• 제목/요약/키워드: Medical Image

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A Design of Emergency Medical Image Communication System EMICS based on DICOM suitable for Emergency medical system

  • Cho, Jeong-Ran
    • 한국컴퓨터정보학회논문지
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    • 제20권7호
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    • pp.91-97
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    • 2015
  • In this paper, we designed a emergency medical image communication system EMICS added concept of emergency medical image to the existing emergency medical information system based on DICOM. Also we suggested a emergency medical image object EMISPS of EMICS. Using EMICS, the emergency medical technician can work together with emergency doctor. Therefore the patient can take more stable care than existing emergency medical information system. Using EMISPS, the emergency medical technician can get exact situation information of the patient.

Analysis of Trends of Medical Image Processing based on Deep Learning

  • Seokjin Im
    • International Journal of Advanced Culture Technology
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    • 제11권1호
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    • pp.283-289
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    • 2023
  • AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

Medical Image Watermarking Based on Visual Secret Sharing and Cellular Automata Transform for Copyright Protection

  • Fan, Tzuo-Yau;Chao, Her-Chang;Chieu, Bin-Chang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권12호
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    • pp.6177-6200
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    • 2018
  • In order to achieve the goal of protecting medical images, some existing watermark techniques for medical image protection mainly focus on improving the invisibility and robustness properties of the method, in order to prevent unnecessary medical disputes. This paper proposes a novel copyright method for medical image protection based on visual secret sharing (VSS) and cellular automata transform (CAT). This method uses the protected medical image feature as well as VSS and a watermark to produce the ownership share image (OSI). The OSI is used for medical image verification and must be registered to a certified authority. In the watermark extraction process, the suspected medical image is used to generate a master share image (MSI). The watermark can be extracted by combining the MSI and the OSI. Different from other traditional methods, the proposed method does not need to modify the medical image in order to protect the copyright of the image. Moreover, the registered OSI used to verify the ownership and its appearance display meaningful information, facilitating image management. Finally, the results of the final experiment can prove the effectiveness of our method.

질환별 의료영상정보 뷰어 매칭 시스템의 구축 (Construction of Medical Image Information Viewer-Matching System Based by Diseases)

  • 노시형;함규성;정창원;주수종
    • 인터넷정보학회논문지
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    • 제20권5호
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    • pp.37-47
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    • 2019
  • 본 논문은 의료진에게 영상정보를 제공하는 데 있어, 환자의 질병정보와 의료영상뷰어를 매칭 지원해주는 시스템을 구축하는 데 목적을 둔다. 현재 상용화된 의료영상정보시스템들은 대부분 하나의 뷰어로 다양한 질환들의 영상정보들을 제공하거나 호환성이 없는 벤더사의 전용뷰어를 사용하고 있다. 따라서 본 논문에서 질환별로 선택이 가능한 전용뷰어들을 통합한 의료영상정보 뷰어 매칭 시스템, 즉 질환별 뷰어 매칭을 위해 의료영상정보 표준인 DICOM 파일 내부에 메타데이터로 저장되는 태그정보에서 추출한 질환 정보를 기반으로 의료영상 전용뷰어들을 매칭하고, 매칭된 뷰어 상에서 디스플레이하는 시스템을 설계 및 구현하였다. 제안 시스템으로부터 의료영상정보의 검색서비스를 통해 수행성능을 분석하고, 다양한 뷰어들과의 호환 및 뷰어제어가 가능함을 보였다.

목적지 이미지와 의료관광 태도가 몽골인의 한국 의료관광 이용의도에 미치는 영향 (The Effect of Destination Image and Attitude toward Medical Tourism on the Mongolian's Intention to Use Korean Medical Tourism Service)

  • 이은주;신택수;진기남
    • 보건행정학회지
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    • 제24권4호
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    • pp.367-379
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    • 2014
  • Background: Over the last decade, medical tourism industry has grown in Korea. Especially the number of Mongolian medical tourists has increased rapidly. Therefore, the Mongolia is one of the targets for Korea medical tourism. The purpose of this study is to investigate the effects of destination image and expected attributes of medical services on Mongolian's intention to use Korean medical tourism service. Methods: This study empirically collected survey data from Mongolian lived in Mongolia. The study analyzed the data using a PLS model. Results: Our results are as follows. First, the country image didn't significantly have causal effects on expected medical service quality and perceived risk. Second, tourism image (e.g., entertainment, economic feasibility, and local convenience) has significantly causal effects on expected medical service quality and perceived risk. However, tourist site as tourism image didn't significantly have causal effects on expected medical service quality and perceived risk. Third, medical image made a statistically significant effect on expected medical service quality and perceived risk. Fourth, the expected medical service quality showed a significant effect on intention to use Korean medical tourism service. Fifth, the perceived risk of medical tourism showed a significant effect on the reliability of medical tourism, but didn't show a significant effect on the intention to use Korean medical tourism service. Finally, the reliability has a significant effect on the intention to use Korean medical tourism service. Conclusion: From our empirical results, this study concluded that as a strategy attracting Mongolian patients, it is more effective to strengthen Korean hospital image and tourism image than Korean country image.

의료 화상 정보 시스템의 설계 및 구현 (Design and Implementation of Medical Image Information System)

  • 지은미;권용무
    • 대한의용생체공학회:의공학회지
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    • 제15권2호
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    • pp.121-128
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    • 1994
  • In this paper, MIlS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemnted system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression! decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

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의료영상 반자동화 영상처리 시스템 (Semi-Automated Image Processing System for Medical Images)

  • 최우영;서명환;유돈식;윤재훈
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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    • pp.225-228
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    • 2003
  • The purpose of this paper is to develop a semi -automated system for medical image processing with which tissues or organs from medical images can be segmented and classified by people who have basic knowledge of image processing. In addition, the proposed medical image processing system is independent on types of human tissues or images. In this paper, a new semi-automated image processing system with essential image processing functions for medical images is introduced

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적응 양자화를 위한 의료 영상 정보의 변환 부호화에 관한 연구 (A Study Transform Coding of Medical Image Using Adaptive Quantization Method)

  • 한영오;박장춘
    • 대한의용생체공학회:의공학회지
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    • 제10권3호
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    • pp.243-252
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    • 1989
  • In this study, medical images, which are X-ray image and CT image, are compressed by the adam live coding technique. The medical images may be treated as special ones, because they are different from general images in many respects. The statistical characteristics that medical images only have in transform domain are analyzed, and then the improved quantization method is proposed for medical images. For chest X-ray image and CT head image, the better results are obtained by the improved adaptive coding technique.

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Multimodal Medical Image Fusion Based on Sugeno's Intuitionistic Fuzzy Sets

  • Tirupal, Talari;Mohan, Bhuma Chandra;Kumar, Samayamantula Srinivas
    • ETRI Journal
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    • 제39권2호
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    • pp.173-180
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    • 2017
  • Multimodal medical image fusion is the process of retrieving valuable information from medical images. The primary goal of medical image fusion is to combine several images obtained from various sources into a distinct image suitable for improved diagnosis. Complexity in medical images is higher, and many soft computing methods are applied by researchers to process them. Intuitionistic fuzzy sets are more appropriate for medical images because the images have many uncertainties. In this paper, a new method, based on Sugeno's intuitionistic fuzzy set (SIFS), is proposed. First, medical images are converted into Sugeno's intuitionistic fuzzy image (SIFI). An exponential intuitionistic fuzzy entropy calculates the optimum values of membership, non-membership, and hesitation degree functions. Then, the two SIFIs are disintegrated into image blocks for calculating the count of blackness and whiteness of the blocks. Finally, the fused image is rebuilt from the recombination of SIFI image blocks. The efficiency of the use of SIFS in multimodal medical image fusion is demonstrated on several pairs of images and the results are compared with existing studies in recent literature.

Medical Image Compression using Adaptive Subband Threshold

  • Vidhya, K
    • Journal of Electrical Engineering and Technology
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    • 제11권2호
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    • pp.499-507
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    • 2016
  • Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.