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lung-segmentation-unet – AI Model by maja011235 | AlphaNeural AI
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This model for
lung segmentation in chest X-ray images
is based on a custom U-Net architecture enhanced with:
ASPP (Atrous Spatial Pyramid Pooling)
in the bottleneck to capture multi-scale context and anatomical structures of varying size
SE (Squeeze-and-Excitation) blocks
to enhance channel-wise attention and suppress irrelevant features such as ribs or background noise
Dilated convolutions
in the decoder to increase the receptive field without sacrificing spatial resolution
The model was trained on the
COVID-19 Radiography Database
and evaluated on a dedicated internal validation set.
It achieves a
Dice score of 98.7%
, demonstrating good performance in segmenting lung fields.
