• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.142-150
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• 2014

The key to model-based iterative reconstruction (MBIR) algorithms for transmission computed tomography lies in the ability to accurately model the data formation process from the emitted photons produced in the transmission source to the measured photons at the detector. Therefore, accurately modeling the system matrix that accounts for the data formation process is a prerequisite for MBIR-based algorithms. In this work we compared quantitative performance of the three representative ray-driven methods for calculating the system matrix; the ray-tracing method (RTM), the distance-driven method (DDM), and the strip-area based method (SAM). We implemented the ordered-subsets separable surrogates (OS-SPS) algorithm using the three different models and performed simulation studies using a digital phantom. Our experimental results show that, in spite of the more advanced features in the SAM and DDM, the traditional RTM implemented in the OS-SPS algorithm with an edge-preserving regularizer out-performs the SAM and DDM in restoring complex edges in the underlying object. The performance of the RTM in smooth regions was also comparable to that of the SAM or DDM.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2204-2212
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• 2022

Recently, the demand for alpha imaging detectors for quantifying the distributions of alpha particles has increased in various fields. This study aims to reconstruct a high-resolution image from an alpha imaging detector by applying a super-spatial resolution method combined with the maximum-likelihood expectation maximization (MLEM) algorithm. To perform the super-spatial resolution method, several images are acquired while slightly moving the detector to predefined positions. Then, a forward model for imaging is established by the system matrix containing the mechanical shifts, subsampling, and measured point-spread function of the imaging system. Using the measured images and system matrix, the MLEM algorithm is implemented, which converges towards a high-resolution image. We evaluated the performance of the proposed method through the Monte Carlo simulations and phantom experiments. The results showed that the super-spatial resolution method was successfully applied to the alpha imaging detector. The spatial resolution of the resultant image was improved by approximately 12% using four images. Overall, the study's outcomes demonstrate the feasibility of the super-spatial resolution method for the alpha imaging detector. Possible applications of the proposed method include high-resolution imaging for alpha particles of in vitro sliced tissue and pre-clinical biologic assessments for targeted alpha therapy.

• 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 KSMRM Conference
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• 2001.11a
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• pp.133-133
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• 2001

Purpose： To determine the relationship between anatomical variation at A-com. artery area an hemodynamically induced aneurysm-mimicking findings on 3D-TOF MRA clinically a experimentally. Method： Sixty-two patients who had no aneurysm at A-com artery on DSA were evalua with MRA. MRA was performed with 1.5T MR machine(Vision, Siemens). Scan parameters o MRA included TR/TE/FA=30/6.4/25$\psi$$\circledR$˙¡, 512＊192 of matrix with MIP technique. The occurrence of signal defect at shoulder area of bifurcated A-com artery on MRA was evalua for the relationship between the symmetricity of bilateral ACA and the patency of A-c artery. DSA images were acquired at both ICA and VA. To analyze hemodynamical facto of signal defect, experimental studies of MRA and DSA were peformed with elastic silic phantom using conducting pulsatile pump. We also compared the results with those o computational fluid dynamics(CFD).

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.413-418
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• 1994

In electrical impedance tomography (EIT), we use boundary current and voltage measurements to provide the information about the cross-sectional distribution of electrical impedance or resistivity One of the major problems in EIT has been the inaccessibility of internal voltage or current data in finding the internal impedance values. We propose a new image reconstruction method using internal current density data measured by NMR. We obtained a two-dimensional current density distribution within a phantom by processing the real and imaginary MR images from a 4.7T NMR machine. We implemented a resistivity image reconstruction algorithm using the finite element method and sensitivity matrix. We presented computer simulation results of the image reconstruction algorithm and furture direction of the research.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.85-91
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• 2018

Computed tomography, which obtains section images from reconstruction process using projection images, has been applied to various fields. The spatial resolution of the reconstructed image depends on the device used in CT system, the object, and the reconstruction process. In this paper, we investigates the effect of the number of projection images and the pixel size of the detector on the spatial resolution of the reconstructed image under the parallel beam geometry. The reconstruction program was written in Visual C++, and the matrix size of the reconstructed image was $512{\times}512$. The numerical bar phantom was constructed and the Min-Max method was introduced to evaluate the spatial resolution on the reconstructed image. When the number of projections used in reconstruction process was small, artifact like streak appeared and Min-Max was also low. The Min-Max showed upper saturation when the number of projections is increased. If the pixel size of the detector is reduced to 50% of the pixel size of the reconstructed image, the reconstructed image was perfectly recovered as the original phantom and the Min-Max decreased as increasing the detector pixel size. This study will be useful in determining the detector and the accuracy of rotation stage needed to achieve the spatial resolution required in the CT system.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.517-527
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• 1997

Magnetic Resonance Spectroscopic Imaging is a methodology combining the imaging and spectroscopy. It can provide the spectrum of each areas of image so that one can easily compare the spectrum of one position to another position of the image. In this study, we developed pulse sequence or the spectroscopic imaging method, RF wave forms or the saturation of water signal, computer simulations to validate our method, and confirmed the methodology with phantom experiment. Then we applied the spectroscopic method to human subject and identified a few important metabolites in in vivo. To develope a water saturating RF waveform, we used Shinnar-Le-Roux algorithm and obtained maximum phase RF waveform. With this RF pulse, it could suppress the water signal to 1:1000. The magnet is shimmed to under 1.0ppm with auto-shimming technique. The saturation bandwidth is 80Hz(2ppm). The water and fat seperation is 3.3ppm(about 140Hz at 1 Tesla magnet), the bandwidth is enough to resolve the difference. But we are more concerned about the narrow window in between the two peaks, in which the small quantity of metabolites reside. We performed the computer simulation and phantom experiments in 8*8 matrix form and showed good agreement in the image and spectrum. Finally we applied spectroscopic imaging to the brain of human subject. Only the lipid signal was shown in the periphery region which agrees with the at distribution in human head surface area. The spectrum inside the brain shows the important metabolites such as NAA, Cr/PCr, Choline. We here have shown the spectroscopic imaging which is normally done above 1.5 Tesla machine can be performed in the 1 Tesla Magnetic Resonance Imaging Unit.

• Progress in Medical Physics
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• v.5 no.1
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• pp.55-66
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• 1994

After proving home-made imaging pulse sequences including tailored RF pulse by phantom, susceptibility-contrast-enhanced MR venograms of cat brain were obtained using tailored RF gradient-echo(TRGE) method. Sagittal MR imaging of the cat brain obtained by TRGE technique shows several veins, for example, dorsal sagittal sinus, straight sinus, vein of corpus callosum and internal cerebral vein, etc., compared with cats anatomical figure. Tailored RF waveform was generated by PASCAL language in ASPECT 3000 computer(Switzland, Bruker). Rectangular-shaped slice profile with bi-linear ramp function as phase distribution in the slice, at which maximum value was 2$\pi$, was fourier transformed to make tailored RF pulse. Experimental MR imaging parameters were TR/TE=205/10 msec, slice thickness TH=7mm, maxtrix size=256$\times$256, in-plane resolution=0.62$\times$0.31mm$^2$, and field of view(FOV)=8cm for both conventional gradient-echo(GE) imaging and TRGE imaging techniques.

• Journal of the Korean Society of Radiology
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• v.1 no.1
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• pp.11-16
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• 2007

In this study, we have performed contrast-detail analysis for an amorphous selenium(a-Se) based digital X-ray imaging system by using a contrast-detail phantom(CDRAD 2.0) to test its low contrast performance. The X-ray imaging system utilizes an 500-mm-thick a-Se semiconductor X-ray absorber coated over an amorphous silicon(a-Si) TFT(thin-film transistor) detector matrix with a $139mm{\times}139mm$ pixel size and a $46.7cm{\times}46.7cm$ active area. In the measurement of contrast-detail curves we first acquired X-ray images of the CDRAD 2.0 phantom at given test conditions(i.e., 40, 50, 60, 70, 80 kVp, and 16 mA.s), and then evaluated the contrast-detail characteristics of the imaging system from each phantom image by using an image quality factor called the image-quality-figure-inverse(IQFinv). The IQFinv values for the imaging system gradually improved with the photon fluence, indicating the improvement of image visibility: 24.4, 35.3, 39.2, 41.5, and 43.4 at photon fluences of $1.8{\times}105$, $5.9{\times}105$, $11.3{\times}105$, $19.4{\times}105$, and $29.4{\times}105$ photons/$mm^2$, respectively.

• Journal of Magnetics
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• v.17 no.2
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• pp.153-157
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• 2012

This study evaluated the ability of Diffusion-Weight Image (DWI), which is one of pulse sequences used in MRI based on the T2 weighted images, to detect samples placed within phantoms according to their size. Two identically sized phantoms, which could be inserted into the breast coil bilaterally, were prepared. Five samples with different sizes were placed in the phantoms, and the T2 weighted images and DWI were obtained. The Breast 2 channel coil of SIEMENS MAGNETOM Avanto 1.5 Tesla equipment was used for the experiments. 2D T2 weighted images were obtained using the following parameters: TR/TE = 6700/74 msec, Thickness/gap = 5/1 mm, Inversion Time (TI) = 130 ms, and matrix = $224{\times}448$. The parameters of DWI were that TR/TE = 8100/90 msec, Thickness/gap = 5/1 mm, matrix = $128{\times}128$, Inversion Time = 185 ms, and b-value = 0, 100, 300, 600, 1000 s/mm. The ratio of the sample volume on DWI compared to the T2 weighted images, which show excellent ability to detect lesions on MR images, was presented as the mean b-value. The measured b-value of the samples was obtained: 0.5${\times}$0.5 cm=0.33/0.34 square ${\times}$ cm (103%), 1${\times}$1 cm=1.28/1.25 square ${\times}$ cm (102.4%), 1.5${\times}$1.5 cm = 2.28/2.67 square ${\times}$ cm (85.39%), 2${\times}$2 cm=3.56/4.08 square ${\times}$ cm (87.25%), and 2.5${\times}$2.5 cm=7.53/8.77 square ${\times}$ cm (85.86%). In conclusion, the detection ability by the size of a sample was measured to be over 85% compared to T2 weighted image, but the detection ability of DWI was relatively lower than that of T2 weighted image.