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10.1109/TUFFC.2021.3107598 http://scihub22266oqcxt.onion/10.1109/TUFFC.2021.3107598 34428140!8905613!34428140     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       IEEE+Trans+Ultrason+Ferroelectr+Freq+Control 2022 ; 69 (1): 73-83 Nephropedia Template TP {{tp|p=34428140|t=2022. Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound Images for Severity Assessment of COVID-19 Pneumonia |pdf=|usr=}}{{34428140}} gab.com Text Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound Images for Severity Assessment of COVID-19 Pneumonia JO: IEEE Trans Ultrason Ferroelectr Freq Control http://www.kidney.de/pget.php?&tw=1&pmid=34428140 #FOAvip Specific patterns of lung ultrasound (LUS) images are used to assess the severity of coronavirus disease 2019 (COVID-19) pneumonia, while such assessment is mainly based on clinicians' qualitative and subjective observations. In this study, we quantitatively analyze the LUS images to assess the severity of COVID-19 pneumonia by characterizing the patterns related to the pleural line (PL) and B-lines (BLs). Twenty-seven patients with COVID-19 pneumonia, including 13 moderate cases, seven severe cases, and seven critical cases, are enrolled. Features related to the PL, including the thickness (TPL) and roughness of the PL (RPL), and the mean (MPLI) and standard deviation (SDPLI) of the PL intensities are extracted from the LUS images. Features related to the BLs, including the number (NBL), accumulated width (AWBL), attenuation coefficient (ACBL), and accumulated intensity (AIBL) of BLs, are also extracted. The correlations of these features with the disease severity are evaluated. The performances of the binary severe/non-severe classification are assessed for each feature and support vector machine (SVM) classifiers with various combinations of features as input. Several features, including the RPL, NBL, AWBL, and AIBL, show significant correlations with disease severity (all ). The classification performance is optimal using the SVM classifier using all the features as input (area under the receiver operating characteristic (ROC) curve = 0.96, sensitivity = 0.93, and specificity = 1). These findings demonstrate that the proposed method may be a promising tool for automatic grading diagnosis and follow-up of patients with COVID-19 pneumonia. Twit Text FOAVip Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound Images for Severity Assessment of COVID-19 Pneumonia ????IEEE Trans Ultrason Ferroelectr Freq Control http://www.kidney.de/pget.php?&tw=1&pmid=34428140 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34428140 #FOAvip English Wikipedia <ref>{{Cite pmid|34428140}}</ref> Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound Images for Severity Assessment of COVID-19 Pneumonia #MMPMID34428140 Wang Y; Zhang Y; He Q; Liao H; Luo J IEEE Trans Ultrason Ferroelectr Freq Control 2022[Jan]; 69 (1): 73-83 PMID34428140show ga Specific patterns of lung ultrasound (LUS) images are used to assess the severity of coronavirus disease 2019 (COVID-19) pneumonia, while such assessment is mainly based on clinicians' qualitative and subjective observations. In this study, we quantitatively analyze the LUS images to assess the severity of COVID-19 pneumonia by characterizing the patterns related to the pleural line (PL) and B-lines (BLs). Twenty-seven patients with COVID-19 pneumonia, including 13 moderate cases, seven severe cases, and seven critical cases, are enrolled. Features related to the PL, including the thickness (TPL) and roughness of the PL (RPL), and the mean (MPLI) and standard deviation (SDPLI) of the PL intensities are extracted from the LUS images. Features related to the BLs, including the number (NBL), accumulated width (AWBL), attenuation coefficient (ACBL), and accumulated intensity (AIBL) of BLs, are also extracted. The correlations of these features with the disease severity are evaluated. The performances of the binary severe/non-severe classification are assessed for each feature and support vector machine (SVM) classifiers with various combinations of features as input. Several features, including the RPL, NBL, AWBL, and AIBL, show significant correlations with disease severity (all ). The classification performance is optimal using the SVM classifier using all the features as input (area under the receiver operating characteristic (ROC) curve = 0.96, sensitivity = 0.93, and specificity = 1). These findings demonstrate that the proposed method may be a promising tool for automatic grading diagnosis and follow-up of patients with COVID-19 pneumonia. |*COVID-19[MESH] |*Pneumonia/diagnostic imaging[MESH] |Humans[MESH] |Lung/diagnostic imaging[MESH] |SARS-CoV-2[MESH]Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound I(epmc).pdf DeepDyve Pubget Overpricing