• Title/Summary/Keyword: Pathological Information System

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Image Edge Detection Technique for Pathological Information System (병리 정보 시스템을 위한 이미지 외곽선 추출 기법 연구)

  • Xiao, Xie;Oh, Sangyoon
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.10
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    • pp.489-496
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    • 2016
  • Thousands of pathological images are produced daily per hospital and they are stored and managed by a pathology information system (PIS). Since image edge detection is one of fundamental analysis tools for pathological images, many researches are targeted to improve accuracy and performance of image edge detection algorithm of HIS. In this paper, we propose a novel image edge detection method. It is based on Canny algorithm with adaptive threshold configuration. It also uses a dividing ruler to configure the two threshold instead of whole image to improve the detection ratio of ruler itself. To verify the effectiveness of our proposed method, we conducted empirical experiments with real pathological images(randomly selected image group, image group that was unable to detect by conventional methods, and added noise image group). The results shows that our proposed method outperforms and better detects compare to the conventional method.

Diet-Right: A Smart Food Recommendation System

  • Rehman, Faisal;Khalid, Osman;Haq, Nuhman ul;Khan, Atta ur Rehman;Bilal, Kashif;Madani, Sajjad A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.6
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    • pp.2910-2925
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    • 2017
  • Inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to lack of concise information about healthy diet, people have to rely on medicines instead of taking preventive measures in food intake. Due to diversity in food components and large number of dietary sources, it is challenging to perform real-time selection of diet patterns that must fulfill one's nutrition needs. Particularly, selection of proper diet is critical for patients suffering from various diseases. In this article, we highlight the issue of selection of proper diet that must fulfill patients' nutrition requirements. To address this issue, we present a cloud based food recommendation system, called Diet-Right, for dietary recommendations based on users' pathological reports. The model uses ant colony algorithm to generate optimal food list and recommends suitable foods according to the values of pathological reports. Diet-Right can play a vital role in controlling various diseases. The experimental results show that compared to single node execution, the convergence time of parallel execution on cloud is approximately 12 times lower. Moreover, adequate accuracy is attainable by increasing the number of ants.

An analysis of a statistical difference of acoustic Parameters' distribution between normal voice and pathological voice (병적 음성과 정상 음성의 음향학적 파라미터 분포에 대한 통계적 분석)

  • 김용주;권순복;김기련;신민철;조철우;왕수건
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.249-252
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    • 2001
  • The most basic means of communication among humans is a voice. Without speaking of voice technologies, we found it is important and convenient to use a voice in everyday life. But. in consideration to speech recognition systems, we can't always desire a normal voice input as input signal to the system. Generally speaking. a pathological voice as against a normal which is a voice with a problem in the larynx. could be also special case of input voice. Of course, but the distortion of a speech signal by environmental effects i.e., noise or transmission channel was a raised problem. we will take up a pathological voices with laryngeal disease which is essential distortion factor in voice. Also, we are to find out the difference of acoustic parameters distribution between normal and pathological voice by a statistical method in our research.

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A Study on Bureaucratic System of Library Organization (도서관조직의 관료제에 관한 연구)

  • Kim Jung Soh
    • Journal of the Korean Society for Library and Information Science
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    • v.15
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    • pp.95-117
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    • 1988
  • The purpose of this research is to analyze the characteristics of bureaucracy on library structure and then to review typologies and parthological phenomena, their following aspects of securities of library. The most important characteristics of library bureaucracy is its strong speciality and needs regurality and its hierarchic power systems. We can separate its systems from machine bureaucracy and professional bureaucracy. and the bureaucratic systems are attended with controls, observance of rules, and pathological phenomena by entrusting sombody with power, etc. To revise these pathological phenomena of the library structure, the following items must be included. First, librarians should be given with professional authority. Second, all librarians should participate in decision-making. Thirdly, it is desirable that the communication should upward communication and lateral communication much more preferable than downward communication. Fourthly, professional. librarians must be maintained with compensation systems. Fifthly, they must be 'PROACTIVE LIBRARIAN' who cope with any given circumstances.

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Telemedicine Software Application

  • UNGUREANU, Ovidiu Costica;POPESCU, Marius-Constantin;CIOBANU, Daniela;UNGUREANU, Elena;SARLA, Calin Gabriel;CIOBANU, Alina-Elena;TODINCA, Paul
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.171-180
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    • 2021
  • Currently, hospitals and medical practices have a large amount of unstructured information, gathered in time at each ward or practice by physicians in a wide range of medical branches. The data requires processing in order to be able to extract relevant information, which can be used to improve the medical system. It is useful for a physician to have access to a patient's entire medical history when he or she is in an emergency situation, as relevant information can be found about the patient's problems such as: allergies to various medications, personal history, or hereditary collateral conditions etc. If the information exists in a structured form, the detection of diseases based on specific symptoms is much easier, faster and with a higher degree of accuracy. Thus, physicians may investigate certain pathological profiles and conduct cohort clinical trials, including comparing the profile of a particular patient with other similar profiles that already have a confirmed diagnosis. Involving information technology in this field will change so the time which the physicians should spend in front of the computer into a much more beneficial one, providing them with the possibility for more interaction with the patient while listening to the patient's needs. The expert system, described in the paper, is an application for medical diagnostic of the most frequently met conditions, based on logical programming and on the theory of probabilities. The system rationale is a search item in the field basic knowledge on the condition. The web application described in the paper is implemented for the ward of pathological anatomy of a hospital in Romania. It aims to ease the healthcare staff's work, to create a connection of communication at one click between the necessary wards and to reduce the time lost with bureaucratic proceedings. The software (made in PHP programming language, by writing directly in the source code) is developed in order to ease the healthcare staff's activity, being created in a simpler and as elegant way as possible.

Developing a Knowledge Modeling System for Reusable Pathological Ontologies (재사용 가능한 병리 온톨로지 구축을 위한 지식 모델링 시스템 개발)

  • 하병현;김홍기;이재일;김명기;강석호
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.64-66
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    • 2003
  • 본 연구에서는 병리진단 시 참여자들의 지식과 의견을 효과적으로 교환할 수 있는 온톨로지를 구축하고. 구축한 온톨로지를 기반으로 진단절차를 전산화하는 PathOnt 시스템을 개발하였다. PathOnt 시스템은 재활용 가능한 온톨로지를 사용함으로써 여러 전문가들 간의 의사소통과 지식공유의 문제를 극복하였으며, 다 층위로 구현하여 웹 어플리케이션으로써의 비전도 제시하였다

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Feature Extraction of Non-proliferative Diabetic Retinopathy Using Faster R-CNN and Automatic Severity Classification System Using Random Forest Method

  • Jung, Younghoon;Kim, Daewon
    • Journal of Information Processing Systems
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    • v.18 no.5
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    • pp.599-613
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    • 2022
  • Non-proliferative diabetic retinopathy is a representative complication of diabetic patients and is known to be a major cause of impaired vision and blindness. There has been ongoing research on automatic detection of diabetic retinopathy, however, there is also a growing need for research on an automatic severity classification system. This study proposes an automatic detection system for pathological symptoms of diabetic retinopathy such as microaneurysms, retinal hemorrhage, and hard exudate by applying the Faster R-CNN technique. An automatic severity classification system was devised by training and testing a Random Forest classifier based on the data obtained through preprocessing of detected features. An experiment of classifying 228 test fundus images with the proposed classification system showed 97.8% accuracy.

A Study on Pathological Pattern Detection using Neural Network on X-Ray Chest Image (신경회로망을 이용한 X-선 흉부 영상의 병변 검출에 관한 연구)

  • 이주원;이한욱;이종회;조원래;장두봉;이건기
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.2
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    • pp.371-378
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    • 2000
  • In this study, we proposed pathological pattern detection system for X-ray chest image using artificial neural network. In a physical examination, radiologists have checked on the chest image projected the view box by a magnifying glass and found out what the disease is. Here, the detection of X-ray fluoroscopy is tedious and time-consuming for human doing. Lowering of efficiency for chest diagnosis is caused by lots mistakes of radiologist because of detecting the micro pathology from the film of small size. So, we proposed the method for disease detection using artificial neural network and digital image processing on a X-ray chest image. This method composes the function of image sampling, median filter, image equalizer used neural network and pattern recognition used neural network. We confirm this method has improved the problem of a conventional method.

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Clinical Specimen Printing System using RFID (RFID를 이용한 검체 프린팅 시스템)

  • Kim, Yong-Phil;Choi, Kwang-Il;Jung, Hoe-Kyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.2
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    • pp.351-356
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    • 2014
  • Although the demand for histopathological examinations has been increasing, medical accidents in management of specimens also have been increasing because most of the examinations are processed manually which can cause careless handing, confusing information and mismatching during the procedure. In the future, histopatological examination will be used frequently for handing incurable diseases and verification of new drug. Thus, efficient and error-free management system for handling personalized medical history and test results is infallibly necessary. In this paper, I have proposed an integrated printing system for informatization of histopathological examination that support the u-Healthcare environment based on RFID in near future. The proposed system supports systematization of whole examination process and information of pathological samples. This system will contribute to reduction of costs, improvement of operational efficiency, and mostly fundamental prevention of medical accidents.

Morphological Variation Classification of Red Blood Cells using Neural Network Model in the Peripheral Blood Images (말초혈액영상에서 신경망 모델을 이용한 적혈구의 형태학적 변이 분류)

  • Kim, Gyeong-Su;Kim, Pan-Gu
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.10
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    • pp.2707-2715
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    • 1999
  • Recently, there have been researches to automate processing and analysing images in the medical field using image processing technique, a fast communication network, and high performance hardware. In this paper, we propose a system to be able to analyze morphological abnormality of red-blood cells for peripheral blood image using image processing techniques. To do this, we segment red-blood cells in the blood image acquired from microscope with CCD camera and then extract UNL fourier features to classify them into 15 classes. We reduce the number of multi-variate features using PCA to construct a more efficient classifier. Our system has the best performance in recognition rate, compared with two other algorithms, LVQ3 and k-NN. So, we show that it can be applied to a pathological guided system.

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