Yang Cong, Huang Qianwen, Ji Xiang, Bai Jingfeng
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:5236-5239. doi: 10.1109/EMBC44109.2020.9175248.
High-intensity focused ultrasound (HIFU) has been widely used for treatment of uterine fibroids. However, due to the limited resolution of ultrasound image in deep organs, the guidance of ultrasound-guided HIFU (USgHIFU) treatment greatly depends on clinicians' experience in US image. To address this issue, fusion of intraoperative US images and pretreatment MR images has been proposed. Contour segmentation and multiple-angles 2D US images combination are performed to obtain 3D points along the contour of uterus. Iterative closest point (ICP) algorithm based on prior knowledge is used to register these point sets. MR and US images of six treated patients are used for evaluation. The mean distance error (MDE) of our algorithm is 1.71±0.59 mm, and the average running time is 0.18 s. The results have verified the feasibility of fusion of MR images and US images for USgHIFU guidance. In addition, this method may be also potential for post-ablation evaluation with follow-up MR images.
高强度聚焦超声（HIFU）已被广泛用于子宫肌瘤的治疗。然而，由于深部器官超声图像分辨率有限，超声引导下的HIFU（USgHIFU）治疗的引导很大程度上依赖于临床医生对超声图像的经验。为了解决这个问题，有人提出将术中超声图像与术前磁共振图像融合。通过进行轮廓分割和多角度二维超声图像组合来获取沿子宫轮廓的三维点。基于先验知识的迭代最近点（ICP）算法用于配准这些点集。使用六名接受治疗患者的磁共振和超声图像进行评估。我们算法的平均距离误差（MDE）为1.71±0.59毫米，平均运行时间为0.18秒。结果验证了磁共振图像和超声图像融合用于USgHIFU引导的可行性。此外，该方法在利用后续磁共振图像进行消融后评估方面也可能具有潜力。
