimensional gross flow fields. The technique however confronts ill-posed reconstruction problems in practical applications. Experimental data are usually limited in projection and angular scanning when a field is captured instantaneously or under the obstruction of test models and test section enclosures. An algorithm, based on a series expansion method, has been developed to improve the reconstruction under the ill-posed conditions. A three-dimensional natural convection flow around two interacting isothermal cubes is experimentally investigated. The flow can provide a challenging reconstruction problem and lend itself to accurate numerical solution for comparison. The refractive index fields at two horizontal sections of the thermal plume with and without an opaque object are reconstructed at a limited view angle of 80$\circ$. The experimental reconstructions are then compared with those from numerical calculation and thermocouple thermometry. It confirms that the technique is applicable to reconstruction of reasonably complex, three-dimensional flow fields.

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A Spline-Regularized Sinogram Smoothing Method for Filtered Backprojection Tomographic Reconstruction

  • Lee, S.J.;Kim, H.S.
    • 대한의용생체공학회:의공학회지
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    • 제22권4호
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    • pp.311-319
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    • 2001
  • Statistical reconstruction methods in the context of a Bayesian framework have played an important role in emission tomography since they allow to incorporate a priori information into the reconstruction algorithm. Given the ill-posed nature of tomographic inversion and the poor quality of projection data, the Bayesian approach uses regularizers to stabilize solutions by incorporating suitable prior models. In this work we show that, while the quantitative performance of the standard filtered backprojection (FBP) algorithm is not as good as that of Bayesian methods, the application of spline-regularized smoothing to the sinogram space can make the FBP algorithm improve its performance by inheriting the advantages of using the spline priors in Bayesian methods. We first show how to implement the spline-regularized smoothing filter by deriving mathematical relationship between the regularization and the lowpass filtering. We then compare quantitative performance of our new FBP algorithms using the quantitation of bias/variance and the total squared error (TSE) measured over noise trials. Our numerical results show that the second-order spline filter applied to FBP yields the best results in terms of TSE among the three different spline orders considered in our experiments.

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스테레오 정합을 이용한 3차원 재구성 과정의 정량적 평가 (Quantitative Assessment of 3D Reconstruction Procedure Using Stereo Matching)

  • 우동민
    • 전기전자학회논문지
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    • 제17권1호
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    • pp.1-9
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    • 2013
  • 3차원 영상 해석 기법에 의해 구해진 DEM(Digital Elevation Map)을 정량적으로 평가하는 것은 영상 해석 기법의 유효성을 검증하기 위해 매우 중요하다. 본 논문에서는 모의 영상 제작에 의한 3차원 재구성 과정의 새로운 정량적 평가 방법을 제안하였다. 제안된 방법은 미리 확보된 DEM과 정사영상(ortho-image)을 가상의 실제 값(pseudo ground truth)으로 가정한 것에 의한 것이다. 제안된 방법의 과정은 그래픽스에서 사용되는 ray tracing 알고리즘을 구성하여 가상의 실제 값에 적용함으로서 원하는 시점으로부터의 한 쌍의 모의 영상을 제작하는 것으로부터 시작된다. 제작된 모의 영상 쌍으로부터 구해진 DEM을 가상의 실제 값과 비교하면 구해진 DEM의 정량적인 오차 분석이 가능하여, 적용된 3차원 영상 해석 기법의 유효성이 평가될 수 있다. 제안된 평가 방법의 타당성을 검증하기 위해, 정량적 및 정성적인 실험이 수행되었다. 이를 위해 발생되는 모의 영상이 실제 형상을 재현하는 정도를 정량적인 수치로서 구하여 제안된 방법을 타당성을 입증하였다. 또한 정합창의 크기 변화에 따른 DEM의 정확도를 제안된 평가 방법에 의해 실험하였다. 이러한 실험 결과가 예견된 결과와 일치함에 의해 제안된 평가 방법의 타당성을 정성적으로도 명백히 증명하였다.

Bayesian Tomographic 재구성에 있어서 Gibbs Smoothing Priors의 효과에 대한 비교연구 (A Comparative Study of the Effects of Gibbs Smoothing Priors in Bayesian Tomographic Reconstruction)

  • 이수진
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 춘계학술대회
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    • pp.279-282
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    • 1997
  • Bayesian reconstruction methods for emission computed tomography have been a topic of interest in recent years, partly because they allow for the introduction of prior information into the reconstruction problem. Early formulations incorporated priors that imposed simple spatial smoothness constraints on the underlying object using Gibbs priors in the form of four-nearest or eight-nearest neighbors. While these types of priors, known as "membrane" priors, are useful as stabilizers in otherwise unstable ML-EM reconstructions, more sophisticated prior models are needed to model underlying source distributions more accurately. In this work, we investigate whether the "thin plate" model has advantages over the simple Gibbs smoothing priors mentioned above. To test and compare quantitative performance of the reconstruction algorithms, we use Monte Carlo noise trials and calculate bias and variance images of reconstruction estimates. The conclusion is that the thin plate prior outperforms the membrane prior in terms of bias and variance.

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