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Article type: Research Article
Authors: Dong, Qi | Cao, Miao* | Gu, Feng | Gong, Weifang | Cai, Qingwu
Affiliations: College of Life Science and Technology, Changchun University of Science and Technology, Changchun, Jilin, China
Correspondence: [*] Corresponding author: Miao Cao, College of Life Science and Technology, Changchun University of Science and Technology, Changchun, Jilin, China. %****␣thc-30-thc213592_temp.tex␣Line␣50␣**** E-mail: [email protected].
Abstract: BACKGROUND: Thermal ablation of liver tumors is a conventional mode for treating liver tumors. In order to reduce the damage to normal tissue endangered by thermal ablation, the physician needs to plan the puncture path before surgery. OBJECTIVE: In this paper, a puncture trajectory planning method for thermal ablation of liver tumor based on NSGA-III is proposed. This method takes the clinical hard constraints and soft constraints into account. METHOD: The feasible puncture region is solved by the hard constraints, and after that the pareto front points are obtained under the soft constraints. When accessing the feasible puncture region, an adaptive morphological closing operation method based on K-means algorithm is adopted to process the spherical angle binary image of obstacles that might be encountered in the puncture process. RANSAC is performed to fit the tangent plane of liver surface when calculating the angle between the puncture trajectory and liver surface. In order to evaluate the puncture path obtained by this method, 6 tumors are selected as experimental subjects, and Hausdorff distance and Overlap Rate of Pareto front points with manually recommend points are calculated respectively. RESULTS: The average value of Hausdorff distance is 24.91 mm, and the mean value of the overlap rate is 86.43%. CONCLUSION: The proposed method can provide high safety and clinical practice of the puncture route.
Keywords: Liver tumor puncture ablation planning, multi-objective optimization, K-means, Random Sampling Consistent algorithm, NSGA-III
DOI: 10.3233/THC-213592
Journal: Technology and Health Care, vol. 30, no. 5, pp. 1243-1256, 2022
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