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yoreurehehee/
Text_Guided_Decision_Support_System

Name: Text_Guided_Decision_Support_System
Availability: InStock

brain-tumor-segmentation

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Text-Guided Decision Support System

Modality-Aware Adaptive Fusion for Brain Tumor Segmentation under Missing MRI Modalities.

Model Description

A 2.5D U-Net with cross-attention text fusion and adaptive gate that dynamically adjusts text contribution based on modality availability. Trained on BraTS 2020 (369 patients) with systematic modality dropout.

Parameters: 21.4M
Input: 4 MRI modalities (FLAIR, T1CE, T2, T1) — any subset supported
Output: 3-region segmentation (ET, NCR, ED) + clinical report
Text encoder: Frozen BioBERT (768-dim)

Performance (BraTS 2020, 74-patient test set)

Metric	Score
15-scenario avg Dice	0.7644
T1CE-missing avg Dice	0.8036
vs RFNet (T1CE-missing)	+0.097

Usage

python

# See https://github.com/HeeKuk99/Text_guided_decision_support_system
python app.py  # launches Gradio demo at localhost:7860

Citation

bibtex

@article{textguided2026,
  title={Modality-Aware Adaptive Text-Visual Fusion for Robust Brain Tumor 
         Segmentation with Missing MRI Modalities},
  year={2026}
}

yoreurehehee/Text_Guided_Decision_Support_System