北京理工大学 增强现实智能医疗实验室

Abstract—Microwave ablation is an effective minimally invasive surgery for the treatment of liver cancer. The safety margin assessment is implemented by mapping the coagulation in the postoperative image to the tumor in the preoperative image. However, an accurate assessment is a challenging task because the tissue shrinks caused by dehydration during microwave ablation. This paper proposes a fast automatic assessment method to compensate for the underestimation of the coagulation caused by the tissue shrinks and precisely quantify the tumor coverage. The proposed method is implemented on GPU including two main steps: (1) a local contractive nonrigid registration for registering the liver parenchyma around the coagulation, and (2) the fast Fourier transform-based Helmholtz-Hodge decomposition for quantifying the location of the shrinkage center and the volume of the original coagulation. The method was quantificationally evaluated on 50 groups of synthetic datasets and 9 groups of clinical MR datasets. Compared with five state-of-the-art methods, the lowest distance to the true deformation field (1.56 ± 0.74 mm) and the highest precision of safety margin (88.89%88.89%) are obtained. The mean computation time is 111±13111±13 s. Results show that the proposed method efficiently improves the accuracy of the safety margin assessment and is thus a promising assessment tool for the microwave ablation.