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Robotic ultrasound can now achieve precise non-normal probe angles, improving diagnostic imaging quality with a tracking error of only 1.06 degrees.
LLMs can learn sequential user preferences without any training by externalizing Bayesian inference, outperforming even fine-tuned models.
Achieve 75mm shorter probe footprints in robotic kidney ultrasound by using a template-guided pivoting strategy that minimizes unnecessary probe translation.
