• Title/Summary/Keyword: Histogram Analysis

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Relationship between DNA ploidy and Survival Time in Small Cell Lung Cancer (소세포 폐암에서 DNA 배수성과 생존 기간과의 관계)

  • Song, Joong-Ho;Yang, Se-Hoon;Jung, Byung-Hak;Jeong, Eun-Taik
    • Tuberculosis and Respiratory Diseases
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    • v.42 no.3
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    • pp.314-321
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    • 1995
  • Background: Flow cytometric study has been used to measure the DNA content of solid tumors for the last decade. DNA ploidy is an important property commonly measured by flow cytometry. The possibility to study archival paraffin-embedded tumors has hastened an appreciation of prognostic utility of this method. The aim of this study is to look for biologic prognostic indicator for survival time of patients with small cell carcinoma of lung in addition to the well known clinical prognostic factors. Method: DNA ploidy was measured by flow cytometric method using tumor cells isolated from paraffin embedded tissue. To evaluate the prognostic significance, DNA ploidy of small cell lung cancer was analysed in 42 patients who died after receiving anticancer chemotherapy. Results: 1) Mean survival time of all patients was 190(${\pm}156$) days. Survival time was shortened, when TNM stage and PS scale were advanced. 2) 62% of all patients was DNA aneuploidy. DNA ploidy had nothing to do with advance of TNM stage and PS scale. 3) Mean survival time of aneuploid tumor was significantly shorter($138{\pm}90$ days) than that of diploid tumors($272{\pm}197$ days).(p<0.001) 4) To exclude the influence of clinical prognostic factors such as TNM stage and PS scale, the analysis was restricted to subgroups of identical stage. We were able to find the same tendency. Conclusion: DNA ploidy is an independent prognostic factor in small cell lung cancer.

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Application of Computer-Aided Diagnosis a using Texture Feature Analysis Algorithm in Breast US images (유방 초음파영상에서 질감특성분석 알고리즘을 이용한 컴퓨터보조진단의 적용)

  • Lee, Jin-Soo;Kim, Changsoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.507-515
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    • 2015
  • This paper suggests 6 cases of TFA parameters algorithm(Mean, VA, RS, SKEW, UN, EN) to search for the detection of recognition rates regarding breast disease using CAD on ultrasound images. Of the patients who visited a university hospital in Busan city from August 2013 to January 2014, 90 cases of breast ultrasound images based on the findings in breast US and pathology were selected. $50{\times}50$ pixel size ROI was selected from the breast US images. After pre-processing histogram equalization of the acquired test images(negative, benign, malignancy), we calculated results of TFA algorithm using MATLAB. As a result, in the TFA parameters suggested, the disease recognition rates for negative and malignancy was as high as 100%, and negative and benign was approximately 83~96% for the Mean, SKEW, UN, and EN. Therefore, there is the possibility of auto diagnosis as a pre-processing step for a screening test on breast disease. A additional study of the suggested algorithm and the responsibility and reproducibility for various clinical cases will determine the practical CAD and it might be possible to apply this technique to range of ultrasound images.

Regional Background Levels of Carbon Monoxide Observed in East Asia during 1991~2004 (1991~2004년 동아시아에서 관측한 일산화탄소의 지역적 배경 농도)

  • Kim, Hak-Sung;Chung, Yong-Seung
    • Journal of the Korean earth science society
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    • v.27 no.6
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    • pp.643-652
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    • 2006
  • Data of the carbon monoxide concentration observed in Mt. Waliguan in China (WLG), Ulaan Uul in Mongolia (UUM), Tae-ahn Peninsula in Korea (TAP), and Ryori in Japan (RYO) were analyzed for a long period between 1991 and 2004. The annual average concentration of carbon monoxide was the highest at TAP $(233{\pm}41ppb)$ followed by $RYO(171{\pm}36ppb),\;UUM(155{\pm}26ppb),\;and\;WLG(135{\pm}22ppb)$. The seasonal variations being high in spring and low in summer were observed in other areas of Eastern Asia except WLG. TAP was high in carbon monoxide concentration in all seasons compared to WLG, UUM and RYO and shows wide distribution of concentration in the histogram, which is caused by the influence of large-scale air pollution due to its downwind location close to the East Asian continent, China in particular. Also, our data was compared with data measured at Mauna Loa (MLO) in Hawaii. According to the origin of the isentropic backward trajectory and its transport passage, carbon monoxide concentration observed in TAP was analyzed as follows: continental background airflows (CBG) were $216{\pm}47ppb$; regionally polluted continental airflows (RPC) were $316{\pm}56ppb$; Oceanic background airflows (OBG) were $108{\pm}41ppb$; and Partly perturbed oceanic airflows (PPO) were $161{\pm}6ppb$. The high concentration of carbon monoxide in TAP is due to the airflow from East Asian continent origin rather than that from the North Pacific origin. Especially, RPC which passes through the eastern China appeared to be the highest in concentration in spring, fall, and winter. However, OBG was affected by the North Pacific air mass with a low carbon monoxide concentration in summer. The NOAA satellite images and GEOS-CHEM model simulation confirmed a large-scale air pollution event that was in the course of expansion from southeastern China bound to the Korean Peninsula and the Korea East Sea by way of the Yellow Sea.

Improved Binarization and Removal of Noises for Effective Extraction of Characters in Color Images (컬러 영상에서 효율적 문자 추출을 위한 개선된 2치화 및 잡음 저거)

  • 이은주;정장호
    • Journal of Information Technology Application
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    • v.3 no.2
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    • pp.133-147
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    • 2001
  • This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.

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Clinical Significance of S-Phase Fraction in Small Cell Lung Cancer (소세포 폐암에서 S-Phase Fraction의 임상적 의의)

  • Kim, Hui-Jung;Jung, Byung-Hak;Jeong, Eun-Taik
    • Tuberculosis and Respiratory Diseases
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    • v.41 no.4
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    • pp.363-371
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    • 1994
  • Background: DNA content analysis of human solid tumor is now widely performed by flow cytometric study. One of the most interesting and potentially important observation in this field is that proliferative activity(S-Phase fraction of cell cycle) may profoundly affect the prognosis. Method: S-Phase fraction(SPF) have been measured by flow cytometric method using tumor cells isolated from paraffin embedded tissue. To evaluate the prognostic significance, SPF of small lung cancer cell was assessed in 42 patients who died after receiving anticancer chemotherapy. Results: 1) Mean survival time of patients with small cell lung cancer was 190(${\pm}156$) days. Survival time were shortened, when TNM stage and PS scale were advanced. 2) Mean value of SPF of patients with small cell lung cancer was 27.4(${\pm}8.5$)%. SPF had nothing to do with advance of TNM stage and PS scale. 3) In each identical TNM stage, there were not statistic significance between SPF and survival times. 4) There was a tendency like that higher SPF, better chemotherapeutic response. Conclusion: We could not find statistic significance between SPF and survival times, but SPF was a good predictive factor for chemotherapeutic response.

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Edge-based spatial descriptor for content-based Image retrieval (내용 기반 영상 검색을 위한 에지 기반의 공간 기술자)

  • Kim, Nac-Woo;Kim, Tae-Yong;Choi, Jong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.1-10
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    • 2005
  • Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

Automatic Segmentation of Pulmonary Structures using Gray-level Information of Chest CT Images (흉부 CT 영상의 밝기값 정보를 사용한 폐구조물 자동 분할)

  • Yim, Ye-Ny;Hong, Helen
    • Journal of KIISE:Software and Applications
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    • v.33 no.11
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    • pp.942-952
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    • 2006
  • We propose an automatic segmentation method for identifying pulmonary structures using gray-level information of chest CT images. Our method consists of following five steps. First, to segment pulmonary structures based on the difference of gray-level value, we select the threshold using optimal thresholding. Second, we separate the thorax from the background air and then the lungs and airways from the thorax by applying the inverse operation of 2D region growing in chest CT images. To eliminate non-pulmonary structures which has similar intensities with the lungs, we use 3D connected component labeling. Third, we segment the trachea and left and right mainstem bronchi using 3D branch-based region growing in chest CT images. Fourth, we can obtain accurate lung boundaries by subtracting the result of third step from the result of second step. Finally, we select the threshold in accordance with histogram analysis and then segment radio-dense pulmonary vessels by applying gray-level thresholding to the result of the second step. To evaluate the accuracy of proposed method, we make a visual inspection of segmentation result of lungs, airways and pulmonary vessels. We compare the result of the conventional region growing with the result of proposed 3D branch-based region growing. Experimental results show that our proposed method extracts lung boundaries, airways, and pulmonary vessels automatically and accurately.

An Analysis of Teaching Statistical Graphs in Elementary School Mathematics Textbooks (초등학교 수학 교과서에 나타난 통계 그래프 지도 방법 분석)

  • Lim Ji Ae;Kang Wan
    • Journal of Elementary Mathematics Education in Korea
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    • v.7 no.1
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    • pp.65-86
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    • 2003
  • Mathematics textbooks are substitutive showing real characters of didactic transposition in pseudo-contextualization and pseudo-personalization. This study analyzed statistical graphs in elementary school mathematics textbooks according to the first to the 7th curriculum in Korea. It focused on the didactic principles used in those methods through those view of Didactic Transposition Theory. The features of the elementary school mathematics textbooks in Korea are investigated and described ethnomethodologically according to each curriculum periods in dividing bar graph, line graph, pictograph, graph of ratio, histogram. The teaching sequences and methods of the statistical graphs, order and methods of sub-learning activities, teaming data, matter of the learning activity indicator were summarized. Usually, the teaching sequences, excepting the graphs of ratio, statistical graphs are introduced in the second semester of each grade. The graph of ratio is introduced in the first semester of 6th grade. As a result of analysing sub-Loaming activities, using them increased from the first to the 7th curriculum and its form was fixed constructive and stable at the 4th curriculum textbooks. As a result of analysing the teaming data, the data of the social aspects are used more frequently and the data of the individual preferences trended more gradually. As a result of analysing the matter of the teaming activity indicators, concept-explanation question style were used more frequently. Statement-practice style and consideration style trended gradually. Concluding remarks are: First, the didactic transposition of the elementary school mathematics textbooks developed systematically according to the first to the 7th curriculum; Second, mathematics textbooks gradually introduced the positive learning style of activity and the learners' spontaneousness; Third, more concrete practice activities and reflective activities were variously introduced considering the level and interest of each elementary student.

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Comparative Study Between Respiratory Gated Conventional 2-D Plan and 3-D Conformal Plan for Predicting Radiation Hepatitis (간암에서 호흡주기를 고려한 2-차원 방사선 치료 방법과 3-차원 입체조형 치료방법에서 방사선 간염 예측의 비교연구)

  • Lee Sang-wook;Kim Gwi Eon;Chung Kap Soo;Lee Chang Geol;Seong Jinsil;Suh Chang Ok
    • Radiation Oncology Journal
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    • v.16 no.4
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    • pp.455-467
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    • 1998
  • Purpose : To evaluate influences associated with radiation treatment planning obtained with the patient breathing freely. Materials and Methods : We compared reduction or elimination of planning target volume (PTV) margins with 2-D conventional plan with inclusion of PTV margins associated with breathing with 3-D conformal therapy. The respiratory non gated 3-D conformal treatment plans were compared with respiratory gated conventional 2-D plans in 4 patients with hepatocellular carcinomas. Isodose distribution, dose statistics, and dose volume histogram (DVH) of PTVs were used to evaluate differences between respiratory gated conventional 2-D plans and respiratory non gated 3-D conformal treatment plans. In addition. the risk of radiation exposure of surrounding normal liver and organs are evaluated by means of DVH and normal tissue complication probabilities (NTCPs). Results : The vertical movement of liver ranged 2-3 cm in all patients. We found no difference between respiratory gated 2-D plans and 3-D conformal treatment plans with the patients breathing freely. Treatment planning using DVH analysis of PTV and the normal liver was used for all patients. DVH and calculated NTCP showed no difference in respiratory gated 2-D plans and respiratory non gated 3-D conformal treatment plans. Conclusion : Respiratory gated radiation therapy was very important in hepatic tumors because radiation induced hepatitis was dependent on remaining normal liver volume. Further investigational studies for respiratory gated radiation.

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Data Mining Algorithm Based on Fuzzy Decision Tree for Pattern Classification (퍼지 결정트리를 이용한 패턴분류를 위한 데이터 마이닝 알고리즘)

  • Lee, Jung-Geun;Kim, Myeong-Won
    • Journal of KIISE:Software and Applications
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    • v.26 no.11
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    • pp.1314-1323
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    • 1999
  • 컴퓨터의 사용이 일반화됨에 따라 데이타를 생성하고 수집하는 것이 용이해졌다. 이에 따라 데이타로부터 자동적으로 유용한 지식을 얻는 기술이 필요하게 되었다. 데이타 마이닝에서 얻어진 지식은 정확성과 이해성을 충족해야 한다. 본 논문에서는 데이타 마이닝을 위하여 퍼지 결정트리에 기반한 효율적인 퍼지 규칙을 생성하는 알고리즘을 제안한다. 퍼지 결정트리는 ID3와 C4.5의 이해성과 퍼지이론의 추론과 표현력을 결합한 방법이다. 특히, 퍼지 규칙은 속성 축에 평행하게 판단 경계선을 결정하는 방법으로는 어려운 속성 축에 평행하지 않는 경계선을 갖는 패턴을 효율적으로 분류한다. 제안된 알고리즘은 첫째, 각 속성 데이타의 히스토그램 분석을 통해 적절한 소속함수를 생성한다. 둘째, 주어진 소속함수를 바탕으로 ID3와 C4.5와 유사한 방법으로 퍼지 결정트리를 생성한다. 또한, 유전자 알고리즘을 이용하여 소속함수를 조율한다. IRIS 데이타, Wisconsin breast cancer 데이타, credit screening 데이타 등 벤치마크 데이타들에 대한 실험 결과 제안된 방법이 C4.5 방법을 포함한 다른 방법보다 성능과 규칙의 이해성에서 보다 효율적임을 보인다.Abstract With an extended use of computers, we can easily generate and collect data. There is a need to acquire useful knowledge from data automatically. In data mining the acquired knowledge needs to be both accurate and comprehensible. In this paper, we propose an efficient fuzzy rule generation algorithm based on fuzzy decision tree for data mining. We combine the comprehensibility of rules generated based on decision tree such as ID3 and C4.5 and the expressive power of fuzzy sets. Particularly, fuzzy rules allow us to effectively classify patterns of non-axis-parallel decision boundaries, which are difficult to do using attribute-based classification methods.In our algorithm we first determine an appropriate set of membership functions for each attribute of data using histogram analysis. Given a set of membership functions then we construct a fuzzy decision tree in a similar way to that of ID3 and C4.5. We also apply genetic algorithm to tune the initial set of membership functions. We have experimented our algorithm with several benchmark data sets including the IRIS data, the Wisconsin breast cancer data, and the credit screening data. The experiment results show that our method is more efficient in performance and comprehensibility of rules compared with other methods including C4.5.