Improved A-Line and B-Line Detection in Lung Ultrasound Using Deep Learning with Boundary-Aware Dice Loss

Improved A-Line and B-Line Detection in Lung Ultrasound Using Deep Learning with Boundary-Aware Dice Loss

Lung ultrasound (LUS) is a non-invasive bedside imaging technique for diagnosing pulmonary conditions, especially in critical care settings. A-lines and B-lines are important features in LUS images that help to assess lung health and identify changes in lung tissue. However, accurately detecting and...

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Bibliographic Details
Main Authors: Soolmaz Abbasi, Assefa Seyoum Wahd, Shrimanti Ghosh, Maha Ezzelarab, Mahesh Panicker, Yale Tung Chen, Jacob L. Jaremko, Abhilash Hareendranathan
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Bioengineering
Subjects:
lung ultrasound
TransUNet
boundary-aware dice loss
deep learning
medical image processing
Online Access:https://www.mdpi.com/2306-5354/12/3/311
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