• Korean Journal of Digital Imaging in Medicine
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• v.1 no.1
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• pp.1-7
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• 1995

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.63-66
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• 2019

Due to the development of medical imaging technology, different imaging technologies provide a large amount of effective information. However, different imaging method caused the limitations of information integrity by using single type of image. Combining different image together so that doctor can obtain the information from medical image comprehensively. Image registration algorithm based on mutual information has become one of the hotspots in the field of image registration with its high registration accuracy and wide applicability. Because the information theory-based registration technology is not dependent on the gray value difference of the image, and it is very suitable for multimodal medical image registration. However, the method based on mutual information has a robustness problem. The essential reason is that the mutual information itself is not have enough information between the pixel pairs, so that the mutual information is unstable during the registration process. A large number of local extreme values are generated, which finally cause mismatch. In order to overcome the shortages of mutual information registration method, this paper proposes a registration method combined with image spatial structure information and mutual information.

• Journal of Biomedical Engineering Research
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• v.12 no.3
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• pp.215-222
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• 1991

In this paper, we present a result of our study on how to construct a pilot MPACS (medical hic lure archiving and communication System) based on X -Window system. The proposed MPACS Is composed of image acquisition units, image archiving and processing units, display units, and all units are Interfaced with a LAN The image management is done according to the TIFF (Tagged Image File Format) , and the dis- play system is built upon generally accepted software packages, namely the X -Window system. Also, lossless and lossy digital image compression methods were implemented and tested with X -ray and CT images.

• Korean Journal of Digital Imaging in Medicine
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• v.8 no.1
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• pp.27-32
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• 2006

The rapid development in digital acquisition technology in radiography has not been accompanied by information regarding optimum radiolographic technique for use with an amorphus silicon flat panel detector. The purpose of our study was to compared imaging characteristics and image quality of an amorphus silicon flat panel detectors for digital chest radiography. All examinations were performed by using an amorphus silicon flat panel detector. Chest radiographs of an chest phantom were obtained with peak kilovoltage values of 60$\sim$150 kVp. Published data ell the effect of x-ray beam energy on imaging characteristics and image qualify when using an amorphus silicon flat panel detector. It is important that radiographers are aware of optimum kVp selection for an amorphus silicon flat panel detector system, particularly for the commonly performed chest examination.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.33-40
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• 2002

In this paper, we proposed a lossless compression algorithm of medical images which is essential technique in picture archive and communication system. Mammographic image and magnetic resonance image in among medical images used in this study, proposed a region growing segmentation algorithm for compression of these images. A proposed algorithm was partition by three sub region which error image, discontinuity index map, high order bit data from original image. And generated discontinuity index image data and error image which apply to a region growing algorithm are compressed using JBIG(Joint Bi-level Image experts Group) algorithm that is international hi-level image compression standard and proper image compression technique of gray code digital Images. The proposed lossless compression method resulted in, on the average, lossless compression to about 73.14% with a database of high-resolution digital mammography images. In comparison with direct coding by JBIG, JPEG, and Lempel-Ziv coding methods, the proposed method performed better by 3.7%, 7.9% and 23.6% on the database used.

• The Journal of the Korean dental association
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• v.43 no.1 s.428
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• pp.41-52
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• 2005

Information Technology has extended its scope to the medical field as well as dental field. Like medical field, network ststem for dental field requires acquisition, storage, and display of images. However, unlike the medical field, the system to integrate several information including medical images has not been developed according to industrial standard for management of digital image for medical use, so called DICOM conformance. which makes the digital environment in dental field more and more difficult and expensive for this standardization and comfortable communication in LAN and WAN. To solve this problem, the DICOM encoder and server has to be developed because the DICOM file can be easily retrieved with patient's information from the DICOM server in the system as DICOM file has the standard specification to integrate the patient's information. The information including image and other discrete data can be easily integrated in DICOM file and can be used without any difficulty for precise diagnosis and for contribution to the decision making for each treatment protocol. Therefore, the system composed of DICOM encoder and server in dental practive for DICOM file must be developed with prudent consideration of the several strategic factors: I) Enhanced diagnostic capability through the integrated information of image and clinical data. ii) Clinician-friendly interface to simulate the systemic treatment procedure in clinical practice iii) Implementation of multidisciplinary treatment protocol The development of DICOM encoder and server based on these strategic considerations will provide paperless and filmless hospital environments by the seamless integration and management of patient's history, several clinical data and clinical images through image processing for quantitative analysis. The system also allows clinicians to provide more predictable dental care for the patients.

• Journal of radiological science and technology
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• v.30 no.2
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• pp.153-159
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• 2007

Digital medical image commenced with an introduction of PACS has become more popular today in the radiation diagnosis and radiation treatment and made great progress, in particular, for medical testing field, whereas it has made slow progress for radiation treatment field. In order to accommodate the current trend of digital from analog, a spherical mechanical check device(SMCD) that is the form of spherical differing from the existing form of flat or cube has been designed and tested its practicability to replace the part in mechanical check with digital image from QA operation. If the distance maintains constance between source(target) and image detector with constant distance to the center of spherical mechanical check device(SMCD), the size will be shown as a constant image at all times regardless of its direction exposed. For the test, two accurate hemispheres are made and put together which results in a sphere of the equilateral circle. It enables a variety of implementation of the existing mechanical check using digital image as follows: congruity level of radiation field and light field, size accuracy of radiation field and collimation field, gantry rotation isocenter check, collimation rotation isocenter check, room laser accuracy check, collimation rotation angle check, couch rotation angle check, and more. In addition, it has proved its practicability in checking isocenter congruity level as real time at the time of simultaneous rotation between gantry and couch that is applied to the non-coplanar field, which had been hard to apply as a device formed of existing flat or cube.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.442-445
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• 2002

We present an algorithm for automatic anatomically adaptive image enhancement of digital chest radiographs. Chest images were exposed using digital radiography system with a 0.143 mm pixel pitch, l4-bit gray levels, and 3121 ${\times}$ 3121 matrix size. A chest radiograph was automatically divided into two classes (lung field and mediastinum) by using a maximum likelihood method. Each pixel in an image was processed using fuzzy domain transformation and enhancement of both the dynamic range and local gray level variations. The lung fields were enhanced appropriately to visualize effectively vascular tissue, the bronchus, and lung tissue, etc as well as pneumothorax and other lung diseases at the same time with the desired mediastinum enhancement. A prototype implementation of the algorithm is undergoing trials in the clinical routine of radiology department of major Korean hospital.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.373-378
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• 2020

For improving interoperability of medical information, health level 7 has initiated the development of a next-generation framework for the exchange of medical information called the Fast health interoperability resources (FHIR). However, there was no attempt to exchange the medical three-dimensional (3D) image with clinical data via FHIR. Thus, we designed a new method. The 3D image to be made from computed tomography was converted to the javascript object notation (JSON) file format, and clinical data was added. We made a test FHIR server, and the client used the postman. The JSON file was attached to the body, and was then transmitted. The transmitted 3D image could be seen through a web browser, and attached clinical data was identified in the source code. This is the first attempt to exchange the medical 3D image. Additional researches will be needed to develop applications or FHIR resources that apply this method.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.285-288
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• 2002

Compression of magnetic resonance images (MRI) has proved to be more difficult than other medical imaging modalities. In an average sized hospital, many tora bytes of digital imaging data (MRI) are generated every year, almost all of which has to be kept. The medical image compression is currently being performed by using different algorithms. In this paper, Fuzzy C-Means (FCM) algorithm is used for the Vector Quantization (VQ). First, a digital image is divided into subblocks of fixed size, which consists of 4${\times}$4 blocks of pixels. By performing 2-D Discrete Cosine Transform (DCT), we select six DCT coefficients to form the feature vector. And using FCM algorithm in constructing the VQ codebook. By doing so, the algorithm can make good time quality, and reduce the processing time while constructing the VQ codebook.