• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.573-576
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• 2017

본 연구는 홍삼 등급판정 과정에서 내부 조직 치밀도 분석을 위해 의료 영상 분석 방법을 이용하여 적외선 영상 측정기기를 개발하였다. 기존 홍삼 내부분석방법은 수동으로 암실환경에서 강한 조명을 홍삼에 투과하여 사람 눈으로 직접 판별하는 과정을 거친다. 이러한 기존 검사 과정은 작업 비효율성과 불균일한 검사기준으로 제품 품질 신뢰도 저하의 단점을 가져온다. 이러한 문제점을 해결하기 위해 본 연구는 적외선 조명환경에서 자동 측정이 가능한 홍삼 내부 측정기기를 개발하였다. 개발된 장치는 홍삼의 빛 투과 특성을 응용한 920nm 파장대역의 적외선 조명기구, 조명 제어회로, 적외선 대역 촬영이 가능한 영상 측정 카메라 장치, $0.9^{\circ}$의 간격으로 $360^{\circ}$ 홍삼 영상취득이 가능한 회전 엑츄에이터로 구성이 된다. 본 연구에서 제안 하는 홍삼 단층 영상분석 방법은, 홍삼을 $0.9^{\circ}$ 간격으로 회전시키어 $360^{\circ}$ 홍삼 내부영상을 취득하여 라돈 변환(Radon transform)을 통해 사이노그램(Sinogram)으로 재구성 하였으며, 역 라돈 변환(Inverse Radon transform)을 통해 단층 영상복원(Back-projection)알고리즘을 구현하였다. 이 결과 홍삼을 절단하지 않고 홍삼 내부 단면영상 획득이 가능하였으며 내공(內空), 내백(內白)의 유무를 판단하고 직경을 파악할 수 있었다. 이를 토대로 등급 판별 공식을 산출하면 신뢰성 있는 홍삼 등급 자동화 측정기기를 개발할 수 있을 것으로 기대된다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.500-508
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• 2008

For efficient compatible system between medical clinics, the medical information has to be built on a standardized protocol such as a HL7 for text data and a DICOM for image data. But it is difficult to exchange information between medical clinics because the systems and softwares are different and also a structure of data and a type of code. Therefore we analyze a structure of DICOM file and design an integrated database for effective information sharing and exchange. The WISD system suggested in this paper separate the DICOM file transmitted by medical clinics to text data and image data and store it in the integrated DB(database) by standardized protocol respectively. It is very efficient that each medical clinic can search and exchange information by web browser using the suggested system. The WISD system can not only search and control of image data and patient information through integrated database and internet, but share medical information without extra charge like construction of new system.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.38-39
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• 2019

본 논문은 R-CDM 의료영상정보를 기반으로 ELK Stack 기술을 적용하여 획득한 데이터의 분석 결과를 시각화하기 위한 시스템에 대해 기술한다. 제안한 시스템은 의료 빅데이터의 검색, 수집 그리고 분석 결과를 모니터링 할 수 있으며, 특히 대량의 데이터의 변화와 데이터간의 차이를 확인할 수 있다. 본 연구에서 제안한 시스템은 수집된 의료영상 빅데이터에 대해 적용하여 현황과 처리결과 그리고 실시간 분석결과에 대한 모니터링을 통해 관리의 효율성을 높여 실시간 검색 및 분석 서비스 분야에 기여할 것으로 기대된다.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.117-120
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• 2008

동영상의 다중 물체 인식 및 추적은 의료영상이나 무인 주행 시스템 등의 응용분야에서 중요성이 높아지고 있다. 본 논문에서는 스포츠 동영상의 다중 물체를 인식 및 추적하기 위해 칼만필터 알고리즘을 사용한다. 칼만필터 알고리즘을 이용한 물체의 이동 궤적 관리를 통해 표적 겹침 현상에 대한 추적 실패를 극복하도록 하였다. 표적 겹침이 일어나는 동영상을 입력 영상으로 이용하여 제안한 실시간 시뮬레이터의 추적 성능을 분석하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.663-669
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• 2017

In diagnostic medical imaging, it is essential to reduce the scattered radiation for the high medical image quality and low patient dose. Therefore, in this study, the influence of the scattered radiation on medical images was analyzed as the tube voltage increases. For this purpose, ANSI chest phantom was used to measure the scattering ratio, and the scattering effect on the image quality was investigated by RMS evaluation, RSD and NPS analysis. It was found that the scattering ratio with increasing x-ray tube voltage gradually increased to 48.8% at 73 kV tube voltage and to 80.1% at 93 kV tube voltage. As a result of RMS analysis for evaluating the image quality, RMS value according to increase of tube voltage was increased, resulting in low image quality. Also, the NPS value at 2.5 lp/mm spatial frequency was increased by 20% when the tube voltage was increased by 93 kV compared to the tube voltage of 73 kV. From this study, it can be seen that the scattering radiation have a significant effect on the image quality according to the increase of x-ray tube voltage. The results of this study can be used as basic data for the improvement of medical imaging quality.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.401-408
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• 2006

In this paper, we propose a new class of segmentation technique for feature extraction based on the statistical and regional classification at each vertical or horizontal line of digital image data. Data is processed and clustered at each line, different from the point or space process. They are designed to segment gray-scale sectional images using a horizontal and vertical line process due to their statistical and property differences, and to extract the feature. The techniques presented here show efficient results in case of the gray level overlap and not having threshold image. Such images are also not easy to be segmented by the global or local threshold methods. Line pixels inform us the sectionable data, and can be set according to cluster quality due to the differences of histogram and statistical data. The total segmentation on line clusters can be obtained by adaptive extension onto the horizontal axis. Each processed region has its own pixel value, resulting in feature extraction. The advantage and effectiveness of the line-cluster approach are both shown theoretically and demonstrated through the region-segmental carotid artery medical image processing.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.282-285
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• 2002

의료영상에서 윤곽선의 추출은 관심영역 대한 객관적인 수치 즉 면적, 부피, 장단축의 길이 등을 분석하고 3차원 재구성을 위해 선행되어야 하는 중요한 과정이다. 현재 윤곽선 추출에 대한 않은 방법들이 개발 중에 있으나 이 방법들은 한계를 지니고 있어 더 높은 수준의 처리가 요구된다. 본 논문에서는 active contour model(snake)을 이용하여 MR뇌 영상에서 종양을 추출하였다. Snake의 에너지 최적화 문제를 dynamic programming을 사용하여 개선하였으며 canny edge detection을 이용하여 잡음에 덜 민감하도록 하였다.