Research map / 3D vision / Depth and stereo
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| combine 2D and 3D base-learners with the learned meta-learner | HVSMR 2016 segmentation · HVSMR 2016 | Overall score: 0.2 -> 0.21 | Helped |
| add unlabeled test images for transductive meta-learner training | Our meta-learner · HVSMR 2016 | Overall score: 0.215 -> 0.234 | Helped |
| add unlabeled training images for semi-supervised meta-learner training | Our meta-learner · HVSMR 2016 | Overall score: -0.036 -> 0.063; -0.045 -> 0.038 | Helped |
| add NN-fit after random-fit (ablation) | Pseudo-label-supervised meta-learner · HVSMR 2016 | Overall score: 0.199 -> 0.215 | Helped |
| add raw image input to the pseudo-label representation (ablation) | Meta-learner · HVSMR 2016 | Overall score: 0.075 -> 0.192 | Helped |
| use pseudo-label supervision instead of ground-truth-only supervision (ablation) | Meta-learner · HVSMR 2016 | Overall score: 0.192 -> 0.215 | Helped |
| mix ground-truth and pseudo-label supervision rather than using pseudo-labels alone (ablation) | Transductive meta-learner · HVSMR 2016 | Overall score: 0.234 -> 0.224 | Hurt |
| add NN-fit after random-fit (ablation) | Pseudo-label-supervised meta-learner · Mouse piriform cortex | Rand F-score: 0.9963 -> 0.9967 | Helped |
| add unlabeled test images for transductive training (ablation) | NN-fit meta-learner · Mouse piriform cortex | Rand F-score: 0.9967 -> 0.9970 | Helped |
Closest papers by meaning
- Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation (NeurIPS 2024 · similarity 0.86)
- E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation (NeurIPS 2024 · similarity 0.86)
- Mamba Goes HoME: Hierarchical Soft Mixture-of-Experts for 3D Medical Image Segmentation (NeurIPS 2025 · similarity 0.86)
- VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging (CVPR 2025 · similarity 0.85)
- UniPro: Unified Multi-Mode Medical Image Segmentation from 2D Images to 3D Volumes via Propagation (NeurIPS 2026 · similarity 0.85)
- Pancakes: Consistent Multi-Protocol Image Segmentation Across Biomedical Domains (NeurIPS 2025 · similarity 0.85)
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