• 제목/요약/키워드: respiratory model

검색결과 434건 처리시간 0.03초

Respiratory Motion Correction on PET Images Based on 3D Convolutional Neural Network

  • Hou, Yibo;He, Jianfeng;She, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권7호
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    • pp.2191-2208
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    • 2022
  • Motion blur in PET (Positron emission tomography) images induced by respiratory motion will reduce the quality of imaging. Although exiting methods have positive performance for respiratory motion correction in medical practice, there are still many aspects that can be improved. In this paper, an improved 3D unsupervised framework, Res-Voxel based on U-Net network was proposed for the motion correction. The Res-Voxel with multiple residual structure may improve the ability of predicting deformation field, and use a smaller convolution kernel to reduce the parameters of the model and decrease the amount of computation required. The proposed is tested on the simulated PET imaging data and the clinical data. Experimental results demonstrate that the proposed achieved Dice indices 93.81%, 81.75% and 75.10% on the simulated geometric phantom data, voxel phantom data and the clinical data respectively. It is demonstrated that the proposed method can improve the registration and correction performance of PET image.

대학생의 호흡기감염 예방행위에 영향을 미치는 요인 (Factors Influencing the Respiratory Infection Preventive Behavior among College Students)

  • 이선희;유하나
    • 실천공학교육논문지
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    • 제15권2호
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    • pp.449-457
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    • 2023
  • 본 서술적 조사연구의 목적은 대학생의 호흡기감염 예방행위에 영향을 미치는 요인으로 건강신념과 호흡기 감염관리 자기효능감을 알아보고자 시도되었다. 대상자는 경상북도 K 시 일개 대학에 재학 중인 학생 178명으로 2020년 9월 1일부터 10월16일까지 구조화된 설문지로 자료를 수집하였다. 연구결과는 다음과 같다; 건강신념은 참여자의 성별(t=-2.86, p=.005), 전공계열(F=2.95, p=.034), 처방된 약물 복용 유무(t=2.18, p=.030)와 유의한 차이가 있었다. 호흡기 감염관리에 대한 자기효능감은 대학생의 성별(t=-3.56, p=<.001), 전공계열(F=4.59, p=.004)과 유의한 차이가 있었다. 건강신념(r=.276, p<.001)과 호흡기 감염관리에 대한 자기효능감(r=.195, p<.001)은 호흡기감염 예방행위에 정적 상관이 있었다. 다중회귀분석 결과 호흡기 감염관리에 대한 자기효능감(β=.66, p<.001)이 호흡기감염 예방 행동에 유의한 영향을 미치는 것으로 나타났고, 모형의 설명력은 43%로 나타났다. 따라서, 대학생의 호흡기감염을 예방하기 위한 행동을 촉진하기 위해서는 호흡기 감염관리에 대한 자기효능감을 강화할 수 있는 프로그램이 개발되어야 할 것이다.

미세먼지 in vivo 모델에서 호흡기 질환에 대한 한약의 효과에 관한 연구 동향 분석 (Review on the Effects of Herbal Medicine on Respiratory Diseases in In Vivo Particulate Matter Models)

  • 우성천;이수원;박양춘
    • 대한한방내과학회지
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    • 제44권3호
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    • pp.418-438
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    • 2023
  • Objective: This study was conducted to review the effects of herbal medicine on respiratory diseases induced by the treatment of particulate matter in in vivo animal models. Methods: Literature searches were performed in seven databases (Pubmed, Embase, Cochrane Library, KISS, KTKP, OASIS, and ScienceON). After the searched studies were screened based on the inclusion/exclusion criteria, the publication date, origin, used animals, induction of particulate matter models, herbal medicine used for intervention, study design, outcome measure, and results of studies were analyzed. Results: Among a total of 972 studies primarily searched, 34 studies were finally included in our study. Of this number, 29 studies induced animal models by using only particulate matter, and 5 studies induced animal models with respiratory diseases, such as asthma and chronic obstructive pulmonary disease, by using particulate matter and other materials. In the selected studies, the treatments of herbal medicine in particulate matter models suppressed oxidative stress and inflammation in lung tissue, bronchoalveolar lavage fluid, and blood as well as lung injury in histological analysis. Conclusion: The results of this study suggest that herbal medicine is effective in treating respiratory diseases induced by particulate matter. These results are also expected to be useful data for designing further studies. However, more systematically designed in vivo studies related to particulate matter are needed.

Meta-analysis of Associations between the MDM2-T309G Polymorphism and Prostate Cancer Risk

  • Chen, Tao;Yi, Shang-Hui;Liu, Xiao-Yu;Liu, Zhi-Gang
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권9호
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    • pp.4327-4330
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    • 2012
  • The mouse double minute 2 (MDM2) gene plays a key role in the p53 pathway, and the SNP 309T/G single-nucleotide polymorphism in the promoter region of MDM2 has been shown to be associated with increased risk of cancer. However, no consistent results were found concerning the relationships between the polymorphism and prostate cancer risk. This meta-analysis, covering 4 independent case-control studies, was conducted to better understand the association between MDM2-SNP T309G and prostate cancer risk focusing on overall and subgroup aspects. The analysis revealed, no matter what kind of genetic model was used, no significant association between MDM2-SNP T309G and prostate cancer risk in overall analysis (GT/TT: OR = 0.84, 95%CI = 0.60-1.19; GG/TT: OR = 0.69, 95%CI = 0.43-1.11; dominant model: OR = 0.81, 95%CI= 0.58-1.13; recessive model: OR = 1.23, 95%CI = 0.95-1.59). In subgroup analysis, the polymorphism seemed more likely to be a protective factor in Europeans (GG/TT: OR = 0.52, 95%CI = 0.31-0.87; recessive model: OR = 0.58, 95%CI = 0.36-0.95) than in Asian populations, and a protective effect of the polymorphism was also seen in hospital-based studies in all models (GT/TT: OR = 0.74, 95%CI = 0.57-0.97; GG/TT: OR = 0.55, 95%CI = 0.38-0.79; dominant model: OR = 0.69, 95%CI = 0.54-0.89; recessive model: OR = 0.70, 95%CI = 0.51-0.97). However, more primary studies with a larger number of samples are required to confirm our findings.

Comparison of Epidermal Growth Factor Receptor Mutations between Primary Tumors and Lymph Nodes in Non-small Cell Lung Cancer: a Review and Meta-analysis of Published Data

  • Wang, Feng;Fang, Ping;Hou, Dan-Yang;Leng, Zai-Jun;Cao, Le-Jie
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권11호
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    • pp.4493-4497
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    • 2014
  • Background: Epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) can predict the clinical response to tyrosine kinase inhibitor (TKI) therapy. However, EGFR mutations may be different in primary tumors (PT) and metastatic lymph nodes (MLN). The aim of this study was to compare EGFR mutations between PT and the corresponding MLN in NSCLC patients, and provide some guidelines for clinical treatment using TKI therapy. Materials and Methods: A systematic review and meta-analysis was performed with several research databases. Relative risk (RR) with the 95% confidence interval (CI) were used to investigate the EGFR mutation status between PT and the corresponding MLN. A random-effects model was used. Results: 9 publications involving 707 patients were included in the analysis. It was found that activation of EGFR mutations identified in PT and the corresponding MLN was 26.4% (187/707) and 19.9% (141/707), respectively. The overall discordance rate in our meta-analysis was 12.2% (86/707). The relative risk (RR) for EGFR mutation in PT relative to MLN was 1.33 (95%CI: 1.10-1.60; random-effects model). There was no significant heterogeneity between the studies ($I^2$=5%, p=0.003). Conclusions: There exists a considerable degree of EGFR mutation discrepancy in NSCLC between PT and corresponding MLN, suggesting that tumor heterogeneity might arise at the molecular level during the process of metastasis.

데이터마이닝 모형을 활용한 호흡기질환의 주요인 선별 (Identification of major risk factors association with respiratory diseases by data mining)

  • 이제영;김현지
    • Journal of the Korean Data and Information Science Society
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    • 제25권2호
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    • pp.373-384
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    • 2014
  • 데이터 마이닝이란 대량의 데이터나 복잡한 구조의 데이터들을 정교한 통계분석과 모델링 테크닉을 이용하여 정확히 식별되지 않는 패턴이나 자료간의 상관관계를 밝혀내어 여러 가지 결과를 예측해 내는 통계적 기법이다. 이러한 데이터 마이닝 기법은 금융, 통신, 유통, 의학 등 다양한 분야에 활용되는데, 본 연구에서는 의학 분야에 적용하여 호흡기질환에 영향을 끼치는 요인을 선별하였다. 분석은 2012년도 경상북도 지역사회건강조사에 참여한 사람 중 의사에게서 폐결핵, 천식, 알레르기성 비염을 진단받은 경험이 있는 호흡기질환군과 건강군으로 정리한 자료를 대상으로 하였다. 호흡기질환이 영향을 끼치는 주요인을 선별하기 위해 인공신경망, 로지스틱 회귀모형, 베이지안 네트워크, C5.0, CART 기법을 이용하였다. 공정한 모형 평가를 위해 전체 데이터를 훈련용 데이터와 검증용 데이터로 나누었고, 훈련용 데이터에서 설정된 모형을 검증용 데이터에 적용하여 정확도를 비교하였다. 그 결과 CART가 최적 모형으로 선정되었으며 CART의 의사결정나무를 통하여 우울감 인지 여부, 현재 흡연여부, 스트레스 인지 여부 순으로 호흡기질환에 영향을 주는 것으로 나타났다. 그리고 호흡기질환의 주요인들에 대한 오즈비를 구하여 개별적인 영향력에 대해서도 밝혔다.

Evaluation of different media for ex vivo porcine lung culture model

  • Yang, Myeon-Sik;Zhou, Zixiong;Khatun, Amina;Nazki, Salik;Jeong, Chang Gi;Kim, Won Il;Lee, Sang Myeong;Kang, Seog-Jin;Lim, Chae Woong;Kim, Bumseok
    • 한국동물위생학회지
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    • 제41권4호
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    • pp.263-269
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    • 2018
  • Developing drugs targeting respiratory pathogen is essential to control respiratory diseases. Many experiments have been performed under in vivo situation. However, in vivo experiments have economical and ethical issues. The objective of this study was to determine the possibility of developing an ex vivo lung culture system with possible application for respiratory infection studies. After isolating lungs from naïve pigs, agarose-inflated lung tissues were prepared and sliced manually. These sliced lung tissues were then subsequently placed on 24-well plates. Eight different combinations of media were used to determine the optimum ex vivo lung culture condition. In addition, lung tissues were infected with porcine reproductive and respiratory syndrome (PRRS) virus at a titer of $1{\times}10^4\;TCID_{50}/mL$. Virus growth was confirmed by titration in MARC-145 cells at 2, 4, 6 days post infection (dpi). We found that ex vivo lung culture in physiological environment was not media specific based on histopathology and cytotoxicity. However, under virus-infected condition, thickened alveolar walls in the lung tissues and stable virus titers at 2, 4, 6 dpi were shown in F12K medium suggesting that it was useful for tissue maintenance and virus infection using PRRS virus infected lung tissues. The present study shows the possibility of using porcine ex vivo lung model for respiratory infection studies.

심층학습을 이용한 영상정보 기반 호흡신호 분류 (Classification of Respiratory States based on Visual Information using Deep Learning)

  • 송주현;이덕우
    • 한국산학기술학회논문지
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    • 제22권5호
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    • pp.296-302
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    • 2021
  • 본 논문에서는 영상정보에 기반한 호흡상태 분류 방법을 제안한다. 호흡신호는 초광대역 레이더 센서를 이용하여 획득하고 호흡신호의 값으로 이루어진 1차원 그래프 대신 그래프의 영상 정보가 담긴 2차원 정보 기반으로 호흡상태를 분류한다. 호흡상태의 분류는 심층신경망 모델을 사용하고, 심층신경망 모델은 호흡신호 그래프가 포함된 2차원 영상의 특징들을 학습하여 영상기반의 호흡상태 분류의 결과를 제공한다. 기존의 레이더 센서 기반 호흡신호의 상태 분류는 1차원 벡터의 구성요소 값 및 그 값들의 변화량을 이용하여 회귀, 심층학습 방법을 적용하였다. 그러나 1차원 그래프 기반의 호흡상태 분류는 다양한 형태의 정상호흡 상태에 대한 분류 성능에서 한계를 보였다. 본 논문에서는 호흡 신호로부터 얻은 그래프의 이미지 자체를 2차원 입력 신호로 사용하여 심층 신경망 모델을 적용하여 분류를 수행하였다. 본 논문에서 제안하는 영상정보 기반의 호흡상태 분류는 기존의 1차원 벡터 기반 호흡상태 분류 대비 호흡상태 분류의 정확도를 약 10% 향상 시켰다. 또한 기존의 두 가지 호흡상태 (정상 및 비정상) 분류에서 확장하여 세 가지 호흡상태 (정상1, 정상2, 비정상) 분류를 수행하였다.

Ovalbumin으로 유발된 천식 동물모델에서 GGX의 효과 (Effects of GGX on an Ovalbumin-induced Asthma Mice Model)

  • 김태현;양원경;이수원;우성천;김승형;박양춘
    • 대한한방내과학회지
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    • 제44권3호
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    • pp.294-312
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    • 2023
  • Objective: The purpose of this study is to evaluate the effects of GGX on an ovalbumin (OVA)-induced asthma mice model. Methods: Balb/c mice were challenged with OVA and then treated with three concentrations of GGX (100, 200, and 400 mg/kg). After sacrifice, the bronchoalveolar lavage fluid (BALF) or lungs of the mice were analyzed by fluorescence-activated cell sorting, ELISA, real-time PCR, H&E, Masson's trichrome, PAS and AB-PAS staining, and immunohistofluorescence staining. Results: GGX significantly inhibited the increase of total cells, immune cells (lymphocyte, neutrophils, macrophage, CD4+, CD8+, CD4+CD69+, CD62L-CD44high+, Gr-1+SiglecF-), and the expression of cytokines (IL-4, IL-5, IL-13, IFN-γ) in BALF. It also significantly inhibited the increase of total cells, immune cells (lymphocyte, neutrophils, eosinophil/macrophage, CD3+, CD19+, CD3+CD193+, CD4+, CD8+, CD4+CD69+, CD62L-CD44high+, and Gr-1+SiglecF-), and the expression of IL-13, TARC, and MCP-1 in lung tissue. GGX decreased the severity of histological lung injury and the expressions of STAT3 and GATA3. Conclusion: This study suggests the probability of using GGX for the treatment of asthma by inhibiting inflammatory immune response.

만성폐쇄성폐질환 동물모델에서 SGX01의 폐손상 억제 효과 (Inhibitory Effects of SGX01 on Lung Injury of COPD Mice Model)

  • 박재준;양원경;유이란;김승형;박양춘
    • 대한한방내과학회지
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    • 제40권4호
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    • pp.567-581
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    • 2019
  • Objective: This study aimed to evaluate the inhibitory effects of SGX01 on the lung injuries of COPD mice model. Materials and Methods: This study was carried out in two ways: in vitro and in vivo. In vitro, L929 cells were challenged with LPS, and then treated with six concentrations of SGX01 (10, 30, 50, 100, 300, and $500{\mu}g/ml$) and analyzed by ELISA. In vivo, C57BL/6 mice were challenged with LPS and cigarette smoking solution (CSS), and then treated with a vehicle only (control group), dexamethasone 3 mg/kg (dexa group), or a SGX01 200 mg/kg (SGX01 group). After sacrifice, the BALF or lung tissue was analyzed with Cytospin, FACS, ELISA, real-time PCR and H&E, and Masson's trichrome staining. Results: SGX01 significantly decreased NO, $TNF-{\alpha}$, and IL-6 on L929 cells challenged with LPS. In the COPD model, SGX01 significantly inhibited the increase of neutrophils, $TNF-{\alpha}$, IL-17A, CXCL-1, MIP2, CD8+ cells in BALF, and $TNF-{\alpha}$, $IL-1{\beta}$ mRNA expression in lung tissue. It also decreased the severity of the histological lung injury. Conclusion: This study suggests the usability of SGX01 for COPD patients by controlling lung tissue injury.