| --- |
| library_name: pytorch |
| tags: |
| - medical-imaging |
| - pathology |
| - microscopy |
| - leukemia |
| - blast-cells |
| - deep-learning |
| - computer-vision |
| --- |
| |
| # 🧬 Blast Cell Detection |
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| ## 📌 Overview |
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| This repository contains a PyTorch-trained model for **blast cell detection in microscopic blood smear images**. |
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| ## 🧪 Dataset |
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| The model was trained using the publicly available: |
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| **ALL-IDB (Acute Lymphoblastic Leukemia Image Database)** |
| 🔗 https://scotti.di.unimi.it/all/ |
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| --- |
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| ## 📦 Model File |
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| - `resnet_unet_attention.pth` → PyTorch model weights |
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| --- |
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| ## 🚀 Usage |
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| To use this model, you must define the same architecture used during training, then load the weights as follows: |
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| ```python |
| import torch |
| |
| model = ... # define your model architecture here |
| model.load_state_dict(torch.load("trained-model.pth", map_location="cpu")) |
| model.eval() |
| ``` |
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| --- |
| license: cc-by-2.0 |
| --- |
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