Penney G P, Blackall J M, Hamady M S, Sabharwal T, Adam A, Hawkes D J
Division of Imaging Sciences, 5th Floor Thomas Guy House, Guy's Hospital, London SE1 9RT, UK.
Med Image Anal. 2004 Mar;8(1):81-91. doi: 10.1016/j.media.2003.07.003.
We present a method to register a preoperative MR volume to a sparse set of intraoperative ultrasound slices. Our aim is to allow the transfer of information from preoperative modalities to intraoperative ultrasound images to aid needle placement during thermal ablation of liver metastases. The spatial relationship between ultrasound slices is obtained by tracking the probe using a Polaris optical tracking system. Images are acquired at maximum exhalation and we assume the validity of the rigid body transformation. An initial registration is carried out by picking a single corresponding point in both modalities. Our strategy is to interpret both sets of images in an automated pre-processing step to produce evidence or probabilities of corresponding structure as a pixel or voxel map. The registration algorithm converts the intensity values of the MR and ultrasound images into vessel probability values. The registration is then carried out between the vessel probability images. Results are compared to a "bronze standard" registration which is calculated using a manual point/line picking algorithm and verified using visual inspection. Results show that our starting estimate is within a root mean square target registration error (calculated over the whole liver) of 15.4 mm to the "bronze standard" and this is improved to 3.6 mm after running the intensity-based algorithm.
我们提出了一种将术前磁共振(MR)容积数据与稀疏的术中超声切片进行配准的方法。我们的目的是实现从术前模态到术中超声图像的信息传递,以辅助肝转移瘤热消融过程中的针穿刺定位。超声切片之间的空间关系通过使用北极星光学跟踪系统跟踪探头来获取。图像在最大呼气时采集,并且我们假定刚体变换的有效性。通过在两种模态中选取单个对应点来进行初始配准。我们的策略是在自动预处理步骤中对两组图像进行解读,以生成作为像素或体素图的对应结构的证据或概率。配准算法将MR图像和超声图像的强度值转换为血管概率值。然后在血管概率图像之间进行配准。将结果与使用手动点/线选取算法计算并通过目视检查验证的“青铜标准”配准进行比较。结果表明,我们的初始估计与“青铜标准”相比,在整个肝脏上计算的均方根目标配准误差为15.4毫米以内,在运行基于强度的算法后,该误差改善到3.6毫米。