• 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.

• Speech Sciences
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• v.14 no.1
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• pp.151-162
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• 2007

This study focuses on the classification of pathological voice using GMM (Gaussian Mixture Model) and compares the results to the previous work which was done by ANN (Artificial Neural Network). Speech data from normal people and patients were collected, then diagnosed and classified into two different categories. Six characteristic parameters (Jitter, Shimmer, NHR, SPI, APQ and RAP) were chosen. Then the classification method based on the artificial neural network and Gaussian mixture method was employed to discriminate the data into normal and pathological speech. The GMM method attained 98.4% average correct classification rate with training data and 95.2% average correct classification rate with test data. The different mixture number (3 to 15) of GMM was used in order to obtain an optimal condition for classification. We also compared the average classification rate based on GMM, ANN and HMM. The proper number of mixtures on Gaussian model needs to be investigated in our future work.

• MALSORI
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• no.66
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• pp.61-72
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• 2008

This paper proposes a method to improve pathological and normal voice classification performance by combining multiple features such as auditory-based and higher-order features. Their performances are measured by Gaussian mixture models (GMMs) and linear discriminant analysis (LDA). The combination of multiple features proposed by the frame-based LDA method is shown to be an effective method for pathological and normal voice classification, with a 87.0% classification rate. This is a noticeable improvement of 17.72% compared to the MFCC-based GMM algorithm in terms of error reduction.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.99-108
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• 2011

The perturbation parameters like jitter, shimmer, and signal-to-noise ratio (SNR) are largely estimated in the particular segment from the subjective or whole portion of the given pathological voice signal although there are many possible regions to be able to analyze the voice signals. In this paper, the pathological voice signals were classified as type 1, 2, 3, or 4 according to narrow band spectrogram and the value differences of the perturbation parameters extracted in the subjective and entire portion tended to be getting bigger as from type 1 to type 4 signals. Therefore, sample selection method based on moving window to analyze type 2 and 3 signals as well as type 1 signals is proposed. Although type 3 signals cannot be analyzed using the perturbation analysis, the type 3 signals by selecting out the samples in which error count is less than 10 through moving window were analyzed. At present, there is no method to be able to analyze the type 4 signals. Future research will endeavor to determine the best way to evaluate such voices.

• Speech Sciences
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• v.5 no.1
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• pp.151-165
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• 1999

This paper describes a series of researches to diagnose vocal diseases using the statistical method and the acoustic signal analysis method. Speech materials are collected at the hospital. Using the pathological database, the basic parameters for the diagnosis are obtained. Based on the statistical characteristics of the parameters, valid parameters are chosen and those are used to diagnose the pathological speech signal. Cepstrum is used to extract parameters which represents characteristics of pathological speech. 3 layered neural network is used to train and classify pathological speech into normal, benign and malignant case.

• YAKHAK HOEJI
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• v.22 no.4
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• pp.226-232
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• 1978

It was to investigate the absorption, excretion, protein binding of ampicillin in the pathological animals pretreated with carbon tetrachloride and mercuric chloride. The absorption of ampicillin was not affected in rats with damaged liver and kidney as compared with that of normal rats. The blood level of ampicillin after oral administration was increased significantly in rabbits with damaged kidney and liver. The blood level of ampicillin in rabbit with damaged kidney was more increased than that in rabbits with damaged liver. In severly damaged rabbits, it was more increased than that of mildly damaged rabbits. Urinary excretion of ampicillin in pathological animals was more inhibited than that of ampicillin in normals. Hepatic excretion of ampicillin was accelerated in rabbits with damaged kidney. However, in rabbits with damaged liver, it was inhibited as compared with that in normals. Protein binding of ampicillin was slightly enhanced by the various concentration of carbon tetrachloride and mercuric chloride, respectively. The results suggest that the increase of blood level of ampicillin in pathological animals was due to the inhibition of renal excretion.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.176-182
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• 2023

Since the introduction of low-dose computed tomography (CT) screening for patients at high risk of lung cancer, the detection rate of suspicious lung cancer has increased. In addition, there have been many advances in therapeutics targeting oncogenic drivers in non-small cell lung cancer. Therefore, accurate pathological diagnosis of lung cancer, including molecular diagnosis, is increasingly important. This review examines the problems in the pathological diagnosis of suspected lung cancer. For successful pathological diagnosis of lung cancer, clinicians should determine the appropriate modality of the diagnostic procedure, considering individual patient characteristics, CT findings, and the possibility of complications. Furthermore, clinicians should make efforts to obtain a sufficient amount of tissue sample using non- or less-invasive procedures for pathological diagnosis and biomarker analysis.

• Journal of fish pathology
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• v.18 no.2
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• pp.105-118
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• 2005

Anemia in fish can be easily recognized by examining the gill color and physical properties of sampled blood. The number of erythrocytes is generally within 1-3 ${\times}10^6$. Hematocrit (Ht) reportedly ranges 35-45% in many of reports which is nearly the same as that in mammals. Anemia in fish can also be classified as hemorrhagic, hemolytic and hypoplastic ones. Fish are also expected to have similar pathological effects by anemia as in mammals. From the fact that fish can survive under extremely low hematocrit below 10% and antarctic icefish (Chanenocephalus aceratus) has no erythrocytes, different pathological effects were expected. Anemia is considered to have one of the most important health parameters, based on the pathological aspect. Therefore, by reviewing clinical and histopathological findings of most of fish diseases already known and then adding our results of experimental anemia, diseases and factors related to anemia were summarized and the pathological effects was discussed.

• 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.

• Journal of Physiology & Pathology in Korean Medicine
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• v.33 no.2
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• pp.75-81
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• 2019

In order to research the pathological entity of Jueyin disease in ${\ll}Shanghanlun{\gg}$, some sharing concept of three-yin-three-yang used in ${\ll}Neijing{\gg}$ and ${\ll}Shanghanlun{\gg}$ were investigated first, and then the meaning of jueyin and jueyin disease were analyzed. In cold damage disease, time-space factor is important because the pathological change is rapid and the symptoms along path are similar, therefore three-yin-three-yang having complex meaning of time and space can be used as an appropriate pathological concept. So to speak, it is able to be interpreted as various modes like variations of yin-yang, qi-blood, change of pulse condition, theories of opening, closing, pivot or exuberance and debilitation of form and qi manifested in the six districts of the human body following disease process. Jueyin is between front taiyin and rear shaoyin, and it's attribution is inherent in qi stagnation and yin exuberance in relative to the location of flank and liver. Putting together above descriptions, pathological entity of jueyin disease is that the symptoms mingled with cold and stagnant heat competing each other when a subject having qi stagnation in flank with cold in extremities and lower abdomen in particular is seized with cold influenza.