Abstract: Aiming at the problem that the classic puncture path planning algorithm does not consider the area around the path when quantifying the path， new constraints condition are proposed to make up for the lack of quantification of the information around the path. A strict constraint condition was proposed based on the blood vessel position information (the surrounding area avoids the blood vessel)， and based on bone density， blood vessel density， and diameter information， three soft constraints (bone density， blood vessel density， and blood vessel risk) were proposed， and the surrounding information was added to the quantification of the path to improve the safety of the puncture path. In order to adapt to the specificity of patients， a soft constraint optimization degree scoring algorithm is proposed， and the weight is set according to the optimization degree of soft constraints， and the puncture path corresponding to the maximum optimization degree is taken as the optimal puncture path. In order to verify the effectiveness of the algorithm， experiments were carried out on the public dataset 3D-IRCADb. The experimental results show that the algorithm proposed in this paper can quickly calculate the optimal puncture path that meets the clinical needs.

Key words: liver cancer ablation; puncture constraints; puncture path planning; multi-objective optimization； surgical navigation