Research map / Detection and segmentation / Open-set and few-shot detection
Alternative Baselines for Low-Shot 3D Medical Image Segmentation—An Atlas Perspective
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the Siamese correspondence baseline instead of LT-Net | CANDI 1-shot segmentation · CANDI | Dice (%) mean: 82.3 (2.5) -> 83.0 (1.8) | Helped |
| Use five atlases with Siamese-Baseline instead of one | Siamese-Baseline · CANDI | Dice (%) mean: 83.0 (1.8) -> 86.2 (2.1) | Helped |
| Use IDA-Baseline instead of LT-Net | Multi-organ 1-shot segmentation · Multi-organ | Dice (%) mean: 58.05 -> 61.28 | Helped |
| Use five atlases instead of one | IDA-Baseline · Multi-organ | Dice (%) mean: 61.28 -> 68.61 | Helped |
| Add backward correspondence and forward-backward cycle consistency (ablation) | Siamese-Baseline · Multi-organ 5-shot | Dice (%) mean: 63.64 -> 65.78 | Helped |
| Add individual-difference modeling to the cycle-consistency model (ablation) | Siamese-Baseline · Multi-organ 5-shot | Dice (%) mean: 65.78 -> 68.61 | Helped |
Closest papers by meaning
- LT-Net: Label Transfer by Learning Reversible Voxel-Wise Correspondence for One-Shot Medical Image Segmentation (CVPR 2020 · similarity 0.89)
- 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)
- SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image Segmentation (AAAI 2025 · similarity 0.85)
- Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation (NeurIPS 2024 · similarity 0.85)
- VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging (CVPR 2025 · similarity 0.85)
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