Automatic Pleural Line Extraction and COVID-19 Scoring from Lung Ultrasound Data

Leonardo Carrer, Elena Donini, Daniele Marinelli, Massimo Zanetti, Federico Mento, Elena Torri, Andrea Smargiassi, Riccardo Inchingolo, Gino Soldati, Libertario Demi, Francesca Bovolo, Lorenzo Bruzzone

Research output: Contribution to journalArticlepeer-review


Recent works highlighted the significant potential of lung ultrasound (LUS) imaging in the management of subjects affected by COVID-19. In general, the development of objective, fast, and accurate automatic methods for LUS data evaluation is still at an early stage. This is particularly true for COVID-19 diagnostic. In this article, we propose an automatic and unsupervised method for the detection and localization of the pleural line in LUS data based on the hidden Markov model and Viterbi Algorithm. The pleural line localization step is followed by a supervised classification procedure based on the support vector machine (SVM). The classifier evaluates the healthiness level of a patient and, if present, the severity of the pathology, i.e., the score value for each image of a given LUS acquisition. The experiments performed on a variety of LUS data acquired in Italian hospitals with both linear and convex probes highlight the effectiveness of the proposed method. The average overall accuracy in detecting the pleura is 84% and 94% for convex and linear probes, respectively. The accuracy of the SVM classification in correctly evaluating the severity of COVID-19 related pleural line alterations is about 88% and 94% for convex and linear probes, respectively. The results as well as the visualization of the detected pleural line and the predicted score chart, provide a significant support to medical staff for further evaluating the patient condition.

Original languageEnglish
Article number9127515
Pages (from-to)2207-2217
Number of pages11
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Issue number11
Publication statusPublished - Nov 2020


  • COVID-19
  • diagnostic
  • lung ultrasound (LUS) imaging
  • signal processing
  • support vector machine (SVM)
  • Viterbi algorithm

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering


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