• Journal of the Korean Society for Precision Engineering
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• v.25 no.1
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• pp.63-71
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• 2008

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.197-206
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• 2009

The medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image classification and retrieval system is necessary. The medical image classification and retrieval system can improve efficiency in a medical diagnosis by providing disease-related images and can be useful in various medical practices by checking diverse cases. However, it is difficult to understand the meanings contained in images because the existing image classification and retrieval system has handled superficial information only. Therefore, a medical image classification system which can classify medical images by analyzing the relation among the elements of the image as well as the superficial information has been required. In this paper, we propose the method for learning and classification of brain MRI, in which the superficial information as well as the spatial information extracted from images are used. The superficial information of images, which is color, shape, etc., is called low-level image information and the logical information of the image is called high-level image information. In extracting both low-level and high-level image information in this paper, the anatomical names and structure of the brain have been used. The low-level information is used to give an anatomical name in brain images and the high-level image information is extracted by analyzing the relation among the anatomical parts. Each information is used in learning and classification. In an experiment, the MRI of the brain including disease have been used.

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.77-77
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• 2003

목적： 한국인의 인체 모델링을 연구하는 과정에서 인체의 부위별로 원하고자하는 부분과 영상 분할 할 수 있는 최적의 영상 분할 알고리듬을 개발하여 3차원 해부학적 영상을 재구현 하는데 그 목적이 있다.

• Korean Journal of Digital Imaging in Medicine
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• v.3 no.1
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• pp.86-90
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• 1997

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.69-78
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• 2016

Ischemic stroke is a disease that the brain tissues cannot function by reducing blood flow due to thrombosis or embolisms. Due to the nature of the disease, it is most important to identify the status of cerebral vessel and the medical images are necessarily used for its diagnosis. Among many indicators, brain MRI is most widely utilized because experts can effectively obtain the semantic information such as cerebral anatomy aiding the diagnosis with it. However, in case of emergency diseases like ischemic stroke, even though a intelligent system is required for supporting the prompt diagnosis and treatment, the current systems have some difficulties to provide the information of medical images intuitively. In other words, as the current systems have managed the medical images based on the basic meta-data such as image name, ID and so on, they cannot consider semantic information inherent in medical images. Therefore, in this paper, to provide core information like cerebral anatomy contained in brain MRI, we suggest a template-driven medical images mapping method. The key idea of the method is defining the mapping characteristics between anatomic feature and representative images by using template images that can be representative of the whole brain MRI image set and revealing the semantic relations that only medical experts can check between images. With our method, it will be possible to manage the medical images based on semantic.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1273-1285
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• 2022

Purpose MR neurography (MRN) is an imaging technique optimized to visualize the peripheral nerves. This review aimed to discover an optimized protocol for MRN of the lumbosacral plexus (LSP) and identify evidence for the clinical benefit of lumbosacral plexopathies. Materials and Methods We performed a systematic search of the two medical databases until September 2021. 'Magnetic resonance imaging', 'lumbosacral plexus', 'neurologic disease', or equivalent terms were used to search the literature. We extracted information on indications, MRN protocols for LSP, and clinical efficacy from 55 studies among those searched. Results MRN of the LSP is useful for displaying the distribution of peripheral nerve disease, guiding perineural injections, and assessing extraspinal causes of sciatica. Three-dimensional short-tau inversion recovery turbo spin-echo combined with vascular suppression is the mainstay of MRN. Conclusion Future work on the MRN of LSP should be directed to technical maturation and clinical validation of efficacy.

• Korean Journal of Digital Imaging in Medicine
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• v.17 no.1
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• pp.43-48
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• 2015

Intracrnial 3D TOF MR angiography was performed in 30 normal volunteers with both 1.5 and 3.0 T MRI system with high resolutions. Used Voxel sizes were $0.39{\times}0.39{\times}0.2$(1.5 T) and $0.19{\times}0.19{\times}0.35$(3.0 T), respectively. High image quality and depiction of small vessel branches were equality demonstrated with 1.5 T and 3.0 T HR TOF MRA(p<0.05). Intracranial high resolution TOF MRA with 1.5 T and 3.0 T provides high diagnostic information with having merits and demerits in depiction of vascular branches.

• Journal of the Korea Computer Graphics Society
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• v.2 no.2
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• pp.21-28
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• 1996

The nature of complexity of medical images makes them difficult to segment using standard techniques. Therefore the usual approaches to segment images continue to predominantly involve manual interaction. But it tediously consumes a good deal of time and efforts of the experts. Hereby a nonmanual parameters estimation which can replace the manual interaction is needed to solve the problem of redundant manual works for an image segmentation. This paper attempts to estimate parameters for an image region segmentation using Scale Space Filtering. This attempt results in estimating the number of regions, their boundary and each representatives to be segmented 2-dimensionally and 3-dimensionally. Using this algorithm, we may diminish the problem of wasted time and efforts for finding prerequisite segmentation parameters, and lead the relatively reasonable result of region segmentation.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.228-231
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• 2004

의학 분야에서 의료 영상 데이터에 해당하는 컴퓨터 단층 찰영(CT. Computer Tomography), 자기 공명 영상법 (MRI : Magnetic Resonance Imaging)둥의 데이터 등이 정확하고 신속한 진단ㆍ관리를 위하여 의료 영상 데이터 중에서 관심의 대상이 되는 영역은 무손실 압축 기법을 수행하고, 그외의 지역은 움직임 보상 방식을 사용하여 압축하는 방식을 제안하고 실험하였다. 그 결과 기존의 손실 압축 기법에 비하여 더 낮은 비트율로 효율적인 압축을 수행하였다.

• 전기의세계
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• v.38 no.8
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• pp.19-25
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• 1989

현재 전세계적으로 퍼져있는 NMR-CT 시스템의 수를 살펴보면 약 370여기가 설치.운영되고 있으며 앞으로 계속 늘어날 전망이다. 국내에서는 1988 한국과학기술원과 금성통신에 의해 자체 개발된 2.0 Tesla 강자장 시스템이 최초로 서울대학병원에 설치 가동된 이래 여러병원에서 시스템들이 설치중에 있다. 첨단의로 진단장치로서의 핵자기 공명 영상법은 그 영상을 통하여 기존의 진단 장치보다 우월함을 증명하고 있으며 초음파 검사나 동위원소 검사 및 X선 전산화 단층 촬영술들을 장점을 두루 지니면서 그 영상법의 다양성 때문에 앞으로의 연구 및 발전에 대한 전망은 아주 밝다고 할 수 있다. 따라서 앞으로의 종합 영상 의료 진단 장치는 이 NMR-CT가 중심이 되어 발전할 것이라고 단언해도 무리한 생각은 아닐 것이다.