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A Novel Approach to Chest X-ray Lung Segmentation Using U-net and Modified Convolutional Block Attention Module
Lung segmentation in chest X-ray (CXR) images is a crucial task in medical image analysis, aiding in accurate disease diagnosis and treatment planning. This study presents an improved U-Net architecture by integrating a Convolutional Block Attention Module (CBAM) to enhance segmentation performance.
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