ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2026
Real-Time SLAM-Based Correction and 3D Visualization for Fluorescence Lifetime Imaging.
Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Fluorescence lifetime (FLT) imaging has been shown to distinguish tumors from normal tissue with high accuracy. However, the practical utility of FLT imaging is hindered by slow acquisition speeds and depth-dependent inaccuracies. To address these challenges, we introduce FLT-SLAM, a novel algorithm that combines rapid FLT imaging with simultaneous localization and mapping (SLAM) for real-time 3D surface reconstruction and depth-corrected FLT estimation. Using a stereo laparoscope, our approach extracts real-time depth information to improve accuracy, while achieving acquisition speeds exceeding 5 Hz. FLT maps are overlaid onto large-scale 3D surface models generated by SLAM, improving visualization and spatial awareness. We validate FLT-SLAM through phantom and ex-vivo tissue measurements, and show that it reduces FLT estimation errors by nearly 20%, thereby demonstrating its potential to enhance real-time, depth-corrected FLT imaging for surgical applications.
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