Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

10.3791/61737 ◽  
2020 ◽  
Author(s):  
Arrigo Cattabriga ◽  
Maria Adriana Cocozza ◽  
Giulio Vara ◽  
Francesca Coppola ◽  
Rita Golfieri
Keyword(s):  
Ground Glass ◽  
Ct Segmentation ◽  
Lung Ct

The Impact of Interstitial Diseases Patterns on Lung CT Segmentation

2021 ◽  
Author(s):  
Francisco Silva ◽  
Tania Pereira ◽  
Joana Morgado ◽  
Antonio Cunha ◽  
Helder P. Oliveira
Keyword(s):  
Ct Segmentation ◽  
The Impact ◽  
Lung Ct

scholarly journals The Volume Ratio of Ground Glass Opacity in Early Lung CT Predicts Mortality in Acute Paraquat Poisoning

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0121691 ◽  
Author(s):  
Xin Kang ◽  
Da-Yong Hu ◽  
Chang-Bin Li ◽  
Xin-Hua Li ◽  
Shu-Ling Fan ◽  
...  
Keyword(s):  
Volume Ratio ◽  
Ground Glass Opacity ◽  
Ground Glass ◽  
Paraquat Poisoning ◽  
Lung Ct

Matrix Patterns Based Active Appearance Models for Lung CT Segmentation

2014 ◽  
Vol 1049-1050 ◽  
pp. 1312-1315
Author(s):  
Yong Li ◽  
Qing Zhu Wang
Keyword(s):  
Appearance Model ◽  
Active Appearance Models ◽  
Shape Model ◽  
New Approach ◽  
Superior Result ◽  
Two Dimensional Image ◽  
Appearance Models ◽  
Active Appearance ◽  
Ct Segmentation ◽  
Lung Ct

Segmentation of diseased lungs in CT images is a nontrivial problem. As Active Appearance Model (AAM) has been applied effectively in this field, we propose a new approach for the construction of traditional AAM to segment the lung fields more accurately and efficiently: Matrixes based AAM (MatAAM). MatAAM is based on two-dimensional image matrixes rather one-dimensional vectors. Its appearance matrix does not need to be transformed into a vector prior to computing the appearance parameter. Instead, a covariance matrix is constructed directly using the normalized appearance matrixes and its eigenvectors are derived for the appearance parameter. The experiment results were compared to other landmark-based methods: Snake, Active Shape Model (ASM), AAM and several modified versions of them. For segmentation of lungs especially diseased lungs, MatAAM performed a superior result in both precision and efficiency.

scholarly journals Computed Tomography Features of COVID-19 in Children: A Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Ji-Gan Wang ◽  
Yu-Fang Mo ◽  
Yu-heng Su ◽  
Li-chuang Wang ◽  
Guang-bing Liu ◽  
...  
Keyword(s):  
Pleural Effusion ◽  
Assessment Tool ◽  
Meta Analysis ◽  
Ct Imaging ◽  
Chest Ct ◽  
Ground Glass ◽  
Imaging Features ◽  
Lung Lesions ◽  
Lung Lobe ◽  
Lung Ct

Objectives: To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice. Methods: We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu. Reports on chest CT imaging features of children with COVID-19 from January 1, 2020, to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software. Results: Thirty-seven articles (1747 children) were included in this study. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8-70.6%), with a rate of 61.0% (95% CI: 50.8-71.2%) in China and 67.8% (95% CI: 57.1-78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7-48.3%), multiple lung lobe lesions 65.1% (95% CI: 55.1-67.9%), and bilateral lung lesions 61.5% (95% CI: 58.8-72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported three cases of white lung, another reported two cases of pneumothorax, and another one case of bullae. CONCLUSION: The lung CT results of children with COVID-19 are usually normal or slightly atypica, with a low sensitivity and specificity compared with that in adults. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. CLINICAL IMPACT: Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool.

A Review of Ground Glass Opacity Detection Methods in Lung CT Images

2017 ◽  
Vol 13 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Lv Linying ◽  
Liu Xiabi ◽  
Zhou Chunwu ◽  
Zhao Xinming ◽  
Zhao Yanfeng
Keyword(s):  
Ground Glass Opacity ◽  
Ct Images ◽  
Detection Methods ◽  
Ground Glass ◽  
Lung Ct

scholarly journals Development and Validation of a New Risk Score for Infection From Coronavirus (SARS-COV-2) [Ri.S.I.Co], That We Learned on the Field Treating Coronavirus Disease (COVID-19) Patients

2020 ◽  
Author(s):  
Paola Fugazzola ◽  
Francesco Favi ◽  
Matteo Tomasoni ◽  
Claudia Zaghi ◽  
Chiara Casadei ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Risk Score ◽  
Risk Model ◽  
Hospitalized Patients ◽  
Ground Glass ◽  
Diagnostic Tools ◽  
Nucleic Acid Detection ◽  
Multivariable Logistic Regression Model ◽  
Lung Ct ◽  
Glass Pattern

Abstract Background: The pandemic of Coronavirus Disease 2019 asked to change the organization of entire hospitals to try to prevent them to become epidemiological clusters. The actually adopted diagnostic tools are lacking of sensibility or specificity. The aim of the study is to create an easy-to-get risk score (Ri.S.I.Co., RIsk Score for Infection from new COronavirus), developed on the field, to stratify patients admitted to the hospital according to their risk of Covid-19 infection.Methods: This prospective study included all patients who were consecutively admitted in the “suspected COVID-19 department” of the Bufalini Hospital, Cesena (Italy). All clinical, radiological and laboratory predictors were included in a multivariable logistic regression model to create a risk model. A simplified model was internally ed externally validated. Two score thresholds for stratifying the probability of COVID-19 infection were introduced.Results: From 11th March to 5th April 2020, 200 patients were consecutively admitted. A Ri.S.I.Co lower than 2 had an higher sensibility than SARS-Cov-2 nucleic acid detection (96,2% vs 65,4%, p<0,001). The presence of ground glass pattern at lung-CT scan had a lower sensibility than a Ri.S.I.Co lower than 2 (88,5% vs 96,2%, p<0,001) and a lower specificity than a Ri.S.I.Co higher than 6 (75,0% vs 96,9%, p<0,001). Conclusions: We believe that the Ri.S.I.Co could allow to stratify admitted patients according to their risk, avoiding hospitals becoming themselves the main Covid-19 carriers. Furthermore, it could guide clinicians in starting therapies early in severe-onset cases with a high probability of COVID-19, before molecular SARS-CoV-2 infection is confirmed.Strengths and limitations of this study:Ri.S.I.Co., (RIsk Score for Infection from new COronavirus) is an easy-to-get risk-score developed on the field, to stratify patients admitted to the hospital according to their risk of Covid-19 infection.We believe that the Ri.S.I.Co could allow to stratify admitted patients according to their risk, before molecular SARS-CoV-2 infection is confirmed, avoiding hospitals becoming themselves the main Covid-19 carriers.Ri.S.I.Co had an higher sensibility than SARS-Cov-2 nucleic acid detection and an higher sensibility and specificity of the presence of ground glass pattern at lung-CT scan.Ri.S.I.Co was developed and validated on hospitalized patients, further studies would be necessary to understand if it is generalizable to non-hospitalized patients or on the population of other countries with different mean age, different prevalence of comorbidities and different health policies.

scholarly journals COVID-19 complicated by strange pulmonary fibrosis

2020 ◽  
Author(s):  
Zhifeng Jiang ◽  
Aiqiao Feng
Keyword(s):  
Pulmonary Fibrosis ◽  
Early Stage ◽  
Early Infection ◽  
Ground Glass ◽  
Lung Ct

Abstract BackgroundThe lung CT of COVID-19 has characteristic changes, showing scattered ground-glass changes extrapulmonary zone. However, we observe a case of early infection of COVID-19 in a patient who did not show classic CT changes, but shows characteristic pulmonary fibrosis.Case presentationWe reported a patient who was infected in the early stage of the COVID epidemic without any treatment. The extrapulmonary zone showed symmetrical and diffuse fibrotic changes.Conclusionsthe lungs of COVID-19 may not show scattered ground-glass changes, but show symmetrical, diffuse pulmonary fibrosis in extrapulmonary, suggests that there may be other mechanisms other than infection involved in the changes in the lungs.

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