Journal article

Automatic deep learning-based pleural effusion classification in lung ultrasound images for respiratory pathology diagnosis

Chung-Han Tsai, Jeroen van der Burgt, Damjan Vukovic, Nancy Kaur, Libertario Demi, David Canty, Andrew Wang, Alistair Royse, Colin Royse, Kavi Haji, Jason Dowling, Girija Chetty, Davide Fontanarosa

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS | ELSEVIER SCI LTD | Published : 2021

Abstract

Lung ultrasound (LUS) imaging as a point-of-care diagnostic tool for lung pathologies has been proven superior to X-ray and comparable to CT, enabling earlier and more accurate diagnosis in real-time at the patient's bedside. The main limitation to widespread use is its dependence on the operator training and experience. COVID-19 lung ultrasound findings predominantly reflect a pneumonitis pattern, with pleural effusion being infrequent. However, pleural effusion is easy to detect and to quantify, therefore it was selected as the subject of this study, which aims to develop an automated system for the interpretation of LUS of pleural effusion. A LUS dataset was collected at the Royal Melbour..

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