Semi-Automatic A-Line Detection and Confidence Scoring in Lung Ultrasound
| Autor: | Oriane Thiery, Garance Martin, Isabelle Bloch, Martin Dres, Umar Saleem, Andrea Pinna |
|---|---|
| Přispěvatelé: | Systèmes Electroniques (SYEL), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Learning, Fuzzy and Intelligent systems (LFI), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Neurophysiologie Respiratoire Expérimentale et Clinique (UMRS 1158), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Service de Médecine Intensive et Réanimation - R3S [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), BioSerenity, IEEE, Thiery, Oriane |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Lung Ultrasound [INFO.INFO-IM]Computer Science [cs]/Medical Imaging [INFO.INFO-IM] Computer Science [cs]/Medical Imaging [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] automatic detection [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing A-lines confidence estimation [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing |
| Zdroj: | BioCAS 2022-Biomedical Circuits and Systems Conference BioCAS 2022-Biomedical Circuits and Systems Conference, IEEE, Oct 2022, Taipei, Taiwan HAL |
| Popis: | International audience; Weaning a patient from mechanical ventilation is a critical task in Intensive Care Units, but it can be made safer by using Lung Ultrasound scoring. This scoring is currently done visually by specialists based on Lung Ultrasound artifacts among which are A-lines. Automating this scoring may help standardizing results and saving time for clinicians. In this paper, we propose a method to automatically detect A-lines from a manual delineation of the pleural line, and by using both the intensity profile of the LUS image and morphological operations. A score is then assigned to significant lines and represents the possibility of them being A-lines. The proposed method shows promising results in differentiating A-lines from other elements with an Area Under the Curve of 0.95; furthermore, using a threshold at 0.5 to detect A-lines leads to very good performances with an accuracy of 95% and a F0.5-score of 0.84. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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