• 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 Korean Information Science Society Conference
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• 2001.10b
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• pp.469-471
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• 2001

뇌 MR 영상의 분석을 통해 질환을 자동적으로 진단하고 판별을 하기 위한 전처리 단계에서 정상인의 MR 영상 모델과 현재 고려되어지는 대상 영상과의 비교 작업이 요구된다. 이를 통해 보다 정확한 질병에 대한 근거를 제시함으로서 진단이 가능하게 된다. 이러한 비교 작업을 위해 우선적으로 해결해야 하는 것이 현재 대상 영상이 정상인의 MR 영상 시리즈 중 어느 위치의 영상과 일치하는 지를 판별해야 한다. 실질적으로 뇌 MR 시리즈는 영상의 특징에 따라 크게 몇 개의 그룹으로 분류된다. 따라서 본 논문에서는 매핑을 위한 각 구성 요소의 특징을 추출해 자동으로 뇌 영상의 그룹핑을 함으로써 매핑시 고려되어지는 슬라이드의 범위를 좁혀줄 뿐만 아니라 영상의 질에 따라 부분적인 손실이 있다 하더라도 전후 관계 정보를 이용하여 유추가 가능한 방법을 제시한다. 800여개의 T2 MR 강조 영상에 대해서 실험을 행하여 비교적 정확한 그룹핑 결과를 유도할 수 있었음을 확인하였다.

• Investigative Magnetic Resonance Imaging
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• v.13 no.2
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• pp.190-194
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• 2009

Generalized lymphangiomatosis is a rare congenital malformation of the lymphatics. CT and MR scan have been used to evaluate lymphangiomas, which appear as large multicystic fluid-filled masses. CT and MR Imaging findings are often helpful in distinguishing lymphangiomas from various vascular disorders. We report the findings of CT, MRI and bone scan in a patient with generalized cystic lymphangiomatosis. Whole body 3.0-T MR scan using STIR sequence with a larger FOV could detect the additional lesions that were not seen at other imaging modalities. We believe that whole body 3.0 T MR imaging is a good modality to evaluate the extent of the disease and following up the patients with the generalized cystic lymphangiomatosis.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.45-51
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• 2005

This paper emphasizes on the accomplishment of compensated proton density image and T2 weighted image taken from the shrinkage surface of the Brain. From the images, the Brain's surface shrinkage in the normal image and the surface shrinkage in the abnormal image can be observed. After the separation of white matter, gray matter, and CSF, this algorithm calculates the volume of each of them automatically. Results are subdivided into particular ages and saved in the database to be analyzed and to be processed statistically. Therefore, by using this algorithm the normal and abnormal stages can be detected in the early stages to diagnose. This result easily discernment Alzheimer patient and is useful for Alzheimer diagnostic and early detection.

• Journal of the Korean Society of Radiology
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• v.83 no.2
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• pp.420-424
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• 2022

Fibrous hamartoma of infancy in the middle ear is extremely rare. We report the case of a 26-month-old male patient who presented with a mass in the left middle ear. A temporal bone CT scan showed complete opacification of the left middle ear and mastoid air cells without ossicular erosion. On MRI, the mass revealed heterogeneous signal intensities indicative of fat and fibrous components. A definitive diagnosis was made postoperatively based on the histological results. Although rare, fibrous hamartoma of infancy should be considered as a differential diagnosis of a middle ear mass during childhood.

• Journal of The Korean Radiological Technologist Association
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• v.25 no.1
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• pp.109.2-110
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• 1999

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.177-178
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• 2012

응급실을 내원한 중증외상 환자로 등록된 환자 중 중등도 분석의 객관상과 진단을 위한 영상의학검사을 시행 받은 환자를 대상으로 생존군과 사망군을 비교하여 생존의 영향을 미치는 인자에 대하여 알아보고자 하며 진단적 영상의학 검사의 유용성과 적절한 영상의학 검사의 시행시점을 알아보기 위한 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1153-1156
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• 2005

PACS system developments for improve of diagnosis efficiency for hospital duty efficiency and patients through various medical image diagnosis device. PACS system studies for nonfilm hospital, but still, image filtering technology Present high accuracy take a photograph image be not enough. On study image processing part is very importance. The fittest of image processing in order to using simple and essential filter try to improvrnent. The future, diagnosis of patients decide accuracy, low cost based Digital XRay system will be using.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.307-310
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• 2021

In the recent years, studies using Computer-Aided Diagnostics(CAD) have been actively conducted, such as signal and image processing technology using breast ultrasound images, automatic image optimization technology, and automatic detection and classification of breast masses. As computer diagnostic technology is developed, it is expected that early detection of cancer will proceed accurately and quickly, reducing health insurance and test ice for patients, and eliminating anxiety about biopsy. In this paper, a quantitative analysis of tumors was conducted in ultrasound images using a gray level co-occurrence matrix(GLCM) to experiment with the possibility of use for computer assistance diagnosis.

• Journal of the Korean Society of Radiology
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• v.84 no.6
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• pp.1233-1243
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• 2023

Percutaneous ultrasound-guided biopsy is useful for the pathologic confirmation of variable body lesions to establish diagnostic and therapeutic approaches. However, deep pelvic lesions are a challenge for pathologic diagnoses because of the presence of the bowel, bladder, major vessels, and pelvic bones which make a percutaneous approach difficult and dangerous. In female, the vagina is elastic and near the pelvic internal organs. Therefore, transvaginal ultrasound may serve as an effective and safe guide for the pathologic diagnosis of pelvis lesions. This review aimed to introduce the indications for, and the method of transvaginal ultrasoundguided biopsy, and to describe the reported diagnostic accuracy and safety.