Jesteban247/brats-segresnet-monai
By Jesteban247 · ↓ 0 · ♥ 0 · Updated 2025-10-23
What's in this repo
This page lists the files in Jesteban247/brats-segresnet-monai, including model_final_20251009_122935.onnx.
- 1 ONNX models (.onnx files)
- 8 files, including 2 .png, 1 .md, 1 .txt, 1 .onnx, 1 .json, 1 .csv
- Last updated 2025-10-23
ONNX files
| File | Size | Download |
|---|---|---|
| model_final_20251009_122935.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
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.
Model info
Created: 2025-10-23
Updated: 2025-10-23
View on Hugging Face