# RDTE-UNet: A Boundary and Detail Aware UNet for Precise Medical Image Segmentation

arXiv: https://arxiv.org/abs/2511.01328 · HTML: https://mlsanity.com/paper/2511.01328/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 28 references that are in the map.
- First posted on arXiv 3 Nov 2025.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation](https://mlsanity.com/paper/2102.04306/) (2021)
- [Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation](https://mlsanity.com/paper/2105.05537/) (2021)
- [UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation](https://mlsanity.com/paper/2004.08790/) (2020)
- [MISSFormer: An Effective Medical Image Segmentation Transformer](https://mlsanity.com/paper/2109.07162/) (2021)
- [Mixed Transformer U-Net For Medical Image Segmentation](https://mlsanity.com/paper/2111.04734/) (2021)
- [LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation](https://mlsanity.com/paper/2107.08623/) (2021)
- [TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation](https://mlsanity.com/paper/2107.05274/) (2021)
- [MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection](https://mlsanity.com/paper/2403.02148/) (2024)
- [Multi-Scale and Detail-Enhanced Segment Anything Model for Salient Object Detection](https://mlsanity.com/paper/2408.04326/) (2024)
- [EulerNet: Adaptive Feature Interaction Learning via Euler's Formula for CTR Prediction](https://mlsanity.com/paper/2304.10711/) (2023)
- [SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation](https://mlsanity.com/paper/2406.14896/) (2024)
- [Adaptive Rectangular Convolution for Remote Sensing Pansharpening](https://mlsanity.com/paper/2503.00467/) (2025)
- [Bootstrapping Audio-Visual Segmentation by Strengthening Audio Cues](https://mlsanity.com/paper/2402.02327/) (2024)
- [RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation](https://mlsanity.com/paper/2501.08458/) (2025)

## Abstract (arXiv)

Medical image segmentation is essential for computer-assisted diagnosis and treatment planning, yet substantial anatomical variability and boundary ambiguity hinder reliable delineation of fine structures. We propose RDTE-UNet, a segmentation network that unifies local modeling with global context to strengthen boundary delineation and detail preservation. RDTE-UNet employs a hybrid ResBlock detail-aware Transformer backbone and three modules: ASBE for adaptive boundary enhancement, HVDA for fine-grained feature modeling, and EulerFF for fusion weighting guided by Euler's formula. Together, these components improve structural consistency and boundary accuracy across morphology, orientation, and scale. On Synapse and BUSI dataset, RDTE-UNet has achieved a comparable level in terms of segmentation accuracy and boundary quality.