• The Journal of the Korean dental association
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• v.50 no.4
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• pp.180-188
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• 2012

Cone beam computed tomography(CBCT) machines recently developed in Korea, being designed for imaging hard tissues of the oral and maxillofacial region. I reported a brief overview of CBCT system, in comparison with coventional computed tomography(CT) system. CBCT provides high resolution, simpler image acquisition, lower dose and cost alternative to conventional CT, promising to revolutionize the practice of oral and maxillofacial radiology.

• Imaging Science in Dentistry
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• v.36 no.3
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• pp.123-129
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• 2006

The use of computed tomography for dental procedures has increased recently. Cone beam computed tomography (CBCT) systems have been designed for imaging hard tissues of the dentomaxillofacial region. CBCT is capable of providing high resolution in images of high diagnostic quality. This technology allows for 3-dimensional representation of the dentomaxillofacial skeleton with minimal distortion, but at lower equipment cost, simpler image acquisition and lower patient dose. Because this technology produces images with isotropic sub-millimeter spatial resolution, it is ideally suited for dedicated dentomaxillofacial imaging. In this paper, we provide a brief overview of cone beam scanning technology and compare it with the fan beam scanning used in conventional CT and the basic principles of currently available CBCT systems.

• Imaging Science in Dentistry
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• v.50 no.4
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• pp.331-337
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• 2020

Purpose: As cone-beam computed tomography (CBCT) has become the most widely used 3-dimensional (3D) imaging modality in the dental field, storage space and costs for large-capacity data have become an important issue. Therefore, if 3D data can be stored at a clinically acceptable compression rate, the burden in terms of storage space and cost can be reduced and data can be managed more efficiently. In this study, a deep learning network for super-resolution was tested to restore compressed virtual CBCT images. Materials and Methods: Virtual CBCT image data were created with a publicly available online dataset (CQ500) of multidetector computed tomography images using CBCT reconstruction software (TIGRE). A very deep super-resolution (VDSR) network was trained to restore high-resolution virtual CBCT images from the low-resolution virtual CBCT images. Results: The images reconstructed by VDSR showed better image quality than bicubic interpolation in restored images at various scale ratios. The highest scale ratio with clinically acceptable reconstruction accuracy using VDSR was 2.1. Conclusion: VDSR showed promising restoration accuracy in this study. In the future, it will be necessary to experiment with new deep learning algorithms and large-scale data for clinical application of this technology.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.378-382
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• 2001

The purpose of this study was to develop an expert system supporting the diagnosis of diffuse interstitial lung disease by high resolution computed tomography. CLIPS(C language integrated production system) with rule-based reasoning was used to develop the system. Development of expert system had three stages knowledge acquisition, knowledge representation, and reasoning. Knowledge was obtained and integrated, from tables and figure legends of a representative textbook in the domain of this expert system, High-Resolution CT of the Lung, by Webb WR, Mueller NL, and Naidich DP. The acquired knowledge was analyzed to form a knowledge base. Overlapping knowledge was eliminated, similar pieces of knowledge were combined and professional terms were defined. The most important knowledge of findings was then selected for each disease. After groupings of combined findings were made, disease groups were analyzed sequentially to determine final diagnoses. The system was based upon the input of 69 diseases, 185 findings, 73 conditions, 387 status, and 62 rules. The system was set up to determine the diagnoses of diseases from the combination of findings using forward reasoning. In an empirical trial, the system was applied to support the diagnosis of 40 cases of diffuse interstitial lung diseases. The performance of two doctors with support of the system was compared to that of another two doctors without support of the system. The two doctors with the support of the system made more accurate diagnoses than the doctors without the support of the system. The system is believed to be useful for the diagnosis of rare diseases and for cases with many possible differential diagnoses. In conclusion, an expert system supporting the high resolution computed tomographic diagnosis of diffuse interstitial lung disease was developed and the system is thought to be useful for medical practice.

• Journal of Magnetics
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• v.19 no.4
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• pp.372-377
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• 2014

The purpose of the study is to investigate how uptake counts of $^{201}Tl$ of radioisotopes in the human body could change, when taking computed tomography and magnetic resonance imaging right after injecting contrast media. $^{201}Tl$ radioisotope substances of iodine contrast medium, which is a computed tomography contrast medium, and paramagnetic contrast medium, which is an magnetic resonance imaging contrast medium, were used as study materials. First, $^{201}Tl$ was put into 4 cc of normal saline in test tube, and then a computed tomography contrast medium of Iopamidol$^{(R)}$ or Dotarem$^{(R)}$, was put into 2 cc of normal saline in test tube. An magnetic resonance imaging contrast medium of Primovist$^{(R)}$ or Gadovist$^{(R)}$ was also put into 2 cc of normal saline in test tube. Each contrast medium was distributed to make $^{201}Tl$ as 3 mCi, with a total of 4 cc. Gamma camera, low energy high resolution collimator, and pinhole collimator were used to obtain images. The uptake count of $^{201}Tl$ was measured with 1000 frames of images, and obtained after 10 times of repetition. This study revealed that the use of Gadovist$^{(R)}$, which is an magnetic resonance imaging contrast medium, showed the smallest number of uptake count, after measuring $^{201}Tl$ uptake count by low energy high resolution collimator. On the other hand, the use of Iopamidol$^{(R)}$, which is a computed tomography contrast medium, showed the biggest difference in uptake count, when measuring $^{99m}Tc$ uptake count by Pinhole collimator. When examining with gamma camera, using contrast medium and $^{201}Tl$, identifying the changes of uptake count is very important for improving the value of diagnosis.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.95-101
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• 2007

Recently, small-animal imaging technology has been rapidly developed for longitudinal screening of laboratory animals such as mice and rats. One of newly developed imaging modalities for small animals is an x-ray micro-CT (computed tomography). We have developed two types of x-ray micro-CT systems for small animal imaging. Both systems use flat-panel x-ray detectors and micro-focus x-ray sources to obtain high spatial resolution of $10{\mu}m$. In spite of the relatively large field-of-view (FOV) of flat-panel detectors, the spatial resolution in the whole-body imaging of rats should be sacrificed down to the order of $100{\mu}m$ due to the limited number of x-ray detector pixels. Though the spatial resolution of cone-beam CTs can be improved by moving an object toward an x-ray source, the FOV should be reduced and the object size is also limited. To overcome the limitation of the object size and resolution, we introduce zoom-in micro-tomography for high-resolution imaging of a local region-of-interest (ROI) inside a large object. For zoom-in imaging, we use two kinds of projection data in combination, one from a full FOV scan of the whole object and the other from a limited FOV scan of the ROI. Both of our micro-CT systems have zoom-in micro-tomography capability. One of both is a micro-CT system with a fixed gantry mounted with an x-ray source and a detector. An imaged object is laid on a rotating table between a source and a detector. The other micro-CT system has a rotating gantry with a fixed object table, which makes whole scans without rotating an object. In this paper, we report the results of in vivo small animal study using the developed micro-CTs.

• Journal of Biomedical Engineering Research
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• v.27 no.4
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• pp.189-196
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• 2006

Micro computed tomography (micro-CT) has been used for in vivo animal study owing to its noninvasive and high spatial resolution capability. However, the sizes of existing detectors for micro-CT systems are too small to obtain whole-body images of a small animal object with $\sim$10 micron resolution and a part of its bones or other organs should be extracted. So, we have introduced the zoom-in micro-tomography technique which can obtain high-resolution images of a local region of an live animal object without extracting samples. In order to verify our zoom-in technique, we performed in vivo animal bone study. We prepared some SD (Sprague-Dawley) rats for making osteoporosis models. They were divided into control and ovariectomized groups. Again, the ovariectomized group is divided into two groups fed with normal food and with calcium-free food. And we took 3D tomographic images of their femurs with 20 micron resolution using our zoom-in tomography technique and observed the bone changes for 12 weeks. We selected ROI (region of interest) of a femur image and applied 2D FDT (fuzzy distance transform) to measure the trabecular bone thickness. The measured results showed obvious bone changes and big differences between control and ovariectomized groups. However, we found that the reliability of the measurement depended on the selection of ROI in a bone image for thickness calculation. So, we extended the method to 3D FDT technique. We selected 3D VOI (volume of interest) in the obtained 3D tomographic images and applied 3D FDT algorithm. The results showed that the 3D technique could give more accurate and reliable measurement.

• Journal of the Korean Wood Science and Technology
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• v.36 no.6
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• pp.13-22
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• 2008

Internal voids affecting the mechanical properties of wood composite were classified into two catagories and characteristics of voids were examined according to density variation of strandboard. The void distribution and content of strandboard according to board density were measured by X-ray computed tomography system and analized using image processing software. Prior to investigation, the densities of strandboard were measured by densitometer and the results were showed high correlation with conventional oven drying method. Based on the image analysis conducted on captured images by X-ray tomography, low resolution can be used to capture the macro-voids (between strand) but not the micro-voids (within strands). Intermediate resolution can be used to capture both the macro and the micro-voids and high resolution can be successfully used to capture the majority of the micro-voids. The content of macro-void was measured and content of micro-void was computed by corresponding related equation. The macro-void distribution can be successfully understood and void content can be correctly estimated through the results.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2341-2347
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• 2021

Because single-photon emission computed tomography (SPECT) is one of the widely used nuclear medicine imaging systems, it is extremely important to acquire high-quality images for diagnosis. In this study, we designed a super-resolution (SR) technique using dense block-based deep convolutional neural network (CNN) and evaluated the algorithm on real SPECT phantom images. To acquire the phantom images, a real SPECT system using a^99mTc source and two physical phantoms was used. To confirm the image quality, the noise properties and visual quality metric evaluation parameters were calculated. The results demonstrate that our proposed method delivers a more valid SR improvement by using dense block-based deep CNNs as compared to conventional reconstruction techniques. In particular, when the proposed method was used, the quantitative performance was improved from 1.2 to 5.0 times compared to the result of using the conventional iterative reconstruction. Here, we confirmed the effects on the image quality of the resulting SR image, and our proposed technique was shown to be effective for nuclear medicine imaging.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3380-3389
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• 2022

We evaluated the performance of an improved hybrid median filter (IHMF) applied to X-ray computed tomography (CT) images obtained using a high-resolution photon-counting cadmium zinc telluride (CZT) detector. To study how the proposed approach improves the image quality, we measured the noise levels and the overall CT-image quality. We established a CZT imaging system with a detector length of 5.12 cm and thickness of 0.3 cm and acquired phantom images. To evaluate the efficacy of the proposed filter, we first modeled two conventional median filters. Subsequently, we were able to achieve a normalized noise power spectrum result of ~10^-8 mm², and furthermore, the proposed method improved the contrast-to-noise ratio by a factor of ~1.51 and the coefficient of variation by 1.55 relative to the counterpart values of the no-filter image. In addition, the IHMF exhibited the best performance among the three filters considered as regards the peak signal-to-noise ratio and no-reference-based image-quality evaluation parameters. Thus, our results demonstrate that the IHMF approach provides a superior image performance over conventional median filtering methods when applied to actual CZT X-ray CT images.