arXiv Computer Vision October 22, 2026 By K S Nithurshen, Saurabh J. Shigwan

SpineContextResUNet: A Computationally Efficient Residual UNet for Spine CT Segmentation

Read the original on arXiv Computer Vision →

SpineContextResUNet is a lightweight 3D Residual U‑Net that uses a Context Block with parallel multi‑dilated convolutions to efficiently capture long‑range anatomical dependencies for spine CT segmentation. It achieves Dice scores of 88.17% on VerSe2020 and 88.13% on CTSpine1K while maintaining a small ~1.7 M parameter footprint. Compared to resource‑heavy Transformers and baselines that fail on commodity hardware, SpineContextResUNet delivers robust inference on edge devices such as the Nvidia Jetson Orin Nano.

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