• Title/Summary/Keyword: Medical Diagnostic Image

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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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Performance Evaluation of the Developed Diagnostic Multi-Leaf Collimator and Implementation of Fusion Image of X-ray Image and Infrared Thermography Image (개발한 진단용 다엽조리개 성능평가 및 X선영상과 적외선체열영상의 융합영상 구현)

  • Kwon, Soon-Mu;Shim, Jae-Goo;Chon, Kwon-Su
    • Journal of radiological science and technology
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    • v.42 no.5
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    • pp.365-371
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    • 2019
  • We have developed and applied a diagnostic Multi-Leaf Collimator (MLC) to optimized the X-ray field in medical imaging and the usefulness evaluated through the fusion of infrared image and X-ray image acquired by infrared camera. The hand and skull radiography with multi-leaf collimator(MLC) showed significant area dose reductions of 22.9% and 31.3% compared to ARC and leakage dose was compliant with KS A 4732. Also scattering doses of 50 cm and 100 cm showed a significant decrease to confirm the usefulness of MLC. It was confirmed that the fusion of infrared images with an adjustable degree of transparency was possible in the X-ray images. Therefore, fusion of anatomical information with physiological convergence is expected to contribute and improvement of diagnostic ability. In addition, the feasibility of convergence X-ray imaging and DITI devices and the possibility of driving MLC with infrared images were confirmed.

Parametric Image Generation and Enhancement in Contrast-Enhanced Ultrasonography (조영증강 초음파 진단에서 파라미터 영상 생성 및 개선 기법)

  • Kim, Shin-Hae;Lee, Eun-Lim;Jo, Eun-Bee;Kim, Ho-Joon
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.4
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    • pp.211-216
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    • 2017
  • This paper proposes image processing techniques that improve usability and performance in a diagnostic system of the contrast-enhanced ultrasonography. For a methodology for visualizing diagnostic parameter data in an ultrasonic medical image, an expression of transition time data with successive pixel values and a method of generating a lesion diagnostic parameter image with four categorized values are presented. We also introduce a MRF-based image enhancement technique to eliminate noises from generated parametric images. Such parametric image generation technique can overcome the difficulty of discriminating dynamic change in patterns in the ultrasonography. The technique clarifies the contour of the region in the original image and facilitates visual determination of the characteristics of the lesion through four colors. With regard to this MRF-based image enhancement, we define the energy function of consecutive pixel values and develop a technique to optimize it, and the usability of the proposed theory is examined through experiments with medical images.

3D Segmentation of a Diagnostic Object in Ultrasound Images Using LoG Operator (초음파 영상에서 LoG 연산자를 이용한 진단 객체의 3차원 분할)

  • 정말남;곽종인;김상현;김남철
    • Journal of Biomedical Engineering Research
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    • v.24 no.4
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    • pp.247-257
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    • 2003
  • This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

A method for ultrasound image edge enhancement by using Probabilistic edge map (초음파 진단영상 대조도 개선을 위한 확률 경계 맵을 이용한 연구)

  • Choi, Woo-hyuk;Park, Won-hwan;Park, Sungyun
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.20 no.1
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    • pp.37-44
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    • 2016
  • Ultrasonic imaging is the most widely modality among modern imaging device for medical diagnosis. Nevertheless, medical ultrasound images suffer from speckle noise and low contrast. In this paper, we propose probabilistic edge map for ultrasound image edge enhancement using automatic alien algorithm. The proposed method used applied speckle reduced ultrasound imaging for edge improvement using sequentially acquired ultrasound imaging. To evaluate the performance of method, the similarity between the reference and edge enhanced image was measured by quantity analysis. The experimental results show that the proposed method considerably improves the image quality with region edge enhancement.

Comprehensive Updates in the Role of Imaging for Multiple Myeloma Management Based on Recent International Guidelines

  • Koeun Lee;Kyung Won Kim;Yousun Ko;Ho Young Park;Eun Jin Chae;Jeong Hyun Lee;Jin-Sook Ryu;Hye Won Chung
    • Korean Journal of Radiology
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    • v.22 no.9
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    • pp.1497-1513
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    • 2021
  • The diagnostic and treatment methods of multiple myeloma (MM) have been rapidly evolving owing to advances in imaging techniques and new therapeutic agents. Imaging has begun to play an important role in the management of MM, and international guidelines are frequently updated. Since the publication of 2015 International Myeloma Working Group (IMWG) criteria for the diagnosis of MM, whole-body magnetic resonance imaging (MRI) or low-dose whole-body computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography/CT have entered the mainstream as diagnostic and treatment response assessment tools. The 2019 IMWG guidelines also provide imaging recommendations for various clinical settings. Accordingly, radiologists have become a key component of MM management. In this review, we provide an overview of updates in the MM field with an emphasis on imaging modalities.

Impact of the Liver Imaging Reporting and Data System on Research Studies of Diagnosing Hepatocellular Carcinoma Using MRI

  • Yura Ahn;Sang Hyun Choi;Jong Keon Jang;So Yeon Kim;Ju Hyun Shim;Seung Soo Lee;Jae Ho Byun
    • Korean Journal of Radiology
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    • v.23 no.5
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    • pp.529-538
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    • 2022
  • Objective: Since its introduction in 2011, the CT/MRI diagnostic Liver Imaging Reporting and Data System (LI-RADS) has been updated in 2014, 2017, and 2018. We evaluated the impact of CT/MRI diagnostic LI-RADS on liver MRI research methodology for the diagnosis of hepatocellular carcinoma (HCC). Materials and Methods: The MEDLINE, EMBASE, and Cochrane databases were searched for original articles reporting the diagnostic performance of liver MRI for HCC between 2011 and 2019. The MRI techniques, image analysis methods, and diagnostic criteria for HCC used in each study were investigated. The studies were classified into three groups according to the year of publication (2011-2013, 2014-2016, and 2017-2019). We compared the percentage of studies adopting MRI techniques recommended by LI-RADS, image analysis methods in accordance with the lexicon defined in LI-RADS, and diagnostic criteria endorsed by LI-RADS. We compared the pooled sensitivity and specificity between studies that used the LI-RADS and those that did not. Results: This systematic review included 179 studies. The percentages of studies using imaging techniques recommended by LI-RADS were 77.8% for 2011-2013, 85.7% for 2014-2016, and 84.2% for 2017-2019, with no significant difference (p = 0.951). After the introduction of LI-RADS, the percentages of studies following the LI-RADS lexicon were 0.0%, 18.4%, and 56.6% in the respective periods (p < 0.001), while the percentages of studies using the LI-RADS diagnostic imaging criteria were 0.0%, 22.9%, and 60.7%, respectively (p < 0.001). Studies that did not use the LI-RADS and those that used the LIRADS version 2018 showed no significant difference in sensitivity and specificity (86.3% vs. 77.7%, p = 0.102 and 91.4% vs. 89.9%, p = 0.770, respectively), with some difference in heterogeneity (I2 = 94.3% vs. 86.7% in sensitivity and I2 = 86.6% vs. 53.2% in specificity). Conclusion: LI-RADS imparted significant changes in the image analysis methods and diagnostic criteria used in liver MRI research for the diagnosis of HCC.