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ThERMO Thermal Imaging Algorithm Improves Precision of Autonomous Tumor Resection
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Naveed D. Riaziat et al. proposed the ThERMO thermal imaging speed optimization algorithm and completed autonomous electrosurgical resection tests on ex vivo porcine tissue using the UR10e robot-based ASTR system. Compared with two fixed cutting speed methods, ThERMO adjusts cutting speed via real-time thermal imaging, reducing thermal damage by up to 52% and improving margin accuracy by up to 59%, without requiring data-driven training or iterative parameter tuning. Histological analysis detected the extent of thermal damage at the cellular level, and 3D photogrammetry verified margin accuracy. The work has been submitted to IEEE Access.
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- ThERMO Thermal Imaging Speed Optimization Algorithm Improves UR10e Robot Autonomous Tumor Resection Accuracy
The ThERMO closed-loop thermal feedback algorithm completed autonomous electrosurgical tests on ex vivo porcine tissue using the UR10e-based ASTR system, reducing thermal injury by up to 52% and improving margin accuracy by up to 59%, without requiring data-driven training or iterative tuning. The algorithm adjusts cutting speed via real-time thermal imaging; histological analysis and 3D photogrammetry verified thermal injury extent and margin accuracy, outperforming two fixed-speed control methods.
arXiv cs.RO ·