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Status: This model repository is a placeholder for the SegFormer-B0 fine-tuned on brain MRI ventricle segmentation data. The current HydroMorph pipeline uses a classical computer vision approach (adaptive thresholding + Otsu + connected-component analysis) which achieves 100% sensitivity at 7.5ms/image without requiring GPU inference.
| Approach | Sensitivity | Specificity | Speed | GPU Required |
|---|---|---|---|---|
| Classical CV (current) | 100% | 50% | 7.5 ms/image | No |
| SegFormer-B0 (planned) | TBD | TBD | ~50 ms/image | Yes |
| VLM Agent (GPT-4o) | 50% | 80% | 8 sec/image | No (API) |
| Cascade (CV → VLM) | 100% | ~80% | — | — |
1@inproceedings{rech2026hydromorph,
2 title={HydroMorph: AI-Assisted Automated Evans Index Measurement
3 Combining Classical Morphometry with Vision-Language Model
4 Self-Correction},
5 author={Rech, Matheus Machado},
6 booktitle={Hydrocephalus 2026 World Congress},
7 year={2026},
8 address={Athens, Greece}
9}