• Title/Summary/Keyword: diagnostic medical image

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System Implementation for Mobile-Based Diagnostic Medical Image Service (모바일 진단의료영상 서비스를 위한 시스템 구현)

  • Kim, Yong-Soo;Jeon, Joonhyeon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38B no.11
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    • pp.870-878
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    • 2013
  • The objective of this paper is to develop mobile-based PACS(Picture Archiving Communication System: mPACS) for diagnostic medical image service available via Android-based mobile smartphone. The proposed mPACS provides an integrated platform for mobile application of diagnostic medical images stored in hospital PACS, and allows the smartphone to store, retrieve, manipulate and transfer the diagnostic medical images. Then, the mPACS platform includes the following features for use in the Android framework (i. e., diagnostic medical image processing) : transfer protocols between PACS, mPACS and smartphone, image format converter, JPEG and JPEG2000 coders, text and avatar search, and etc. This mPACS is shown to be useful and effective in providing a solution for mobile-based diagnostic medical image service.

Medical Image Compression using Adaptive Subband Threshold

  • Vidhya, K
    • Journal of Electrical Engineering and Technology
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    • v.11 no.2
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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.

Implementation of Medical Diagnostic Information System and Conformance Test of Medical Image in Mobile Environment (모바일 환경에서 의료 진단 정보 시스템의 구현 및 의료 영상의 적합성 평가)

  • Cho, Chung-Ho;Kim, Gwang-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.6
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    • pp.713-720
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    • 2015
  • As the hand-held mobile devices are widely used, they are recently coming into convergence with medical diagnostic systems. Furthermore, the wireless mobile Internet and the various kinds of communication devices are rapidly coming into wide use converging with medical technology. The mobile communication environments can make people get more health care services beyond space and time. In this paper, we implement and evaluate the mobile client and the medical diagnostic information server for transmitting, searching and updating the medical diagnostic information. The DICOM CT image and the compressed JPEG 2000 CT image are statistically evaluated by t-test performance whether those images are clinically appropriate. In the case of the DICOM CT image, we realize that the average value is relatively more appropriate to the clinical diagnosis than the JPEG 2000 CT image.

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

  • 지은미;권용무
    • Journal of Biomedical Engineering Research
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    • v.15 no.2
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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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The effects of noise reduction, sharpening, enhancement, and image magnification on diagnostic accuracy of a photostimulable phosphor system in the detection of non-cavitated approximal dental caries

  • Kajan, Zahra Dalili;Davalloo, Reza Tayefeh;Tavangar, Mayam;Valizade, Fatemeh
    • Imaging Science in Dentistry
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    • v.45 no.2
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    • pp.81-87
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    • 2015
  • Purpose: Contrast, sharpness, enhancement, and density can be changed in digital systems. The important question is to what extent the changes in these variables affect the accuracy of caries detection. Materials and Methods: Forty eight extracted human posterior teeth with healthy or proximal caries surfaces were imaged using a photostimulable phosphor (PSP) sensor. All original images were processed using a six-step method: (1) applying "Sharpening 2" and "Noise Reduction" processing options to the original images; (2) applying the "Magnification 1:3" option to the image obtained in the first step; (3) enhancing the original images by using the "Diagonal/"option; (4) reviewing the changes brought about by the third step of image processing and then, applying "Magnification 1:3"; (5) applying "Sharpening UM" to the original images; and (6) analyzing the changes brought about by the fifth step of image processing, and finally, applying "Magnification 1:3." Three observers evaluated the images. The tooth sections were evaluated histologically as the gold standard. The diagnostic accuracy of the observers was compared using a chi-squared test. Results: The accuracy levels irrespective of the image processing method ranged from weak (18.8%) to intermediate (54.2%), but the highest accuracy was achieved at the sixth image processing step. The overall diagnostic accuracy level showed a statistically significant difference (p=0.0001). Conclusion: This study shows that the application of "Sharpening UM" along with the "Magnification 1:3" processing option improved the diagnostic accuracy and the observer agreement more effectively than the other processing procedures.

Study on Body Constitution and Disease Symptoms and Signs (논체질여병증(论体质与病证))

  • Cui, Zheng-Zhi;Cui, Ming-Hua
    • Journal of Korean Medical classics
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    • v.22 no.4
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    • pp.241-247
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    • 2009
  • Body constitution research in Korean traditional medicine adopt the diagnosis and treatment theory of "image-differentiation[body constitution differentiation, disease differentiation] in combination with syndrome differentiation diagnostic model and symptoms and signs of herbal property belong to image" as its core, which is key national medical science research project of State Administration of Traditional Chinese Medicine, the project brought up 4 key scientific problem ? body constitution differentiation theory, correlation theory of body constitution and disease, body constitution adjustable theory and symptoms and signs of herbal property belong to image theory. In body constitution pathology, it brought up "correlation between body constitution and symptoms", "differentiation between body constitution and symptoms" which increase the diagnostic level and diagnostic accuracy rate. In the condition of pathology, it obviously has low reliability according to body constitution differentiation, sometimes happen the description not comply with body constitution and disease symptoms, which lead to decrease the clinic diagnostic and treatment level, treatment effect not satisfying too. Now taking 4 key scientific achievement as criterion to illustrate the body constitution and disease symptoms.

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Development of Automated Rapid Influenza Diagnostic Test Method Based on Image Recognition (영상 인식 기반 신속 인플루엔자 자동 판독 기법 개발)

  • Lee, Ji Eun;Joo, Yoon Ha;Lee, Jung Chan
    • Journal of Biomedical Engineering Research
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    • v.40 no.3
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    • pp.97-104
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    • 2019
  • To examine different types of influenza diagnostic test kits automatically, automated rapid influenza diagnostic test method based on image recognition is proposed in this paper. First, the proposed methods classify a variety of the rapid influenza diagnostic test kit based on support vector machine that analyzes the kits' feature point. Then, to improve the accuracy of test, the proposed methods match the histogram of both the target image of influenza kit and the input image of influenza kit for minimizing the effect of environment factors, such as lighting and exposure variations. And, to minimize the effect from composition of the hand-helds devices, the proposed methods extract the feature point and match point-by-point between target image of influenza kit and input image of influenza kit. Experimental results of 124 experimental group show that the proposed methods significantly have effectiveness, which shows 90% accuracy in moderate antigen, for the preliminary examination of influenza, and provides the opportunity for taking action against influenza.

심전도

  • 서병설
    • Journal of Biomedical Engineering Research
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    • v.9 no.1
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    • pp.131-134
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    • 1988
  • In this paper, MIIS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemented 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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