• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.847-858
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• 2016

An overview is given on the work of the Laboratory of Nuclear Energy Systems at ETH, Zurich (ETHZ) and of the Laboratory of Thermal Hydraulics at Paul Scherrer Institute (PSI), Switzerland on tight-lattice bundles. Two-phase flow in subchannels of a tight triangular lattice was studied experimentally and by computational fluid dynamics simulations. Two adiabatic facilities were used: (1) a vertical channel modeling a pair of neighboring sub-channels; and (2) an arrangement of four subchannels with one subchannel in the center. The first geometry was equipped with two electrical film sensors placed on opposing rod surfaces forming the subchannel gap. They recorded 2D liquid film thickness distributions on a domain of $16{\times}64$ measuring points each, with a time resolution of 10 kHz. In the bubbly and slug flow regime, information on the bubble size, shape, and velocity and the residual liquid film thickness underneath the bubbles were obtained. The second channel was investigated using cold neutron tomography, which allowed the measurement of average liquid film profiles showing the effect of spacer grids with vanes. The results were reproduced by large eddy simulation + volume of fluid. In the outlook, a novel nonadiabatic subchannel experiment is introduced that can be driven to steady-state dryout. A refrigerant is heated by a heavy water circuit, which allows the application of cold neutron tomography.

• Progress in Medical Physics
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• v.33 no.4
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• pp.172-179
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• 2022

Recently, tetrahedral phantoms have been newly adopted as international standard mesh-type reference computational phantoms (MRCPs) by the International Commission on Radiological Protection, and a program has been developed to convert them to computational tomography images and DICOM-RT structure files for application of radiotherapy. Through this program, the use of the tetrahedral standard phantom has become available in clinical practice, but utilization has been difficult due to various library dependencies requiring a lot of time and effort for installation. To overcome this limitation, in this study a newly developed TET2DICOM-GUI, a TET2DICOM program based on a graphical user interface (GUI), was programmed using only the MATLAB language so that it can be used without additional library installation and configuration. The program runs in the same order as TET2DICOM and has been optimized to run on a personal computer in a GUI environment. A tetrahedron-based male international standard human phantom, MRCP-AM, was used to evaluate TET2DICOM-GUI. Conversion into a DICOM-RT dataset applicable in clinical practice in about one hour with a personal computer as a basis was confirmed. Also, the generated DICOM-RT dataset was confirmed to be effectively implemented in the radiotherapy planning system. The program developed in this study is expected to replace actual patient data in future studies.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.91-98
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• 2017

Electrical impedance tomography is a nondestructive imaging technique to reconstruct unknown conductivity distribution based on applied current data and measured voltage data through an array of electrodes attached on the periphery of a domain. In this paper, an inverse method based on truncated singular value decomposition is proposed to solve the inverse problem with the generalized Tikhonov regularization and to reconstruct the conductivity distribution. In order to reduce the inverse computational time, truncated singular value decomposition is applied to the inverse term after the generalized regularization matrix is taken out from the inverse matrix term. Numerical experiments and phantom experiments have been performed to verify the performance of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.83-90
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• 2017

Electrical impedance tomography is a relatively new nondestructive imaging modality in which the internal conductivity distribution is reconstructed based on the injected currents and measured voltages through electrodes placed on the surface of a domain. In this paper, a fast iterative Gauss-Newton method is proposed to increase the spatial resolution as well as reduce the inverse computational time in the inverse problem, which could be applied to online binary mixture flow applications. To evaluate the reconstruction performance of the proposed method, numerical experiments have been carried out and the results are analyzed.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.279-287
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• 2009

Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging modality providing cross-sectional images of a conductivity distribution inside an electrically conducting object. MREIT has rapidly progressed in its theory, algorithm and experimental technique and now reached the stage of in vivo animal and human experiments. Conductivity image reconstructions in MREIT require various steps of carefully implemented numerical computations. To facilitate MREIT research, there is a pressing need for an MREIT software package with an efficient user interface. In this paper, we present an example of such a software, called CoReHA which stands for conductivity reconstructor using harmonic algorithms. It offers various computational tools including preprocessing of MREIT data, identification of boundary geometry, electrode modeling, meshing and implementation of the finite element method. Conductivity image reconstruction methods based on the harmonic $B_z$ algorithm are used to produce cross-sectional conductivity images. After summarizing basics of MREIT theory and experimental method, we describe technical details of each data processing task for conductivity image reconstructions. We pay attention to pitfalls and cautions in their numerical implementations. The presented software will be useful to researchers in the field of MREIT for simulation as well as experimental studies.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.49-56
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• 1997

In emission computed tomography, statistical reconstruction methods in the context of a Bayesian framework have been a topic of interest over the last decade. This was mainly due to the fact that Bayesian approaches can incorporate a priori information into the reconstruction algorithm. Although these approaches can exhibit good performance, their applications to the clinic is hindered mainly by their high computational cost. On the other hand, the speed and simplicity of the filtered backprojection (FBP) algorithm have led to its widespread use in most clinical applications. In this work, we use spline models, which have been quite useful in Bayesian reconstruction, as regularizers for high-frequency apodization in FBP algorithm and show that the effects of using spline models as priors in Bayesian reconstruction can also be achieved in FBP reconstruction.

• Current Optics and Photonics
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• v.2 no.5
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• pp.453-459
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• 2018

We have developed a high-performance signal-processing and image-rendering heterogeneous computation system for optical coherence tomography (OCT) on mobile processor. In this paper, we reveal it by demonstrating real-time OCT image processing using a Snapdragon 800 mobile processor, with the introduction of a heterogeneous image visualization architecture (HIVA) to accelerate the signal-processing and image-visualization procedures. HIVA has been designed to maximize the computational performances of a mobile processor by using a native language compiler, which targets mobile processor, to directly access mobile-processor computing resources and the open computing language (OpenCL) for heterogeneous computation. The developed mobile image processing platform requires only 25 ms to produce an OCT image from $512{\times}1024$ OCT data. This is 617 times faster than the naïve approach without HIVA, which requires more than 15 s. The developed platform can produce 40 OCT images per second, to facilitate real-time mobile OCT image visualization. We believe this study would facilitate the development of portable diagnostic image visualization with medical imaging modality, which requires computationally expensive procedures, using a mobile processor.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.211-216
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• 2005

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 a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.159-164
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• 2004

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 a simultaneous perturbation method as an image reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.154-156
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• 1996

A new method for electric resistivity tomography(ERT) is developed for geophysical inverse problems by adapting the sensitivity analysis. The outputs of the potential electrodes are computed using two dimensional finite element method in the wave number space by Fourier transforming the governing equations. The resistance distribution in the region of interests, which makes the computed potential distribution coincide with the measured potential, is found by minimizing the objective function using an optimization method. In this process the sensitivity analysis is introduced in order to compute the derivatives of the objective function. And an adjoint variable method is used to save the computational efforts for sensitivity coefficients.