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OCTN: Neural OCT Representations for Robot-Guided Precision Intervention
Optical coherence tomography (OCT) offers compact, contactless, micron-scale imaging suitable for intraoperative guidance, but native OCT volumes are discretely sampled, anisotropic, and currently inefficient for downstream geometric reasoning and robot integration. We present OCTN (pronounced "octane"), an implicit neural representation framework that converts volumetric OCT scans into a continuous, differentiable, and spatially faithful tissue-intensity field. OCTN uses a two-stage hybrid training strategy that combines supervision from acquired voxels with inter-slice interpolations, preser
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-06T20:01:34.000Z
First collected: 2026-09-20T21:12:06.801Z. This is not the publication date.