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brats-segresnet-monai
Jesteban247/brats-segresnet-monai
brats-segresnet-monai is a image segmentation model from Jesteban247. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for monai. The card lists the license as apache-2.0.
This model fine-tunes SegResNet for 3D brain tumor segmentation (Tumor Core, Whole Tumor, Enhancing Tumor) using the BraTS2020 Dataset. The model was trained with mixed precision (FP16) using MONAI and Accelerate for…
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Updated Oct 23, 2025
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At a glance
- Task
- Image Segmentation
- Library
- monai
- License
- apache-2.0
- Access
- Public
- Created
- Oct 23, 2025
- Updated
- Oct 23, 2025
- SHA
- 4cb42f30
Model card
From the Hugging Face model README
🧠 SegResNet — BraTS Brain Tumor Segmentation (3D, FP16)
This model fine-tunes SegResNet for 3D brain tumor segmentation (Tumor Core, Whole Tumor, Enhancing Tumor) using the
BraTS2020 Dataset.
The model was trained with mixed precision (FP16) using MONAI and Accelerate for efficient multi-GPU training.
⚙️ Configuration
| Attribute | Value |
|---|---|
| Base Model | SegResNet (MONAI) |
| Dataset | BraTS2020 (Kaggle) |
| Epochs | 150 |
| Batch Size (per GPU) | 2 |
| ROI Size | 128×128×128 |
| Optimizer | Adam (LR=0.0001, WD=1e-05) |
| Precision | FP16 (mixed=True) |
| Framework | MONAI + Accelerate |
| Device | Multi-GPU (num_processes=2) |
🩺 Example Segmentation
2D Prediction
3D Prediction
📈 Results (Final Test Metrics)
| Metric | Average | Tumor Core (TC) | Whole Tumor (WT) | Enhancing Tumor (ET) |
|---|---|---|---|---|
| Dice | 0.789 | 0.775 | 0.874 | 0.719 |
| Precision | 0.847 | 0.856 | 0.938 | 0.749 |
| Recall | 0.771 | 0.762 | 0.839 | 0.713 |
| Accuracy | 0.987 | 0.999 | 0.999 | 0.964 |
| Loss | 0.192 | - | - | - |
FP16 mixed precision enabled faster training while maintaining high segmentation accuracy.
No data augmentation was used to preserve original image fidelity.
- Task
- Image Segmentation
- Library
- monai
- License
- apache-2.0
- Languages
- en
- Created
- Oct 23, 2025
- Updated
- Oct 23, 2025