{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T14:52:13Z","timestamp":1784040733039,"version":"3.55.0"},"reference-count":36,"publisher":"Acoustical Society of America (ASA)","issue":"6","funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01EB021396"],"award-info":[{"award-number":["R01EB021396"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010686","name":"H2020 European Institute of Innovation and\n              Technology","doi-asserted-by":"publisher","award":["UltraOn EIT Digital 2021"],"award-info":[{"award-number":["UltraOn EIT Digital 2021"]}],"id":[{"id":"10.13039\/100010686","id-type":"DOI","asserted-by":"publisher"}]},{"name":"VRT foundation","award":["Covid-19 call 2020 grant number 1"],"award-info":[{"award-number":["Covid-19 call 2020 grant number 1"]}]}],"content-domain":{"domain":["pubs.aip.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,12,1]]},"abstract":"<jats:p>Ultrasound in point-of-care lung assessment is becoming increasingly relevant. This is further reinforced in the context of the COVID-19 pandemic, where rapid decisions on the lung state must be made for staging and monitoring purposes. The lung structural changes due to severe COVID-19 modify the way ultrasound propagates in the parenchyma. This is reflected by changes in the appearance of the lung ultrasound images. In abnormal lungs, vertical artifacts known as B-lines appear and can evolve into white lung patterns in the more severe cases. Currently, these artifacts are assessed by trained physicians, and the diagnosis is qualitative and operator dependent. In this article, an automatic segmentation method using a convolutional neural network is proposed to automatically stage the progression of the disease. 1863 B-mode images from 203 videos obtained from 14 asymptomatic individual,14 confirmed COVID-19 cases, and 4 suspected COVID-19 cases were used. Signs of lung damage, such as the presence and extent of B-lines and white lung areas, are manually segmented and scored from zero to three (most severe). These manually scored images are considered as ground truth. Different test-training strategies are evaluated in this study. The results shed light on the efficient approaches and common challenges associated with automatic segmentation methods.<\/jats:p>","DOI":"10.1121\/10.0007272","type":"journal-article","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T13:29:00Z","timestamp":1638797340000},"page":"4118-4127","update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":25,"title":["Investigating training-test data splitting strategies for automated\n          segmentation and scoring of COVID-19 lung ultrasound images"],"prefix":"10.1121","volume":"150","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5673-3834","authenticated-orcid":false,"given":"Roshan","family":"Roshankhah","sequence":"first","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, North Carolina State University 1 , Raleigh, North Carolina 27606, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasamin","family":"Karbalaeisadegh","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology 2 , Atlanta, Georgia 30332, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hastings","family":"Greer","sequence":"additional","affiliation":[{"name":"Kitware Inc. 3 , Clifton Park, New York 12065, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6571-7809","authenticated-orcid":false,"given":"Federico","family":"Mento","sequence":"additional","affiliation":[{"name":"Ultrasound Laboratory, University of Trento 4 , Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gino","family":"Soldati","sequence":"additional","affiliation":[{"name":"Azienda USL Toscana nord ovest Sede di Lucca, Diagnostic and Interventional Ultrasound Unit Lucca 5 , Toscana, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Smargiassi","sequence":"additional","affiliation":[{"name":"Pulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario Agostino Gemelli IRCCS. Roma 6 , Lazio, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Riccardo","family":"Inchingolo","sequence":"additional","affiliation":[{"name":"Pulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario Agostino Gemelli IRCCS. Roma 6 , Lazio, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elena","family":"Torri","sequence":"additional","affiliation":[{"name":"BresciaMed 7 , Brescia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiziano","family":"Perrone","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Istituto di Ricovero e Cura a Carattere Scientifico 8 , San Matteo, Pavia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Aylward","sequence":"additional","affiliation":[{"name":"Kitware Inc. 3 , Clifton Park, New York 12065, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0635-2133","authenticated-orcid":false,"given":"Libertario","family":"Demi","sequence":"additional","affiliation":[{"name":"Ultrasound Laboratory, University of Trento 4 , Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marie","family":"Muller","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, North Carolina State University 1 , Raleigh, North Carolina 27606, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"231","published-online":{"date-parts":[[2021,12,6]]},"reference":[{"key":"2024081218311374900_c1","unstructured":"CDC, \u201cCases in U.S.|CDC,\u201d available at https:\/\/covid.cdc.gov\/covid-data-tracker\/#datatracker-home (Last viewed 28\n          January 2021)."},{"key":"2024081218311374900_c2","doi-asserted-by":"publisher","first-page":"1451","DOI":"10.1038\/s41418-020-0530-3","article-title":"COVID-19 infection: The perspectives on immune\n            responses","volume":"27","year":"2020","journal-title":"Cell Death Differ."},{"issue":"11","key":"2024081218311374900_c3","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1001\/jama.2020.1585","article-title":"Clinical characteristics of 138 hospitalized patients\n            with 2019 novel coronavirus-infected pneumonia in Wuhan, China","volume":"323","year":"2020","journal-title":"JAMA, J. 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