FabianRei
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Update README on deepliif weights
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README.md
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@@ -31,6 +31,7 @@ This repository contains two critical checkpoints for the APEDIA pipeline:
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- `tp_pred_model_checkpoint.pth`: This model checkpoint is responsible for detecting tumor areas in PD-L1 stained Whole-Slide Image (WSI) patches.
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- `seg_model_checkpoint.pth`: This checkpoint powers the detection and classification of cell types within tumor patches, distinguishing between background, non-tumor cells, PD-L1 positive cells, and PD-L1 negative cells.
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## Usage
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The model weights will be automatically downloaded by the APEDIA library when executing predictions to calculate the Tumor Proportion Score (TPS). Ensure that you have the latest version of APEDIA installed to use these models effectively.
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- `tp_pred_model_checkpoint.pth`: This model checkpoint is responsible for detecting tumor areas in PD-L1 stained Whole-Slide Image (WSI) patches.
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- `seg_model_checkpoint.pth`: This checkpoint powers the detection and classification of cell types within tumor patches, distinguishing between background, non-tumor cells, PD-L1 positive cells, and PD-L1 negative cells.
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- `deepliif_latest_net_G1.pth`: Derived from the DeepLIIF library, this is the checkpoint of a generative adversarial network (GAN) designed to isolate the Hema (hematoxylin) component in IHC-stained slides. For more information on DeepLIIF, visit their [GitHub repository](https://github.com/nadeemlab/DeepLIIF/tree/main).
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## Usage
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The model weights will be automatically downloaded by the APEDIA library when executing predictions to calculate the Tumor Proportion Score (TPS). Ensure that you have the latest version of APEDIA installed to use these models effectively.
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