Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation

• URL: http://arxiv.org/abs/2602.19412v1
• Date: Mon, 23 Feb 2026 01:10:04 GMT
• Title: Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation
• Authors: Mingjie Li, Yizheng Chen, Md Tauhidul Islam, Lei Xing,
• Abstract summary: U-Nets have been instrumental in advancing biomedical image segmentation (BIS)<n>One reason is the conventional down-sampling techniques that prioritize computational efficiency at the expense of information retention.<n>This paper introduces a simple but effective strategy, we call it Stair Pooling, which moderates the pace of down-sampling and reduces information loss.
• Score: 14.794177610936046
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: U-Net architectures have been instrumental in advancing biomedical image segmentation (BIS) but often struggle with capturing long-range information. One reason is the conventional down-sampling techniques that prioritize computational efficiency at the expense of information retention. This paper introduces a simple but effective strategy, we call it Stair Pooling, which moderates the pace of down-sampling and reduces information loss by leveraging a sequence of concatenated small and narrow pooling operations in varied orientations. Specifically, our method modifies the reduction in dimensionality within each 2D pooling step from $\frac{1}{4}$ to $\frac{1}{2}$. This approach can also be adapted for 3D pooling to preserve even more information. Such preservation aids the U-Net in more effectively reconstructing spatial details during the up-sampling phase, thereby enhancing its ability to capture long-range information and improving segmentation accuracy. Extensive experiments on three BIS benchmarks demonstrate that the proposed Stair Pooling can increase both 2D and 3D U-Net performance by an average of 3.8\% in Dice scores. Moreover, we leverage the transfer entropy to select the optimal down-sampling paths and quantitatively show how the proposed Stair Pooling reduces the information loss.

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