• Title/Summary/Keyword: computational reconstruction

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Lineage Tracing: Computational Reconstruction Goes Beyond the Limit of Imaging

  • Wu, Szu-Hsien (Sam);Lee, Ji-Hyun;Koo, Bon-Kyoung
    • Molecules and Cells
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    • v.42 no.2
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    • pp.104-112
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    • 2019
  • Tracking the fate of individual cells and their progeny through lineage tracing has been widely used to investigate various biological processes including embryonic development, homeostatic tissue turnover, and stem cell function in regeneration and disease. Conventional lineage tracing involves the marking of cells either with dyes or nucleoside analogues or genetic marking with fluorescent and/or colorimetric protein reporters. Both are imaging-based approaches that have played a crucial role in the field of developmental biology as well as adult stem cell biology. However, imaging-based lineage tracing approaches are limited by their scalability and the lack of molecular information underlying fate transitions. Recently, computational biology approaches have been combined with diverse tracing methods to overcome these limitations and so provide high-order scalability and a wealth of molecular information. In this review, we will introduce such novel computational methods, starting from single-cell RNA sequencing-based lineage analysis to DNA barcoding or genetic scar analysis. These novel approaches are complementary to conventional imaging-based approaches and enable us to study the lineage relationships of numerous cell types during vertebrate, and in particular human, development and disease.

Interactive prostate shape reconstruction from 3D TRUS images

  • Furuhata, Tomotake;Song, Inho;Zhang, Hong;Rabin, Yoed;Shimada, Kenji
    • Journal of Computational Design and Engineering
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    • v.1 no.4
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    • pp.272-288
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    • 2014
  • This paper presents a two-step, semi-automated method for reconstructing a three-dimensional (3D) shape of the prostate from a 3D transrectal ultrasound (TRUS) image. While the method has been developed for prostate ultrasound imaging, it can potentially be applicable to any other organ of the body and other imaging modalities. The proposed method takes as input a 3D TRUS image and generates a watertight 3D surface model of the prostate. In the first step, the system lets the user visualize and navigate through the input volumetric image by displaying cross sectional views oriented in arbitrary directions. The user then draws partial/full contours on selected cross sectional views. In the second step, the method automatically generates a watertight 3D surface of the prostate by fitting a deformable spherical template to the set of user-specified contours. Since the method allows the user to select the best cross-sectional directions and draw only clearly recognizable partial or full contours, the user can avoid time-consuming and inaccurate guesswork on where prostate contours are located. By avoiding the usage of noisy, incomprehensible portions of the TRUS image, the proposed method yields more accurate prostate shapes than conventional methods that demand complete cross-sectional contours selected manually, or automatically using an image processing tool. Our experiments confirmed that a 3D watertight surface of the prostate can be generated within five minutes even from a volumetric image with a high level of speckles and shadow noises.

Enhancement of Image Reconstruction Using Region of Interest Method Based on Adaptive Threshold Value in Electrical Impedance Tomography (전기 임피던스 단층촬영법에서 적응 문턱치 기반의 관심영역 기법을 사용한 영상 복원의 개선)

  • Kim, Chang Il;Kim, Bong Seok;Kim, Kyung Youn
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.8
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    • pp.99-106
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    • 2017
  • Electrical impedance tomography is a nondestructive imaging modality in which the internal resistivity distribution is reconstructed based on the injected currents and measured voltages inside a domain of interest. In this paper, an adaptive threshold value based region of interest (ROI) method is proposed to improve the spatial resolution of reconstructed images as well as to reduce the computational time of the inverse problem. Adaptive threshold value is calculated by INTERMODES method and ROI is determined from the domain based on this value. Moreover, the computational domain of image reconstruction is restricted within a ROI and iterative Gauss-Newton method is employed to estimate the resistivity distribution. To evaluate the performance of the proposed method, numerical experiments have been performed and the results are analyzed.

Simplified Factorizing-Technique for Airborne FMCW-SAR Image Reconstruction (항공기 기반 FMCW-SAR 영상복원을 위한 간소화된 분할연산기법)

  • Hwang, Ji-Hwan;Kim, Duk-Jin;Kim, Jin-Woo;Ok, Jae-Woo;Shin, Hee-Sub;You, Eung-Noh
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.28 no.9
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    • pp.723-732
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    • 2017
  • Simplified factorizing-technique to improve the efficiency on computational procedure and the complexity of the conventional back-projection algorithm, which is used to reconstruct airborne FMCW-SAR image, is suggested, and the reconstruction process of SAR image by this simplified factorizing-technique are presented in this paper. This technique can be efficiently applied to airborne FMCW-SAR having a relatively narrow beamwidth and long synthetic aperture length, and its basic rationale is to exclude the data that has low level of contribution during computational procedure. Using the raw data of practical airborne FMCW-SAR system, performances of this proposed technique such as SAR image quality and processing time were compared and analyzed.

Distributed Video Compressive Sensing Reconstruction by Adaptive PCA Sparse Basis and Nonlocal Similarity

  • Wu, Minghu;Zhu, Xiuchang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2851-2865
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    • 2014
  • To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

Visual Quality Enhancement of Three-Dimensional Integral Imaging Reconstruction for Partially Occluded Objects Using Exemplar-Based Image Restoration

  • Zhang, Miao;Zhong, Zhaolong;Piao, Yongri
    • Journal of information and communication convergence engineering
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    • v.14 no.1
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    • pp.57-63
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    • 2016
  • In generally, the resolution of reconstructed three-dimensional images can be seriously degraded by undesired occlusions in the integral imaging system, because the undesired information of the occlusion overlap the three-dimensional images to be reconstructed. To solve the problem of the undesired occlusion, we present an exemplar-based image restoration method in integral imaging system. In the proposed method, a minimum spanning tree-based stereo matching method is used to remove the region of undesired occlusions in each elemental image. After that, the removed occlusion region of each elemental images are re-established by using the exemplar-based image restoration method. For further improve the performance of the image restoration, the structure tensor is used to solve the filling error cause by discontinuous structures. Finally, the resolution enhanced three-dimensional images are reconstructed by using the restored elemental images. The preliminary experiments are presented to demonstrate the feasibility of the proposed method.

Regularized Modified Newton-Raphson Algorithm for Electrical Impedance Tomography Based on the Exponentially Weighted Least Square Criterion (전기 임피던스 단층촬영을 위한 지수적으로 가중된 최소자승법을 이용한 수정된 조정 Newton-Raphson 알고리즘)

  • Kim, Kyung-Youn;Kim, Bong-Seok
    • Journal of IKEEE
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    • v.4 no.2 s.7
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    • pp.249-256
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    • 2000
  • In EIT(electrical impedance tomography), the internal resistivity(or conductivity) distribution of the unknown object is estimated using the boundary voltage data induced by different current patterns using various reconstruction algorithms. In this paper, we present a regularized modified Newton-Raphson(mNR) scheme which employs additional a priori information in the cost functional as soft constraint and the weighting matrices in the cost functional are selected based on the exponentially weighted least square criterion. The computer simulation for the 32 channels synthetic data shows that the reconstruction performance of the proposed scheme is improved compared to that of the conventional regularized mNR at the expense of slightly increased computational burden.

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Spatially Scalable Kronecker Compressive Sensing of Still Images (공간 스케일러블 Kronecker 정지영상 압축 센싱)

  • Nguyen, Canh Thuong;Jeon, Byeungwoo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.10
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    • pp.118-128
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    • 2015
  • Compressive sensing (CS) has to face with two challenges of computational complexity reconstruction and low coding efficiency. As a solution, this paper presents a novel spatially scalable Kronecker two layer compressive sensing framework which facilitates reconstruction up to three spatial resolutions as well as much improved CS coding performance. We propose a dual-resolution sensing matrix based on the quincunx sampling grid which is applied to the base layer. This sensing matrix can provide a fast-preview of low resolution image at encoder side which is utilized for predictive coding. The enhancement layer is encoded as the residual measurement between the acquired measurement and predicted measurement data. The low resolution reconstruction is obtained from the base layer only while the high resolution image is jointly reconstructed using both two layers. Experimental results validate that the proposed scheme outperforms both conventional single layer and previous multi-resolution schemes especially at high bitrate like 2.0 bpp by 5.75dB and 5.05dB PSNR gain on average, respectively.

Multi-spectral Imaging-based Color Image Reconstruction Using the Conventional Bayer CFA (베이어 CFA 카메라를 사용한 다중 스펙트럼 기반 컬러영상 생성 기술)

  • Shin, Jeong-Ho
    • Journal of Broadcast Engineering
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    • v.16 no.3
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    • pp.561-565
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    • 2011
  • This paper presents an imaging system for reconstruction of enhanced color images using the conventional Bayer CFA. By extracting various colors such as RGBCY from two sequential images which consist of a image by broadband G channel lens filter and the other image captured without one, the proposed color image reconstruction system can reduce the computational complexity for demosaicking and make high resolution color information without aliasing artifacts. Because the proposed system uses the common Bayer CFA image sensor, fabricating a new type of CFA is not necessary for obtaining a multi-spectral image, which can be easily extensible for applications of multi-spectral imaging. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing demosaicking methods, the proposed camera system showed the significant improvements in the sense of color resolution.

Fast Implementations of Projector-Backprojector Pairs for Iterative Tomographic Reconstruction (반복법을 사용한 단층영상 재구성을 위한 투사기 및 역투사기의 고속 구현)

  • 김수미;이수진;김용호
    • Journal of Biomedical Engineering Research
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    • v.24 no.5
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    • pp.473-480
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    • 2003
  • Iterative reconstruction methods have played a prominent role in emission computed tomography due to their remarkable advantages over the conventional filtered backprojection method. However, since iterative reconstructions typically are comprised of repeatedly projecting and backprojecting the data, the computational load required for reconstructing an image depends highly on the performance of the projector-backprojector pair used in the algorithm. In this work we compare quantitative performance of representative methods for implementing projector-backprojector pairs. To reduce the overall cost for the projection-backprojection operations for each method, we investigate how previously computed results can be reused so that the number of redundant calculations can be minimized. Our experimental results demonstrate that the ray tracing method not only outperforms other methods in computation time, but also provides improved reconstructions with good accuracy.