pith:CONITIDR
Towards Real-Time Autonomous Navigation: Transformer-Based Catheter Tip Tracking in Fluoroscopy
A two-class SegFormer model tracks catheter tips in fluoroscopy at 4.44 mm mean error, supporting real-time robotic navigation for stroke treatment.
arxiv:2605.14253 v1 · 2026-05-14 · cs.CV · cs.LG
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Claims
On manually-labeled moderate complexity fluoroscopic video data, the two-class SegFormer achieved a mean absolute error of 4.44 mm, outperforming U-Net (4.60 mm), U-Net+Transformer (6.20 mm) and all three-class models (5.19-7.74 mm).
The manually-labeled moderate complexity fluoroscopic video data and the described post-processing steps (two-step component filtering, one-pixel medial skeletonization, greedy arc-length path following with contour fall-back) will generalize to the full range of clinical imaging conditions including heavy occlusion and varying device types.
SegFormer two-class segmentation tracks catheter tips in fluoroscopy with 4.44 mm mean absolute error on moderate-complexity data, outperforming U-Net variants and prior CathAction benchmarks by up to 5% Dice.
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| First computed | 2026-05-17T23:39:10.548853Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Canonical record JSON
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