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Update model: lung-segmentation-unet

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  2. README.md +9 -0
  3. model.keras +3 -0
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+ This model for **lung segmentation in chest X-ray images** is based on a custom U-Net architecture enhanced with:
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+ - **ASPP (Atrous Spatial Pyramid Pooling)** in the bottleneck to capture multi-scale context and anatomical structures of varying size
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+ - **SE (Squeeze-and-Excitation) blocks** to enhance channel-wise attention and suppress irrelevant features such as ribs or background noise
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+ - **Dilated convolutions** in the decoder to increase the receptive field without sacrificing spatial resolution
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+ The model was trained on the [COVID-19 Radiography Database](https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database) and evaluated on a dedicated internal validation set.
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+ It achieves a **Dice score of 98.7%**, demonstrating good performance in segmenting lung fields.
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