• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.365-373
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• 1997

In this paper, a new method of the 3D(dimensional) image reconstruction is proposed to build up the 3D image from 2D images using digital image processing techniques and computer graphics. First, the new feature extraction algorithm that doesn't need various input parameters and is not affected by threshold is adopted This new algorithm extracts feature points by eliminating some undesirable points on the ground of the connectivity. Second, as the cast function to reconstruct surfaces using extracted feature points, the minimum distance measure between two plane images has been adopted According to this measure, the surface formation algorithm doesn't need complex calculation and takes the form of triangle or trapezoid To investigate usefulness, this approach has been applied to a head CT image and compared with other methods. Experimental comparisons show that the suggested algorithm yields better performance on feature extraction than others. In contrast with the other methods, the complex calculation for surface formation in the proposed algorithm is not necessary.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1553-1561
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• 2024

Nondestructive radiography using cosmic ray muons has been used for decades to monitor nuclear reactor and spent nuclear fuel storage. Because nuclear fuel assemblies are highly dense and large, typical radiation probes such as x-rays cannot penetrate these target imaging objects. Although cosmic ray muons are highly penetrative for nuclear fuels as a result of their relatively high energy, the wide application of muon tomography is limited because of naturally low cosmic ray muon flux. This work presents a new image reconstruction algorithm to maximize the utility of cosmic ray muon in tomography applications. Muon momentum information is used to improve imaging resolution, as well as muon scattering angle. In this work, a new convolution was introduced known as M-value, which is a mathematical integration of two measured quantities: scattering angle and momentum. It captures the objects' quantity and density in a way that is easy to use with image reconstruction algorithms. The results demonstrate how to reconstruct images when muon momentum measurements are included in a typical muon scattering tomography algorithm. Using M-value improves muon tomography image resolution by replacing the scattering angle value without increasing computation costs. This new algorithm is projected to be a standard nondestructive radiography technique for spent nuclear fuel and nuclear material management.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.41-46
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• 2023

Iterative reconstruction of CT takes a long time because projection and back-projection are alternatively repeated until taking a good image. To reduce the reconstruction time, we need a fast algorithm for calculating the projection which is a time-consuming step. In this paper, we proposed a new algorithm to calculate the line integral and the algorithm is approximately 10% faster than the well-known Siddon method (Jacobs version) and has a good image quality. Although the algorithm has been investigated for the case of parallel beams, it can be extended to the case of fan and cone beam geometries in the future.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.5-7
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• 1991

We have developed an efficient and robust image reconstruction algorithm for static impedance imaging. This improved Newton-Raphson method produced more accurate images by reducing the undesirable effects of the ill-conditioned Hessian matrix. We found that our electrical impedance tomography (EIT) system could produce two-dimensional static images from a physical phantom with 7% spatial resolution at the center and 5% at the periphery. Static EIT image reconstruction requires a large amount of computation. In order to overcome the limitations on reducing the computation time by algorithmic approaches, we implemented the improved Newton-Raphson algorithm on a parallel computer system and showed that the parallel computation could reduce the computation time from hours to minutes.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.232-235
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• 1988

Recently, an iterative reconstruction-reprojection (IRR) algorithm has been suggested for application to incomplete data computed tomography (CT). In the IRR, the interpolation operation is performed in the image space during reconstruction-reprojection. The errors associated with the interpolation degrade the reconstructed image and may cause divergence unless a large number of rays is used. In this paper, we propose an improved IRR algorithm which eliminates the need for interpolation. The proposed algorithm adopts a new sampling scheme in which samples (projection data) is taken in phase with the samples of the Cartesian grid.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.111-117
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• 1996

In tis paper, a new morphological algorihtm for binary image reconstruction from graayscale skeleton is proposed. In the proposed algorithm, grayscale morphological dilation is utilizedm instead of binary morphological operatons for the conventional methods. The algorithm is proven mathematically and verified by computer simulation results.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.3 no.2
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• pp.65-71
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• 2017

To assess the effects of filter and reconstruction of Cu-64 PET data on Siemens scanner, the various reconstruction algorithm with various filters were assessed in terms of spatial resolution, non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR). Image reconstruction was performed using filtered backprojection (FBP), 2D ordered subset expectation maximization (OSEM), 3D reprojection algorithm (3DRP), and maximum a posteriori algorithms (MAP). For the FBP reconstruction, ramp, butterworth, hamming, hanning, or parzen filters were used. Attenuation or scatter correction were performed to assess the effect of attenuation and scatter correction. Regarding spatial resolution, highest achievable volumetric resolution was $3.08mm^3$ at the center of FOV when MAP (${\beta}=0.1$) reconstruction method was used. SOR was below 4% for FBP when ramp, Hamming, Hanning, or Shepp-logan filter were used. The lowest NU (highest uniform) after attenuation & scatter correction was 5.39% when FBP (parzen filter) was used. Regarding RC, 0.9 < RC < 1.1 was obtained when OSEM (iteration: 10) was used when attenuation and scatter correction were applied. In this study, image quality of Cu-64 on Siemens Inveon PET was investigated. This data will helpful for the quantification of Cu-64 PET data.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.146-153
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• 2015

In order to contain as much information as possible in a single image, a wide FOV(Field-Of-View) imaging system is required. The catadioptric imaging system with hyperbolic cylinder mirror can acquire over 180 degree horizontal FOV realtime panorama image by using a conventional camera. Because the hyperbolic cylinder mirror has a curved surface in horizontal axis, the original image acquired from the imaging system has the geometrical distortion, which requires the image processing algorithm for reconstruction. In this paper, the image reconstruction algorithms for two cases are studied: (1) to obtain an image with uniform angular resolution and (2) to obtain horizontally rectilinear image. The image acquisition model of the hyperbolic cylinder mirror imaging system is analyzed by the geometrical optics and the image reconstruction algorithms are proposed based on the image acquisition model. To show the validity of the proposed algorithms, experiments are carried out and presented in this paper. The experimental results show that the reconstructed images have a uniform angular resolution and a rectilinear form in horizontal axis, which are natural to human.

• Journal of Broadcast Engineering
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• v.8 no.1
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• pp.19-29
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• 2003

The demand for high-resolution images is gradually increasing, whereas many imaging systems yield aliased and undersampled images during image acquisition. In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized Iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for application with multiframe environments. Since the registration error in each low-resolution has a different pattern, the regularization parameters are determined adaptively for each channel. We propose a methods for estimating the regularization parameter automatically. The preposed algorithm are robust against the registration error noise. and they do not require any prior information about the original image or the registration error process. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.298-304
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• 2009

This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.