• Title/Summary/Keyword: Image data classification

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A Prostate Segmentation of TRUS Image using Average Shape Model and SIFT Features (평균 형상 모델과 SIFT 특징을 이용한 TRUS 영상의 전립선 분할)

  • Kim, Sang Bok;Seo, Yeong Geon
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.3
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    • pp.187-194
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    • 2012
  • Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease, transrectal ultrasound(TRUS) images are being used because the cost is low. But, accurate detection of prostate boundaries is a challenging and difficult task due to weak prostate boundaries, speckle noises and the short range of gray levels. This paper proposes a method for automatic prostate segmentation in TRUS images using its average shape model and invariant features. This approach consists of 4 steps. First, it detects the probe position and the two straight lines connected to the probe using edge distribution. Next, it acquires 3 prostate patches which are in the middle of average model. The patches will be used to compare the features of prostate and nonprostate. Next, it compares and classifies which blocks are similar to 3 representative patches. Last, the boundaries from prior classification and the rough boundaries from first step are used to determine the segmentation. A number of experiments are conducted to validate this method and results showed that this new approach extracted the prostate boundary with less than 7.78% relative to boundary provided manually by experts.

CLINICAL STUDY OF POSITRON EMISSION TOMOGRAPHY WITH $[^{18}F]$-FLUORODEOXYGLUCOSE IN MAXILLOFACIAL TUMOR DIAGNOSIS (구강 악안면 영역의 암종 진단에 있어서 $[^{18}F]$-Fluorodeoxyglucose를 이용한 양전자방출 단층촬영의 임상적 연구)

  • Kim, Jae-Hwan;Kim, Kyung-Wook;Kim, Yong-Kack
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.26 no.5
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    • pp.462-469
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    • 2000
  • Positron Emission Tomography(PET) is a new diagnostic method that can create functional images of the distribution of positron emitting radionuclides, which when administered intravenously in the body, makes possible anatomical and functional analysis by quantity of biochemical and physiological process. After genetic and biochemical changes in initial stage, malignant tumor undergoes functional changes before undergoing anatomical changes. So, early diagnosis of malignant tumors by functional analysis with PET can be achieved, replacing traditional anatomical analysis, such as computed tomography(CT) and magnetic resonance image(MRI), etc. Similarly, PET can identify malignant tumor without confusion with scar and fibrosis in follow up check. In the Korea Cancer Center Hospital(KCCH) from October 1997 to September 1999, clinical study was performed in 79 cases that underwent 89 times PET evaluation with [18F]-Fluorodeoxyglucose for diagnosis of oral and maxillofacial tumors, and the data was analysed by Bayesian $2{\times}2$ Classification Table. The results were as follows : Evaluation for initial diagnosis with FDG-PET (P<0.005) 1. Agreement rate or accuracy rate is 88.9%. 2. Sensitivity is 95.2%, and specificity 66.7%. 3. Positive predictive rate is 90.9%, and negative predictive rate 80.0%. 4. In consideration of tumor stage, diagnostic rate in less than stage II was 90% and in greater than stage III 100%. 5. In consideration of tumor size, diagnostic rate in less than T2 was 92.3% and in greater than T3 100%. After primary treatment, evaluation for follow up check with FDG-PET (P < 0.001) 1. Agreement rate or accuracy rate is 85.4%. 2. Sensitivity is 87.5%, and specificity 82.4%. 3. Positive predictive rate is 87.5%, and negative predictive rate 82.4%. 4. In 24 recurred cases, 6 had distant metastasis, and 5 of them were diagnosed with FDG-PET, resulting in diagnostic rate of FDG-PET of 83.3%. From the above results, Positron Emission Tomography with [18F]- Fluorodeoxyglucose appears to be more sensitive and accurate for detecting the presence of oral and maxillofacial tumors, and has various clinical applications such as early diagnosis of tumor in initial and follow up check and detection of distant metastasis.

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Characteristics of Greenup and Senescence for Evapotranspiration in Gyeongan Watershed Using Landsat Imagery (Landsat 인공위성 이미지를 이용한 경안천 유역 증발산의 생장기와 휴면기 분포 특성 분석)

  • Choi, Minha;Hwang, Kyotaek;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.1B
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    • pp.29-36
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    • 2011
  • Evapotranspiration (ET) from the various surfaces needs to be understood because it is a crucial hydrological factor to grasp interaction between the land surface and the atmosphere. A traditional way of estimating it, which is calculating it empirically using lysimeter and pan evaporation observations, has a limitation that the measurements represent only point values. However, these measurements cannot describe ET because it is easily affected by outer circumstances. Thus, remote sensing technology was applied to estimate spatial distribution of ET. In this study, we estimated major components of energy balance method (i.e. net radiation flux, soil heat flux, sensible heat flux, and latent heat flux) and ET as a map using Mapping Evapo-Transpiration with Internalized Calibration (METRIC) satellite-based image processing model. This model was run using Landsat imagery of Gyeongan watershed in Korea on Feb 1, 2003 and Sep 13, 2006. Basic statistical analyses were also conducted. The estimated mean daily ETs had respectively 22% and 11% of errors with pan evaporation data acquired from the Suwon Weather Station. This result represented similar distribution compared with previous studies and confirmed that the METRIC algorithm had high reliability in the watershed. In addition, ET distribution of each land use type was separately examined. As a result, it was identified that vegetation density had dominant impacts on distribution of ET. Seasonally, ET in a growing season represented significantly higher than in a dormant season due to more active transpiration. The ET maps will be useful to analyze how ET behaves along with the circumstantial conditions; land cover classification, vegetation density, elevation, topography.

Fractal Analysis of Tidal Channel using High Resolution Satellite Image (고해상도 위성 영상을 이용한 조류로의 프랙털 분석)

  • Eom, Jin-Ah;Lee, Yoon-Kyung;Ryu, Joo-Hyung;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.23 no.6
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    • pp.567-573
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    • 2007
  • Tidal channel development is influenced by sediment type, grain size, composition and tidal current. Tidal channels are usually characterized by channel formation, density and shape. Quantitative analysis of tidal channels using remotely sensed data have rarely been studied. The objective of this study is to quantify tidal channels in terms of fractal dimension and compare different inter-tidal channel patterns and compare with DEM (Digital Elevation Model). For the fractal analysis, we used box counting method which had been successfully applied to streams, coastlines and others linear features. For a study, the southern part of Ganghwado tidal flats was selected which know for high dynamics of tidal currents and vast tidal flats. This area has different widths and lengths of tidal channels. IKONOS was used for extracting tidal channels, and the box counting method was applied to obtain fractal dimensions (D) for each tidal channel. Yeochari area where channels showed less dense development and low DEM had low fractal dimenwion near $1.00{\sim}1.20$. Area (near Donggumdo and Yeongjongdo) of dendritic channel pattern and high DEM resulted in high fractal dimension near $1.20{\sim}1.35$. The difference of fractal dimensions according to channel development in tidal flats is relatively large enough to use as an index for tidal channel classification. Therefore we could conclude that fractal dimension, channel development and DEM in tidal channel has high correlation. Using fractal dimension, channel development and DEM, it would be possible to quantify the tidal channel development in association with surface characteristics.

Development and Validation of Figure-Copy Test for Dementia Screening (치매 선별을 위한 도형모사검사 개발 및 타당화)

  • Kim, Chobok;Heo, Juyeon;Hong, Jiyun;Yi, Kyongmyon;Park, Jungkyu;Shin, Changhwan
    • 한국노년학
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    • v.40 no.2
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    • pp.325-340
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    • 2020
  • Early diagnosis and intervention of dementia is critical to minimize future risk and cost for patients and their families. The purpose of this study was to develop and validate Figure-Copy Test(FCT), as a new dementia screening test, that can measure neurological damage and cognitive impairment, and then to examine whether the grading precesses for screening can be automated through machine learning procedure by using FCT imag es. For this end, FCT, Korean version of MMSE for Dementia Screening (MMSE-DS) and Clock Drawing Test were administrated to a total of 270 participants from normal and damaged elderly groups. Results demonstrated that FCT scores showed high internal constancy and significant correlation coefficients with the other two test scores. Discriminant analyses showed that the accuracy of classification for the normal and damag ed g roups using FCT were 90.8% and 77.1%, respectively, and these were relatively higher than the other two tests. Importantly, we identified that the participants whose MMSE-DS scores were higher than the cutoff but showed lower scores in FCT were successfully screened out through clinical diagnosis. Finally, machine learning using the FCT image data showed an accuracy of 73.70%. In conclusion, our results suggest that FCT, a newly developed drawing test, can be easily implemented for efficient dementia screening.

Stock Price Direction Prediction Using Convolutional Neural Network: Emphasis on Correlation Feature Selection (합성곱 신경망을 이용한 주가방향 예측: 상관관계 속성선택 방법을 중심으로)

  • Kyun Sun Eo;Kun Chang Lee
    • Information Systems Review
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    • v.22 no.4
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    • pp.21-39
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    • 2020
  • Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

Fully Automatic Coronary Calcium Score Software Empowered by Artificial Intelligence Technology: Validation Study Using Three CT Cohorts

  • June-Goo Lee;HeeSoo Kim;Heejun Kang;Hyun Jung Koo;Joon-Won Kang;Young-Hak Kim;Dong Hyun Yang
    • Korean Journal of Radiology
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    • v.22 no.11
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    • pp.1764-1776
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    • 2021
  • Objective: This study aimed to validate a deep learning-based fully automatic calcium scoring (coronary artery calcium [CAC]_auto) system using previously published cardiac computed tomography (CT) cohort data with the manually segmented coronary calcium scoring (CAC_hand) system as the reference standard. Materials and Methods: We developed the CAC_auto system using 100 co-registered, non-enhanced and contrast-enhanced CT scans. For the validation of the CAC_auto system, three previously published CT cohorts (n = 2985) were chosen to represent different clinical scenarios (i.e., 2647 asymptomatic, 220 symptomatic, 118 valve disease) and four CT models. The performance of the CAC_auto system in detecting coronary calcium was determined. The reliability of the system in measuring the Agatston score as compared with CAC_hand was also evaluated per vessel and per patient using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. The agreement between CAC_auto and CAC_hand based on the cardiovascular risk stratification categories (Agatston score: 0, 1-10, 11-100, 101-400, > 400) was evaluated. Results: In 2985 patients, 6218 coronary calcium lesions were identified using CAC_hand. The per-lesion sensitivity and false-positive rate of the CAC_auto system in detecting coronary calcium were 93.3% (5800 of 6218) and 0.11 false-positive lesions per patient, respectively. The CAC_auto system, in measuring the Agatston score, yielded ICCs of 0.99 for all the vessels (left main 0.91, left anterior descending 0.99, left circumflex 0.96, right coronary 0.99). The limits of agreement between CAC_auto and CAC_hand were 1.6 ± 52.2. The linearly weighted kappa value for the Agatston score categorization was 0.94. The main causes of false-positive results were image noise (29.1%, 97/333 lesions), aortic wall calcification (25.5%, 85/333 lesions), and pericardial calcification (24.3%, 81/333 lesions). Conclusion: The atlas-based CAC_auto empowered by deep learning provided accurate calcium score measurement as compared with manual method and risk category classification, which could potentially streamline CAC imaging workflows.

Nondestructive Quantification of Corrosion in Cu Interconnects Using Smith Charts (스미스 차트를 이용한 구리 인터커텍트의 비파괴적 부식도 평가)

  • Minkyu Kang;Namgyeong Kim;Hyunwoo Nam;Tae Yeob Kang
    • Journal of the Microelectronics and Packaging Society
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    • v.31 no.2
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    • pp.28-35
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    • 2024
  • Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

Analysis on the Spatial Characteristics Caused by the Cropland Increase Using Multitemporal Landsat Images in Lower Reach of Duman River, Northeast Korea (다시기 위성영상을 이용한 두만강 하류지역의 농경지 개간의 공간적 특성분석)

  • Lee, Min-Boo;Han, Uk;Kim, Nam-Shin;Han, Ju-Youn;Shin, Keun-Ha;Kang, Chul-Sung
    • Journal of the Korean Geographical Society
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    • v.38 no.4
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    • pp.630-639
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    • 2003
  • This study aims to analysis the distribution and change of cropland and forest, the Onseong, Saebyeol, and Eundeok counties on the lower reach of Duman(Tumen) river, northeast Korea, using 1992 year Landsat TM data, 2000 year Landsat ETM data, and digital terrain elevation data(DTED). Land cover and land use of the study areas are classified into cropland, forest, village, and water body, using the supervised classification method including 1:50,000 DTED analysis, image band composition, and principal component analysis(PCA). Results of quantitative analysis present that each growth rate of cropland of Onseong and Eundeok are 22.8% and 14.7% corresponding to decreasing rates of forest, 8% and 13.6% during 8 years from 1992 to 2000. In Onseong, Saebyeol, and Eundeok, each values of mean elevations and slope gradients increased to 192m, 95m, and 91m from 157m, 85m, and 78m, and to 6.6$^{\circ}$, 3.0$^{\circ}$, and 4.4$^{\circ}$ from 5.2$^{\circ}$, 2.5$^{\circ}$, and 3.0$^{\circ}$. Especially, in case of newly developed cropland, the values of mean elevation and mean gradient have 225m, 122m, and 127m, and 9.4$^{\circ}$, 5.1$^{\circ}$, and 8.0$^{\circ}$, in above three regions. These new croplands were developing along to deeper valleys and toward lower hill and mountain slope up to knickpoint zone of gradient change. Deforested lands for cropland have formed irregular pattern of patch-type, and become sources for the sheet erosion, rilling and gulleying in mountain slope and sedimentation in local river channel. Though there were no field checking, analysis using landsat images and GIS mapping can help understand actual environmental problems relating to cropland development of mountain slope in North Korea.

Classification of submitted KSNMT dissertation (대한핵의학기술학회 투고 논문 분류)

  • Han, Dong-Chan;Lee, Hyuk;Hong, Gun-Chul;Ahn, Byeong-Ho;Choi, Seong-Wook
    • The Korean Journal of Nuclear Medicine Technology
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    • v.21 no.1
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    • pp.65-69
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    • 2017
  • Purpose KSNMT(Korea Society of Nuclear Medicine Technology) stepping first step in 1997, has published first journal related with nuclear medicine technology in 1985. With classifying In Vivo Session Dissertation reported in the entire journal, trend of the Dissertation will be studied. Materials and Methods Dissertations which published from 1985 to first half of 2016 in the journal are classified with presentation form and with scanner, And all the data is organized with Excel program. Through the data, the number of dissertations published in each year, the number of dissertation published in details, and keyword distributions in each period are analyzed. Results The number of In-vivo section dissertations was 1151 and the number of In-vivo section dissertations that have common subject with In-vitro section was 28. The number of In-vivo section dissertation in 1980s was 46, in 1990s was 149, in 2000 was 467 and from 2010 to the first half of 2016 was 517. The number of dissertation with original articles was 571, with abstract was 529, with symposium was 31, with special lecture was 25, with review was 11, with interesting image was 7, with poster was 3 and with case report was 2. With symposium and special lecture excluded, which count 56, the number of dissertation with PET was 319, with Planar was 302, with SPECT was 172, with radiopharmaceutical was 113, with guard and safety management 103, with BMD was 28, etc. was 86. The number of dissertation about oncology was 201, about scanner was 179, about cardiovascular and circulatory system was 102, about safe environment was 82, about musculoskeletal system was 76, about nervous nuclear medicine was 66, about quality assurance was 61, about genitourinary system was 56, about endocrine system was 49, about digestive system was 44, about Therapy, about industrial safety was 24, about molecular imaging was 15, infection and inflammation was 9, about respiratory system was 8 and etc. was 108. The mostly used keyword through 1999 to 2005 was PET and through 2006 to 2016 was PET/CT. Conclusion To encourage various dissertations to be submitted, Korea Society of Nuclear Medicine should analyze date about not only about dissertations that are already published, but also about various research materials. Moreover, Korea Society of Nuclear Medicine also have to provide technical support such as sharing big data from homepage and systematical support to its member to publish dissertation that has high impact factor. It is important each individual researcher to have continuing effort as well as each organization cooperation.

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