SpineContextResUNet: A Computationally Efficient Residual UNet for Spine CT Segmentation
Automated segmentation of the vertebral column in Computed Tomography (CT) scans is a prerequisite for pathological assessment and surgical planning. However, state-of-the-art methods, particularly those based on Transformers or large-scale ensembles, demand substantial GPU resources, creating a barrier for clinical adoption in resource-constrained environments or on edge devices. To address this, we introduce SpineContextResUNet, a computationally efficient 3D Residual U-Net designed for rapid spinal localization. Our architecture integrates a lightweight Context Block that employs parallel multi-dilated convolutions to capture long-range anatomical dependencies without the high latency ...
| Authors | K S Nithurshen, Saurabh J. Shigwan |
|---|---|
| Primary category | cs.CV |
| Published | 20 May 2026 |
| Last updated at source | 20 May 2026 |
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