• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.1-16
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• 2019

Dynamic contrast enhanced (DCE) magnetic resonance (MR) imaging plays an important role in non-invasive detection and characterization of primary and metastatic lesions in the liver. Recently, efforts have been made to improve spatial and temporal resolution of DCE liver MRI for arterial phase imaging. Review of recent publications related to arterial phase imaging of the liver indicates that there exist primarily two approaches: breath-hold and free-breathing. For breath-hold imaging, acquiring multiple arterial phase images in a breath-hold is the preferred approach over conventional single-phase imaging. For free-breathing imaging, a combination of three-dimensional (3D) stack-of-stars golden-angle sampling and compressed sensing parallel imaging reconstruction is one of emerging techniques. Self-gating can be used to decrease respiratory motion artifact. This article introduces recent MRI technologies relevant to hepatic arterial phase imaging, including differential subsampling with Cartesian ordering (DISCO), golden-angle radial sparse parallel (GRASP), and X-D GRASP. This article also describes techniques related to dynamic 3D image reconstruction of the liver from golden-angle stack-of-stars data.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.3
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• pp.20-25
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• 1980

A singular value decomposition (SVD) pseudo-inversion method has been applied to the image reconstruction from projections. This approach is relatively unknown and differs from conventionally used reconstructioll methods such as the Foxier convolution and iterative techniques. In this paper, two SVD pseudo-inversion methods have been discussed for the search of optimum reconstruction and restoration, one using truncated inverse filtering, the other scalar Wiener filtering. These methods partly overcome the ill-conditioned nature of restoration problems by trading off between noise and signal quality. To test the SVD pseudo-inversion method, simulations were performed from projection data obtained from a phantom using truncated inversefiltering. The results are presented together with some limitations particular to the applications of the method to the general class of 3-D image reconstruction and restoration.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1145-1148
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• 2002

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera and the problem of recovering 3D models from three vanishing points of box scene. Our approach is to compute only three vanishing points without this information such as the focal length, rotation matrix, and translation from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector ν. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by the standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• Progress in Medical Physics
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• v.20 no.2
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• pp.62-71
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• 2009

Recently, optical coherence tomography (OCT) has demonstrated considerable promise for the noninvasive assessment of biological tissues. However, OCT images difficult to analyze due to speckle noise. In this paper, we tested various image processing techniques for speckle removal of human and rabbit cartilage OCT images. Also, we distinguished the images which get with methods of image segmentation for OCT images, and found the most suitable method for segmenting an image. And, we selected image segmentation suitable for OCT before image reconstruction. OCT was a weak point to system design and image processing. It was a limit owing to measure small a distance and depth size. So, good edge matching algorithms are important for image reconstruction. This paper presents such an algorithm, the chamfer matching algorithm. It is made of background for 3D image reconstruction. The purpose of this paper is to describe good image processing techniques for speckle removal, image segmentation, and the 3D reconstruction of cartilage OCT images.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.243-250
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• 1998

Reconstruction aspects of spiral scan imaging for ultra fast magnetic resonance imagine(MRI) have been investigated with polar and rectangular coordinates-based reconstruction. For the reconstruction of the spiral scan imaging, acquired data in spiral trjectory should be converted to polar or rectangular grids, where interpolation techniques are used. Various reconstruction algorithms for spiral scan imaging are tested, and reconstructed image qualities are compared with computed phantom. An improved reconstruction algorithm with dc-offset correction in projection domain is proposed, which provides the best reconstructed image quality from the simulation. Image artifact with existing algorithms is completely removed with the proposed method.

• Progress in Medical Physics
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• v.31 no.3
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• pp.81-98
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• 2020

This review aims to provide a brief, comprehensive overview of advanced technologies of nuclear medicine physics, with a focus on recent developments from both hardware and software perspectives. Developments in image acquisition/reconstruction, especially the time-of-flight and point spread function, have potential advantages in the image signal-to-noise ratio and spatial resolution. Modern detector materials and devices (including lutetium oxyorthosilicate, cadmium zinc tellurium, and silicon photomultiplier) as well as modern nuclear medicine imaging systems (including positron emission tomography [PET]/computerized tomography [CT], whole-body PET, PET/magnetic resonance [MR], and digital PET) enable not only high-quality digital image acquisition, but also subsequent image processing, including image reconstruction and post-reconstruction methods. Moreover, theranostics in nuclear medicine extend the usefulness of nuclear medicine physics far more than quantitative image-based diagnosis, playing a key role in personalized/precision medicine by raising the importance of internal radiation dosimetry in nuclear medicine. Now that deep-learning-based image processing can be incorporated in nuclear medicine image acquisition/processing, the aforementioned fields of nuclear medicine physics face the new era of Industry 4.0. Ongoing technological developments in nuclear medicine physics are leading to enhanced image quality and decreased radiation exposure as well as quantitative and personalized healthcare.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.257-263
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• 2011

Sparse-view CT imaging is considered to be a solution to reduce x-ray dose of CT. Sparse-view CT imaging may have severe streak artifacts that could compromise the image qualities. We have compared quality of sparseview images reconstructed with two representative iterative reconstruction techniques, SIRT and TV-minimization, in terms of image error and edge preservation. In the comparison study, we have used the Shepp-Logan phantom image and real CT images obtained with a micro-CT. In both phantom image and real CT image tests, TV-minimization technique shows the best performance in error reduction and preserving edges. However, the excessive computation time of TV-minimization is a technical challenge for the practical use.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.513-516
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• 2002

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.104-110
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• 2014

This paper considers two reconstruction schemes of structured-sparse signals, turbo inference and Markov chain Monte Carlo (MCMC) inference, in compressed sensing(CS) technique that is recently getting an important issue for an efficient video wireless transmission system using multi-copter as an unmanned aerial vehicle. Proposed reconstruction algorithms are setting importance on reduction of image data sizes, fast reconstruction speed and errorless reconstruction. As a result of experimentation with twenty kinds of images, we can find turbo reconstruction algorithm based on loopy belief propagation(BP) has more excellent performances than MCMC algorithm based on Gibbs sampling as aspects of average reconstruction computation time, normalized mean squared error(NMSE) values.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.557-567
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• 2015

With the increasing demands of 3D spatial information in urban environment, the importance of point clouds generation techniques have been increased. In particular, for as-built BIM, the point clouds with the high accuracy and density is required to describe the detail information of building components. Since the terrestrial LiDAR has high performance in terms of accuracy and point density, it has been widely used for as-built 3D modelling. However, the high cost of devices is obstacle for general uses, and the image-based 3D reconstruction technique is being a new attraction as an alternative solution. This paper compares the image-based 3D reconstruction technique and the terrestrial LiDAR in point of establishing the as-built BIM of outdoor structures. The point clouds generated from the image-based 3D reconstruction technique could roughly present the 3D shape of a building, but could not precisely express detail information, such as windows, doors and a roof of building. There were 13.2~28.9 cm of RMSE between the terrestrial LiDAR scanning data and the point clouds, which generated from smartphone and DSLR camera images. In conclusion, the results demonstrate that the image-based 3D reconstruction can be used in drawing building footprint and wireframe, and the terrestrial LiDAR is suitable for detail 3D outdoor modeling.