| license: mit | |
| tags: | |
| - brain-tumor-segmentation | |
| - radiology-report-generation | |
| - brats2020 | |
| - medical-imaging | |
| - text-guided-segmentation | |
| # TextBraTS-arch3: Lightweight 2.5D Text-Guided Brain Tumor Segmentation | |
| A lightweight 2.5D convolutional network for brain tumor segmentation + radiology report generation on the TextBraTS/BraTS2020 dataset. | |
| ## Results (93-patient official test set) | |
| | Metric | Value | | |
| |---|---| | |
| | Avg Dice | 83.8% | | |
| | Avg HD95 | 3.41 mm | | |
| | ET Dice | 79.7 | | |
| | WT Dice | 89.5 | | |
| | TC Dice | 82.3 | | |
| Beats TextCSP SOTA (4.81mm) and TextBraTS (5.13mm) on HD95 at **10.4M parameters**. | |
| ## Repo structure | |
| - `segmentation/best_avg.pt` — segmentation model checkpoint (epoch 64, val-selected) | |
| - `t5/model.safetensors` + tokenizer — fine-tuned T5-small report generation head | |
| - `t5/img_proj.pt` — image-conditioned projection weights for T5 | |
| ## Architecture | |
| - **Input:** 2.5D — 4 MRI modalities × 3 adjacent axial slices = 12 channels at 128×128 | |
| - **Encoder:** 4-stage ResNet (32→64→128→256 ch) | |
| - **Text:** Offline RadBERT embeddings (zero forward-pass text cost) | |
| - **Decoder:** Attention-gated skips + soft cascade WT→TC→ET | |
| - **Report gen:** ImageConditionedT5-small (8 image-prefix soft tokens) | |
| ## Dataset | |
| TextBraTS / BraTS2020 — official split: 220 train / 56 val / 93 test | |