• Title/Summary/Keyword: Automated Diagnosis

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Automated Detection of Pulmonary Nodules in Chest X-ray Radiography Using Genetic Algorithm (흉부 X-ray 영상에서 유전자 알고리즘을 이용한 폐 결절 자동 추출)

  • 류지연;이경일;장정란;오명진;이배호
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.553-555
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    • 2002
  • 컴퓨터지원진단(Computer Aided Diagnosis; CAD) 시스템은 방사선 의사들이 흉부 X-ray 영상에서 결절을 탐지하는데 있어 실제적으로 발생할 수 있는 오진율을 줄이고, 폐 결절이 존재하는 폐야에서 결절의 존재 유무를 판단하여 검출을 표시함으로써 진단율을 개선시킬 수 있도록 하였다. 본 논문은 흉부 X-ray 영상에서의 폐 결절을 추출하는데 유전자 알고리즘(Genetic Algorithm)을 이용한 템플릿 매칭(Template Matching) 방법을 제안한다. 제안한 방법은 흉부 X-ray 영상에 존재하는 결절과 레퍼런스 이미지를 매칭시켜 적합도를 계산한 후, 그 값을 통하여 수치가 낮은 개체를 선택하여 높은 개체와 교차시킨다. 그리고 레퍼런스 이미지는 결절이 존재하는 환자 X-ray 영상에서 샘플 노듈을 추출한 후 가우시안 분포를 갖는 512개의 레퍼런스 이미지를 생성하였다. 본 논문에서 사용된 영상은 결절 50개, 비결절 30개와 흉부 X-ray 영상에서 육안으로 판별이 가능한 결절 영상을 20개를 포함하여 총 100개 영상을 사용하였다. 실험 결과 83%의 결절을 자동 추출 하였으며, 가장 적절한 레퍼런스 이미지를 발견하고 이를 흉부영상에 매칭시켜 정확한 결절의 위치를 확인하였다.

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Automated Speech Analysis Applied to Sasang Constitution Classification (음성을 이용한 사상체질 분류 알고리즘)

  • Kang, Jae-Hwan;Yoo, Jong-Hyang;Lee, Hae-Jung;Kim, Jong-Yeol
    • Phonetics and Speech Sciences
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    • v.1 no.3
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    • pp.155-163
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    • 2009
  • This paper introduces an automatic voice classification system for the diagnosis of individual constitution based on Sasang Constitutional Medicine (SCM) in Traditional Korean Medicine (TKM). For the developing of this algorithm, we used the voices of 473 speakers and extracted a total of 144 speech features from the speech data consisting of five sustained vowels and one sentence. The classification system, based on a rule-based algorithm that is derived from a non parametric statistical method, presents binary negative decisions. In conclusion, 55.7% of the speech data were diagnosed by this system, of which 72.8% were correct negative decisions.

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A Study on the Elimination of 60Hz Powerline Inteirference for the Automated Diagnosis of Electrocsrdiogram (심전도 자동진단을 위한 60Hz 전원잡음 제거 필터에 관한 연구)

  • Kweon, Hyukje;Jeong, Keesam;Lee, Myoungho
    • Journal of Biomedical Engineering Research
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    • v.17 no.1
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    • pp.99-108
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    • 1996
  • Diverse digital filters have been designed previously to eliminate powerline(AC) interference in the electrocardiouam. This paper describes filtering methods which have been developed recursive notch, adaptive, IEF(Incremental Estimation Filter) and proposes a new AIEF(Advanced Incremental Estimation Filter) method. The performances of these filters are compared on artificial signals as well as actual ECG signals with the aid of validated CSE(Common Standards for Quantitative Electrocardiowaphy). AC interference in this database is shown to exhibit two qualities especially relevant to filter design : considerable deviations from a nominal 60Hz frequency and substantial noise at higher harmonics.

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A Real Time Automated Diagnosis Algorithm of Electrocardiogram Based-on Microcomputer (마이크로 컴퓨터를 이용한 실시간 ECG 자동진단 알고리즘)

  • 윤형로;최경훈
    • Journal of Biomedical Engineering Research
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    • v.6 no.1
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    • pp.55-64
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    • 1985
  • The cardiac activation process using three dimensional ventricular model is simulated.To study this theme, we constructed a cardiac ventricular model and simulated the cardiac activation process using the action potential duration and the activation time. The cardiac ventricular model is generated by the logical combination of the elliptic equations. The action potential duration could be obtained from the fact that it is linearly distributed between model cells. The cardiac activation process was simulated by the law of "all-or-none" Based on the activation time and the action potential do-ration the cardiac potential at the arbitrary time after the activation of the model cell was computed. To test the validity of model, the comparison of the results of model simulation with the physiological data was performed. In conclusion, this model shows the simular results which is comparable to the real conduction of the cardiac excitation.xcitation.

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Automated Chromosome Samples Extraction using Region Splitting Method (영역분할 기법을 이용한 염색체 표본 자동추출)

  • Eom, Sang-Hee;Jeon, Gye-Rok;Lee, Kwon-Soon;Chang, Yong-Hoon;Lee, Sang-Yeol
    • Proceedings of the KOSOMBE Conference
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    • v.1995 no.05
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    • pp.127-130
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    • 1995
  • Chromosome analysis is an important and difficult task for clinical diagnosis, for mutagen dosimetry, and for biological research. It is expensive, time consuming and imprecise when performed manually. Efforts lo automate some or all of the procedures have continued for more than 30 years, with only limited success. An acquiring sample from chromosome group is not solved with automatic method. It is still performed by user. This paper represents the method of an automatic chromosome sample extraction which based on region splitting, and scan converted method.

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A study of estimation and removal of baseline drift for the automated diagnosis of electrocardiogram (심전도 자동 진단을 위한 기저선 동요 평가 및 제거에 관한 연구)

  • 권혁제;이명호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.7
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    • pp.99-106
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    • 1996
  • Estimation and removal procedures for baseline drift have been developed using linear, cubic spline, and bilineared transformed high pass filter. Linear and cubic spline interpolation with the PQ and TP segmens, which are considered to be isoelectric, as fiducial points ahve been estimated respectively. For a quantitative validation of the estimation procedure, 4 ECGs with arfificial baseline drift were constructed and analyzed by mean square error calculations and amplitude histograms. Also real ECGs were analyzed in a test set of the CSE data set 3 and set 4. Baseline drift detecton rule were designed and new method for the decision of fiducial point were constructed to avoid distorting as the case of premature ventricular or atrial contraction. From these comparison, proposed cubic spline method with PQ and TP segment (CS_PQ & TP) emerged as the most efficient method.

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Discrimination of Pathological Speech Using Hidden Markov Models

  • Wang, Jianglin;Jo, Cheol-Woo
    • Speech Sciences
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    • v.13 no.3
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    • pp.7-18
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    • 2006
  • Diagnosis of pathological voice is one of the important issues in biomedical applications of speech technology. This study focuses on the discrimination of voice disorder using HMM (Hidden Markov Model) for automatic detection between normal voice and vocal fold disorder voice. This is a non-intrusive, non-expensive and fully automated method using only a speech sample of the subject. Speech data from normal people and patients were collected. Mel-frequency filter cepstral coefficients (MFCCs) were modeled by HMM classifier. Different states (3 states, 5 states and 7 states), 3 mixtures and left to right HMMs were formed. This method gives an accuracy of 93.8% for train data and 91.7% for test data in the discrimination of normal and vocal fold disorder voice for sustained /a/.

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An Advanced Instrumentation Signal Analyzing Technique for Automated Power Plant Monitoring and Fault Diagnosis (발전소 운전감시 및 고장진단을 위한 계측기기 신호의 전처리 기법에 관한 연구)

  • Chang, Tae-Gyu
    • Proceedings of the KIEE Conference
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    • 1996.11a
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    • pp.450-453
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    • 1996
  • This research presents a new method of detecting and diagnosing faults of a power plant. Detection of characteristic wave patterns from multichannel instrumentation signals forms the basis of the proposed approach. The dynamics of 500MW drum-type boiler (Boryung coal-fired plant unit #1 and #2) and its control systems are modeled and simulated to generate diverse operation patterns and fault situations and to utilize them for the development of the fault detection algorithms. The results of the boiler system modeling and simulations show a fairly high agreement when compared with some of the actual plant performance test data.

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A Study on the Feature Region Segmentation for the Analysis of Eye-fundus Images (안저영상(眼低映像) 해석(解析)을 위한 특징영성(特徵領域)의 분할(分割)에 관한 연구(硏究))

  • Kang, Jeon-Kwun;Kim, Seung-Bum;Ku, Ja-Yl;Han, Young-Hwan;Hong, Hong-Seung
    • Proceedings of the KOSOMBE Conference
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    • v.1993 no.11
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    • pp.27-30
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    • 1993
  • Information about retinal blood vessels can be used in grading disease severity or as part of the process of automated diagnosis of diseases with ocular menifestations. In this paper, we address the problem of detecting retinal blood vessels and optic disk (papilla) in Eye-fundus images. We introduce an algorithm for feature extraction based on Fuzzy festering(FCM). The results ore compared to those obtained with other methods. The automatic detection of retinal blood vessels and optic disk in the Eye-fundus images could help physicians in diagnosing ocular diseases.

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Diagnosis for the Welding Condition of the CAL Process using Neuro-Fuzzy System (뉴로-퍼지 시스템을 이용한 CAL공정내 용접상태 진단)

  • 김경민;김이곤;박중조;송명현;정양희;배영철;최남섭
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.4
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    • pp.885-893
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    • 2000
  • The use of neural-fuzzy system to model mesh seam welding is described in this paper. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current, torch travel speed and the pressure and so on. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other. The effectiveness of the proposed neuro-fuzzy algorithms is demonstrated by computer simulations.

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