Research map / 3D vision / Face and shape
Vox2Cortex: Fast Explicit Reconstruction of Cortical Surfaces From 3D MRI Scans With Geometric Deep Neural Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Vox2Cortex rather than DeepCSR | Cortical surface reconstruction · ADNI_large, left WM surface | ASSD (mm): 0.422 -> 0.345 | Helped |
| Use Vox2Cortex rather than DeepCSR | Cortical surface reconstruction · OASIS, left WM surface | ASSD (mm): 0.360 -> 0.315 | Helped |
| Use Vox2Cortex rather than DeepCSR | Cortical surface reconstruction · Test-retest | ASSD (mm): 0.357 -> 0.228 | Helped |
| Use a lower-resolution template at test time (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.455 | Hurt |
| Sample image features from the encoder only (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.453 | No clear effect |
| Replace curvature-weighted Chamfer with classic Chamfer (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.852 | Hurt |
| Omit nearest-neighbor information exchange between meshes (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.444 | Hurt |
| Use an ellipsoidal template instead of the smoothed cortex template (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.459 | Hurt |
| Omit the voxel decoder (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.413 | No clear effect |
| Apply Laplacian loss to absolute coordinates instead of displacement fields (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.467 | Hurt |
| Replace graph-convolution layers with linear layers (ablation) | Vox2Cortex · ADNI_small, left WM surface | ASSD (mm): 0.401 -> 0.538 | Hurt |
| Use a lower-resolution template at test time (ablation) | Vox2Cortex · Test-retest | Inference time per scan: 18.0s -> 2.1s | Helped |
Closest papers by meaning
- Coupled Reconstruction of Cortical Surfaces by Diffeomorphic Mesh Deformation (NeurIPS 2023 · similarity 0.92)
- Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction (ICLR 2024 · similarity 0.86)
- FlatClip: Reusing Image Foundation Models for fMRI Representation Learning via Cortical Flatmaps (NeurIPS 2026 · similarity 0.85)
- GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction (NeurIPS 2025 · similarity 0.84)
- M-plicits: Neural Implicit Surfaces via Nested Multiscale Residuals (NeurIPS 2026 · similarity 0.84)
- Efficient Noise Calculation in Deep Learning-based MRI Reconstructions (ICML 2025 · similarity 0.84)
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