Literature DB >> 24277902

Automated B-line scoring on thoracic sonography.

Laura J Brattain1, Brian A Telfer, Andrew S Liteplo, Vicki E Noble.   

Abstract

With the proliferation of portable sonography and the increase in nontraditional users, there is an increased need for automated decision support to standardize results. We developed algorithms to evaluate the presence or absence of "B-lines" on thoracic sonography as a marker for interstitial fluid. Algorithm performance was compared against an average of scores from 2 expert clinical sonographers. On the set for algorithm development, 90% of the scores matched the average expert scores with differences of 1 or less. On the independent set, a perfect match was achieved. We believe that these are the first reported results in computerized B-line scoring.

Keywords:  B-lines; diagnostic assistant; extravascular lung water; pulmonary edema; thoracic sonography

Mesh:

Year:  2013        PMID: 24277902     DOI: 10.7863/ultra.32.12.2185

Source DB:  PubMed          Journal:  J Ultrasound Med        ISSN: 0278-4297            Impact factor:   2.153


  13 in total

Review 1.  Machine learning for medical ultrasound: status, methods, and future opportunities.

Authors:  Laura J Brattain; Brian A Telfer; Manish Dhyani; Joseph R Grajo; Anthony E Samir
Journal:  Abdom Radiol (NY)       Date:  2018-04

2.  Optimizing B-lines on lung ultrasound: an in-vitro to in-vivo pilot study with clinical implications.

Authors:  Christopher N Schmickl; Aravind Ajakumar Menon; Rajanigandha Dhokarh; Bhavna Seth; Frank Schembri
Journal:  J Clin Monit Comput       Date:  2019-05-14       Impact factor: 2.502

3.  Line Detection as an Inverse Problem: Application to Lung Ultrasound Imaging.

Authors:  Nantheera Anantrasirichai; Wesley Hayes; Marco Allinovi; David Bull; Alin Achim
Journal:  IEEE Trans Med Imaging       Date:  2017-06-29       Impact factor: 10.048

4.  Investigating training-test data splitting strategies for automated segmentation and scoring of COVID-19 lung ultrasound images.

Authors:  Roshan Roshankhah; Yasamin Karbalaeisadegh; Hastings Greer; Federico Mento; Gino Soldati; Andrea Smargiassi; Riccardo Inchingolo; Elena Torri; Tiziano Perrone; Stephen Aylward; Libertario Demi; Marie Muller
Journal:  J Acoust Soc Am       Date:  2021-12       Impact factor: 2.482

Review 5.  Lung B-line artefacts and their use.

Authors:  Christoph F Dietrich; Gebhard Mathis; Michael Blaivas; Giovanni Volpicelli; Armin Seibel; Daniel Wastl; Nathan S S Atkinson; Xin-Wu Cui; Mei Fan; Dong Yi
Journal:  J Thorac Dis       Date:  2016-06       Impact factor: 2.895

6.  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

Review 7.  Ultrasound of extravascular lung water: a new standard for pulmonary congestion.

Authors:  Eugenio Picano; Patricia A Pellikka
Journal:  Eur Heart J       Date:  2016-05-12       Impact factor: 29.983

8.  Lung ultrasound imaging in avian influenza A (H7N9) respiratory failure.

Authors:  Nga Wing Tsai; Chun Wai Ngai; Ka Leung Mok; James W Tsung
Journal:  Crit Ultrasound J       Date:  2014-05-20

9.  Computerized Diagnostic Assistant for the Automatic Detection of Pneumothorax on Ultrasound: A Pilot Study.

Authors:  Shane M Summers; Eric J Chin; Brit J Long; Ronald D Grisell; John G Knight; Kurt W Grathwohl; John L Ritter; Jeffrey D Morgan; Jose Salinas; Lorne H Blackbourne
Journal:  West J Emerg Med       Date:  2016-03-02

Review 10.  Thoracic Ultrasound: What Non-radiologists Need to Know.

Authors:  Jonathan P Williamson; Chris Grainge; Ahilan Parameswaran; Scott H Twaddell
Journal:  Curr Pulmonol Rep       Date:  2017-01-27
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