Papers › S2S2: Semantic Stacking for Robust Semantic Segmentation in Medical Imaging
S2S2: Semantic Stacking for Robust Semantic Segmentation in Medical Imaging
Yimu Pan, Sitao Zhang, Alison D. Gernand, Jeffery A. Goldstein, James Z. Wang
Robustness and generalizability in medical image segmentation are often hindered by scarcity and limited diversity of training data, which stands in contrast to the variability encountered during inference. While conventional strategies -- such as domain-specific augmentation, specialized architectures, and tailored training procedures -- can alleviate these issues, they depend on the availability and reliability of domain knowledge. When such knowledge is unavailable, misleading, or improperly applied, performance may deteriorate. In response, we introduce a novel, domain-agnostic, add-on, and data-driven strategy inspired by image stacking in image denoising. Termed ``semantic stacking,'' our method estimates a denoised semantic representation that complements the conventional segmentation loss during training. This method does not depend on domain-specific assumptions, making it broadly applicable across diverse image modalities, model architectures, and augmentation techniques. Through extensive experiments, we validate the superiority of our approach in improving segmentation performance under diverse conditions. Code is available at https://github.com/ymp5078/Semantic-Stacking.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Medical Image Segmentation | Automatic Cardiac Diagnosis Challenge (ACDC) | TransUNet | Avg DSC | 90.4 | #15 of 20 | Archive leaderboard | report |
| Medical Image Segmentation | CVC-ClinicDB | FCBFormer | mean Dice | 0.9488 | #8 of 48 | Archive leaderboard | report |
| Medical Image Segmentation | Kvasir-SEG | FCBFormer | mean Dice | 0.932 | #13 of 58 | Archive leaderboard | report |
| Medical Image Segmentation | Synapse multi-organ CT | TransUNet | Avg DSC | 81.19 | #16 of 23 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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