• Title/Summary/Keyword: and Pre-Processing

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Development of deep learning structure for complex microbial incubator applying deep learning prediction result information (딥러닝 예측 결과 정보를 적용하는 복합 미생물 배양기를 위한 딥러닝 구조 개발)

  • Hong-Jik Kim;Won-Bog Lee;Seung-Ho Lee
    • Journal of IKEEE
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    • v.27 no.1
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    • pp.116-121
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    • 2023
  • In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (108 or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 108. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.

Quantitative Analysis of Digital Radiography Pixel Values to absorbed Energy of Detector based on the X-Ray Energy Spectrum Model (X선 스펙트럼 모델을 이용한 DR 화소값과 디텍터 흡수에너지의 관계에 대한 정량적 분석)

  • Kim Do-Il;Kim Sung-Hyun;Ho Dong-Su;Choe Bo-young;Suh Tae-Suk;Lee Jae-Mun;Lee Hyoung-Koo
    • Progress in Medical Physics
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    • v.15 no.4
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    • pp.202-209
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    • 2004
  • Flat panel based digital radiography (DR) systems have recently become useful and important in the field of diagnostic radiology. For DRs with amorphous silicon photosensors, CsI(TI) is normally used as the scintillator, which produces visible light corresponding to the absorbed radiation energy. The visible light photons are converted into electric signal in the amorphous silicon photodiodes which constitute a two dimensional array. In order to produce good quality images, detailed behaviors of DR detectors to radiation must be studied. The relationship between air exposure and the DR outputs has been investigated in many studies. But this relationship was investigated under the condition of the fixed tube voltage. In this study, we investigated the relationship between the DR outputs and X-ray in terms of the absorbed energy in the detector rather than the air exposure using SPEC-l8, an X-ray energy spectrum model. Measured exposure was compared with calculated exposure for obtaining the inherent filtration that is a important input variable of SPEC-l8. The absorbed energy in the detector was calculated using algorithm of calculating the absorbed energy in the material and pixel values of real images under various conditions was obtained. The characteristic curve was obtained using the relationship of two parameter and the results were verified using phantoms made of water and aluminum. The pixel values of the phantom image were estimated and compared with the characteristic curve under various conditions. It was found that the relationship between the DR outputs and the absorbed energy in the detector was almost linear. In a experiment using the phantoms, the estimated pixel values agreed with the characteristic curve, although the effect of scattered photons introduced some errors. However, effect of a scattered X-ray must be studied because it was not included in the calculation algorithm. The result of this study can provide useful information about a pre-processing of digital radiography.

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Effect of Accelerated Storage on the Microstructure and Water Absorption Characteristics of Korean Adzuki Bean (Vigna angularis L.) Cultivar (팥의 가속화 저장에 따른 미세구조 및 수분흡수 특성)

  • Jieun Kwak;Seon-Min Oh;You-Geun Oh;Yu-Chan Choi;Hyun-Jin Park;Suk-Bo Song;Jeong-Heui Lee;Jeom-Sig Lee
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.68 no.3
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    • pp.167-174
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    • 2023
  • This study investigated the microstructure and water absorption characteristics of the Korean adzuki bean (Vigna angularis L.) cultivar under accelerated storage. The germination rate, acid value, redness (a*), and yellowness (b*) values showed no significant differences after three months of storage compared to pre-storage under low temperatures (4℃). However, a statistically significant difference was observed under accelerated high temperatures (45℃). In particular, after storage for three months, the germination rate and acid value were 0% and 33.63 mg KOH/100g, respectively, under accelerated high temperatures. After storage for three months, the holes, hilum damage, and spaces between the seed coat and cotyledon shortened the time and speed of water absorption under accelerated high temperatures compared to that under low temperatures. Conversely, further research is required to investigate the reason for the low rate of parallel water absorption.

Design of a Crowd-Sourced Fingerprint Mapping and Localization System (군중-제공 신호지도 작성 및 위치 추적 시스템의 설계)

  • Choi, Eun-Mi;Kim, In-Cheol
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.9
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    • pp.595-602
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    • 2013
  • WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

Axial wall thickness of zirconia abutment in anterior region (전치부 지르코니아 지대주의 축벽 두께)

  • Moon, Seung-Jin;Heo, Yu-Ri;Lee, Gyeong-Je;Kim, Hee-Jung
    • The Journal of Korean Academy of Prosthodontics
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    • v.53 no.4
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    • pp.345-351
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    • 2015
  • Purpose: The purpose of this study was to evaluate the proper axial thickness of zirconia abutment applied to implant in the anterior region. Materials and methods: Zirconia abutments were prepared at different axial wall thickness by processing pre-sintered zirconia blocks via CAD/CAM to obtain equal specimens. The abutments were each produced with a thickness of 0.5 mm (Group 1), 0.8 mm (Group 2), 1.2 mm (Group 3), or 1.5 mm (Group 4). The implant used in this study was a external connection type one (US, Osstem, Pussan, Korea) product and the zirconia abutment was prepared via replication of a cemented abutment. The crowns were prepared via CAM/CAM with a thickness of 1.5 mm and were cemented to the abutments using $RelyX^{TM}$ UniCem cement. A universal testing machine was used to apply load at 30 degrees and measure fracture strength of the zirconia abutment. Results: Fracture strength of the abutments for Group 1, Group 2, Group 3, and Group 4 were $236.00{\pm}67.55N$, $599.00{\pm}15.80N$, $588.20{\pm}33.18N$, and $97.83{\pm}98.13N$, respectively. Group 1 showed a significantly lower value, as compared to the other groups (independent Mann-Whitney U-test. P<.05). No significant differences were detected among Group 2, Group 3, and Group 4 (independent Mann-Whitney U-test. P>.05). Conclusion: Zirconia abutment requires optimal thickness for fracture resistance. Within the limitation of this study, > 0.8 mm thickness is recommended for zirconia abutment in anterior implants.

Role of p-38 MAP Kinase in apoptosis of hypoxia-induced osteoblasts (저산소 상태로 인한 조골세포 고사사기전에서 p-38 MAP kinase의 역할에 관한 연구)

  • Yoon, Jeong-Hyeon;Jeong, Ae-Jin;Kang, Kyung-Hwa;Kim, Sang-Cheol
    • The korean journal of orthodontics
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    • v.33 no.3 s.98
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    • pp.169-183
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    • 2003
  • Tooth movement by orthodontic force effects great tissue changes within the periodontium, especially by shifting the blood flow in the pressure side and resulting in a hypoxic state of low oxygen tension. The aim of this study is to elucidate the possible mechanism of apoptosis in response to hypoxia in MC3T3El osteoblasts, the main cells in bone remodeling during orthodontic tooth movement. MC3T3El osteoblasts under hypoxic conditions ($2\%$ orygen) resulted in apoptosis in a time-dependent manner as estimated by DNA fragmentation assay and nuclear morphology stained with fluorescent dye, Hoechst 33258. Pretreatment with Z-VAD-FMK, a pancaspase inhibitor, or Z-DEVD-CHO, a specific caspase-3 inhibitor, completely suppressed the DNA ladder in response to hypoxia. An increase in caspase-3-like protease (DEVDase) activity was observed during apoptosis, but no caspase-1 activity (YVADase) was detected. To confirm what caspases are involved in apoptosis, Western blot analysis was performed using anti-caspase-3 or -6 antibodies. The 10-kDa protein, corresponding to the active products of caspase-3, and the 10-kDa protein of the active protein of caspase-6 were generated in hypoxia-challenged cells in which the processing of the full length form of caspase-3 and -6 was evident. While a time course similar to this caspase-3 and -6 activation was evident, hypoxic stress caused the cleavage of lamin A, which was typical of caspase-6 activity. In addition, the stress elicited the release of cytochrome c into the cytosol during apoptosis. Furthermore, we observed that pre-treatment with SB203580, a selective p38 mitogen activated protein kinase inhibitor, attenuated the hypoxia-induced apoptosis. The addition of SB203S80 suppressed caspase-3 and -6-like protease activity by hypoxia up to $50\%$. In contrast, PD98059 had no effect on the hypoxia-induced apoptosis. To confirm the involvement of MAP kinase, JNK/SAPK, ERK, or p38 kinase assay was performed. Although p38 MAPK was activated in response to hypoxic treatment, the other MAPK -JNK/SAPK or ERK- was either only modestly activated or not at all. These results suggest that p38 MAPK is involved in hypoxia-induced apoptosis in MC3T3El osteoblasts.

Principal component analysis in C[11]-PIB imaging (주성분분석을 이용한 C[11]-PIB imaging 영상분석)

  • Kim, Nambeom;Shin, Gwi Soon;Ahn, Sung Min
    • The Korean Journal of Nuclear Medicine Technology
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    • v.19 no.1
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    • pp.12-16
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    • 2015
  • Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

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The Impacts of Need for Cognitive Closure, Psychological Wellbeing, and Social Factors on Impulse Purchasing (인지폐합수요(认知闭合需要), 심리건강화사회인소대충동구매적영향(心理健康和社会因素对冲动购买的影响))

  • Lee, Myong-Han;Schellhase, Ralf;Koo, Dong-Mo;Lee, Mi-Jeong
    • Journal of Global Scholars of Marketing Science
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    • v.19 no.4
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    • pp.44-56
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    • 2009
  • Impulse purchasing is defined as an immediate purchase with no pre-shopping intentions. Previous studies of impulse buying have focused primarily on factors linked to marketing mix variables, situational factors, and consumer demographics and traits. In previous studies, marketing mix variables such as product category, product type, and atmospheric factors including advertising, coupons, sales events, promotional stimuli at the point of sale, and media format have been used to evaluate product information. Some authors have also focused on situational factors surrounding the consumer. Factors such as the availability of credit card usage, time available, transportability of the products, and the presence and number of shopping companions were found to have a positive impact on impulse buying and/or impulse tendency. Research has also been conducted to evaluate the effects of individual characteristics such as the age, gender, and educational level of the consumer, as well as perceived crowding, stimulation, and the need for touch, on impulse purchasing. In summary, previous studies have found that all products can be purchased impulsively (Vohs and Faber, 2007), that situational factors affect and/or at least facilitate impulse purchasing behavior, and that various individual traits are closely linked to impulse buying. The recent introduction of new distribution channels such as home shopping channels, discount stores, and Internet stores that are open 24 hours a day increases the probability of impulse purchasing. However, previous literature has focused predominantly on situational and marketing variables and thus studies that consider critical consumer characteristics are still lacking. To fill this gap in the literature, the present study builds on this third tradition of research and focuses on individual trait variables, which have rarely been studied. More specifically, the current study investigates whether impulse buying tendency has a positive impact on impulse buying behavior, and evaluates how consumer characteristics such as the need for cognitive closure (NFCC), psychological wellbeing, and susceptibility to interpersonal influences affect the tendency of consumers towards impulse buying. The survey results reveal that while consumer affective impulsivity has a strong positive impact on impulse buying behavior, cognitive impulsivity has no impact on impulse buying behavior. Furthermore, affective impulse buying tendency is driven by sub-components of NFCC such as decisiveness and discomfort with ambiguity, psychological wellbeing constructs such as environmental control and purpose in life, and by normative and informational influences. In addition, cognitive impulse tendency is driven by sub-components of NFCC such as decisiveness, discomfort with ambiguity, and close-mindedness, and the psychological wellbeing constructs of environmental control, as well as normative and informational influences. The present study has significant theoretical implications. First, affective impulsivity has a strong impact on impulse purchase behavior. Previous studies based on affectivity and flow theories proposed that low to moderate levels of impulsivity are driven by reduced self-control or a failure of self-regulatory mechanisms. The present study confirms the above proposition. Second, the present study also contributes to the literature by confirming that impulse buying tendency can be viewed as a two-dimensional concept with both affective and cognitive dimensions, and illustrates that impulse purchase behavior is explained mainly by affective impulsivity, not by cognitive impulsivity. Third, the current study accommodates new constructs such as psychological wellbeing and NFCC as potential influencing factors in the research model, thereby contributing to the existing literature. Fourth, by incorporating multi-dimensional concepts such as psychological wellbeing and NFCC, more diverse aspects of consumer information processing can be evaluated. Fifth, the current study also extends the existing literature by confirming the two competing routes of normative and informational influences. Normative influence occurs when individuals conform to the expectations of others or to enhance his/her self-image. Whereas informational influence occurs when individuals search for information from knowledgeable others or making inferences based upon observations of the behavior of others. The present study shows that these two competing routes of social influence can be attributed to different sources of influence power. The current study also has many practical implications. First, it suggests that people with affective impulsivity may be primary targets to whom companies should pay closer attention. Cultivating a more amenable and mood-elevating shopping environment will appeal to this segment. Second, the present results demonstrate that NFCC is closely related to the cognitive dimension of impulsivity. These people are driven by careless thoughts, not by feelings or excitement. Rational advertising at the point of purchase will attract these customers. Third, people susceptible to normative influences are another potential target market. Retailers and manufacturers could appeal to this segment by advertising their products and/or services as products that can be used to identify with or conform to the expectations of others in the aspiration group. However, retailers should avoid targeting people susceptible to informational influences as a segment market. These people are engaged in an extensive information search relevant to their purchase, and therefore more elaborate, long-term rational advertising messages, which can be internalized into these consumers' thought processes, will appeal to this segment. The current findings should be interpreted with caution for several reasons. The study used a small convenience sample, and only investigated behavior in two dimensions. Accordingly, future studies should incorporate a sample with more diverse characteristics and measure different aspects of behavior. Future studies should also investigate personality traits closely related to affectivity theories. Trait variables such as sensory curiosity, interpersonal curiosity, and atmospheric responsiveness are interesting areas for future investigation.

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A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.155-174
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    • 2022
  • From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (

    ) were the topic modeling results for each research topic (
    ) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.

  • CComparative evaluation of the methods of producing planar image results by using Q-Metrix method of SPECT/CT in Lung Perfusion Scan (Lung Perfusion scan에서 SPECT-CT의 Q-Metrix방법과 평면영상 결과 산출방법에 대한 비교평가)

    • Ha, Tae Hwan;Lim, Jung Jin;Do, Yong Ho;Cho, Sung Wook;Noh, Gyeong Woon
      • The Korean Journal of Nuclear Medicine Technology
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      • v.22 no.1
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      • pp.90-97
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      • 2018
    • Purpose The lung segment ratio which is obtained through quantitative analyses of lung perfusion scan images is calculated to evaluate the lung function pre and post surgery. In this Study, the planar image production methods by using Q-Metrix (GE Healthcare, USA) program capable of not only quantitative analysis but also computation of the segment ratio after having performed SPECT/CT are comparatively evaluated. Materials and Methods Lung perfusion scan and SPECT/CT were performed on 50 lung cancer patients prior to surgery who visited our hospital from May 1, 2015 to September 13, 2016 by using Discovery 670(GE Healthcare, USA) equipment. AP(Anterior Posterior)method that uses planar image divided the frontal and rear images into three rectangular portions by means of ROI tool while PO(Posterior Oblique)method computed the segment ratio by dividing the right lobe into three parts and the left lobe into two parts on the oblique image. Segment ratio was computed by setting the ROI and VOI in the CT image by using Q-Metrix program and statistically analysis was performed with SPSS Ver. 23. Results Regarding the correlation concordance rate of Q-Metrix and AP methods, RUL(Right upper lobe), RML(Right middle lobe) and RLL(Right lower lobe) were 0.224, 0.035 and 0.447. LUL(Left upper lobe) and LLL(Left lower lobe) were found to be 0.643 and 0.456, respectively. In the PO method, the right lobe were 0.663, 0.623 and 0.702, respectively, while the left lobe were 0.754 and 0.823. When comparison was made by using the Paired sample T-test, Right lobe were $11.6{\pm}4.5$, $26.9{\pm}6.2$ and $17.8{\pm}4.2$, respectively in the AP method. Left lobe were $28.4{\pm}4.8$ and $15.4{\pm}5.6$. The right lobe of PO had values of $17.4{\pm}5.0$, $10.5{\pm}3.6$ and $27.3{\pm}6.0$, while the left lobe had values of $21.6{\pm}4.8$ and $23.1{\pm}6.6$, thereby having statistically significant difference in comparison to the Q-Metrix method for each of the lobes (P<0.05). However, there was no statistically significant difference in Right middle lobe (P>0.05). Conclusion The AP method showed low concordance rate in correlation with the Q-Metrix method. However, PO method displayed high concordance rate overall. although AP method had significant differences in all lobes, there was no significant difference in Right middle lobe of PO method. Therefore, at the time of production of lung perfusion scan results, utilization of Q-Metrix method of SPECT/CT would be useful in computation of accurate resultant values. Moreover, it is deemed possible to expect obtain more practical sectional computation result values by using PO method at the time of planar image acquisition.


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