Literature DB >> 30530325

Automatic Detection of B-Lines in In Vivo Lung Ultrasound.

Ramin Moshavegh, Kristoffer Lindskov Hansen, Hasse Moller-Sorensen, Michael Bachmann Nielsen, Jorgen Arendt Jensen.   

Abstract

This paper proposes an automatic method for accurate detection and visualization of B-lines in ultrasound lung scans, which provides a quantitative measure for the number of B-lines present. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Herlev, Denmark) driving a 5.5-MHz linear transducer (BK Ultrasound). Four healthy subjects and four patients, after major surgery with pulmonary edema, were scanned at four locations on each lung for B-line examination. Eight sequences of 50 frames were acquired for each subject yielding 64 sequences in total. The proposed algorithm was applied to all 3200 in-vivo lung ultrasound images. The results showed that the average number of B-lines was 0.28±0.06 (Mean±Std) in scans belonging to the patients compared to 0.03 ± 0.06 (Mean ± Std) in the healthy subjects. Also, the Mann-Whitney test showed a significant difference between the two groups with the p -value of 0.015, and indicating that the proposed algorithm was able to differentiate between the healthy volunteers and the patients. In conclusion, the method can be used to automatically and to quantitatively characterize the distribution of B-lines for diagnosing pulmonary edema.

Entities:  

Year:  2018        PMID: 30530325     DOI: 10.1109/TUFFC.2018.2885955

Source DB:  PubMed          Journal:  IEEE Trans Ultrason Ferroelectr Freq Control        ISSN: 0885-3010            Impact factor:   2.725


  6 in total

1.  The Evolution of Ultrasound in Critical Care: From Procedural Guidance to Hemodynamic Monitor.

Authors:  Igor Barjaktarevic; Jon-Émile S Kenny; David Berlin; Maxime Cannesson
Journal:  J Ultrasound Med       Date:  2020-08-04       Impact factor: 2.153

2.  Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

Authors:  Jiangang Chen; Chao He; Jintao Yin; Jiawei Li; Xiaoqian Duan; Yucheng Cao; Li Sun; Menghan Hu; Wenfang Li; Qingli Li
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2021-06-29       Impact factor: 2.725

3.  Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound Images for Severity Assessment of COVID-19 Pneumonia.

Authors:  Yuanyuan Wang; Yao Zhang; Qiong He; Hongen Liao; Jianwen Luo
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2021-12-31       Impact factor: 3.267

4.  Quantitative pleural line characterization outperforms traditional lung texture ultrasound features in detection of COVID-19.

Authors:  Laith R Sultan; Yale Tung Chen; Theodore W Cary; Khalid Ashi; Chandra M Sehgal
Journal:  J Am Coll Emerg Physicians Open       Date:  2021-04-02

Review 5.  State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses.

Authors:  Federico Mento; Umair Khan; Francesco Faita; Andrea Smargiassi; Riccardo Inchingolo; Tiziano Perrone; Libertario Demi
Journal:  Ultrasound Med Biol       Date:  2022-09-22       Impact factor: 3.694

6.  Application of Critical Care Ultrasound in Patients With COVID-19: Our Experience and Perspective.

Authors:  Tongjuan Zou; Wanhong Yin; Yan Kang
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2020-09-01       Impact factor: 3.267

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.