Lung Segmentation with Lightweight Convolutional Attention Residual U-Net

Lung Segmentation with Lightweight Convolutional Attention Residual U-Net

<b>Background:</b> Examining chest radiograph images (CXR) is an intricate and time-consuming process, sometimes requiring the identification of many anomalies at the same time. Lung segmentation is key to overcoming this challenge through different deep learning (DL) techniques. Many re...

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Bibliographic Details
Main Authors: Meftahul Jannat, Shaikh Afnan Birahim, Mohammad Asif Hasan, Tonmoy Roy, Lubna Sultana, Hasan Sarker, Samia Fairuz, Hanaa A. Abdallah
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Diagnostics
Subjects:
lung segmentation
convolutional block attention module
dice loss
lightweight residual U-Net
CXR images
Online Access:https://www.mdpi.com/2075-4418/15/7/854
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