Degradation-Aware Blur-Segmentation of Brain Tumor
Multimodal 3D MRI brain tumor segmentation is a pivotal step in radiotherapy target delineation, surgical planning and post-treatment assessment. Existing methods often assume artifact-free MRI images. However, inevitable patient motion during scanning introduces artifacts and blur that degrade boundary and texture features, leading to poor segmentation performance. To bridge this gap, we introduce Degradation-Aware Blur-Segmentation Net (DABSeg), a synchronous deblurring 3D multimodal MRI segmentation network that unifies blur removal and accurate segmentation. Specifically, we propose a feature-domain motion-deblurring stem to compensate for blur and rebalance intensity. Concurrently, t...
| Authors | Yuchun Wang, Xiaosong Li, Gefei Liang et al. |
|---|---|
| Primary category | eess.IV |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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