Cha Dong Ik, Lee Min Woo, Kim Ah Yeong, Kang Tae Wook, Oh Young-Taek, Jeong Ja-Yeon, Chang Jung-Woo, Ryu Jiwon, Lee Kyong Joon, Kim Jaeil, Bang Won-Chul, Shin Dong Kuk, Choi Sung Jin, Koh Dalkwon, Seo Bong Koo, Kim Kyunga
1 Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
2 Medical Imaging R&D Group, Health & Medical Equipment Business, Samsung Electronics Co., Ltd., Seoul, Republic of Korea.
Acta Radiol. 2017 Nov;58(11):1349-1357. doi: 10.1177/0284185117693459. Epub 2017 Feb 20.
Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3-16 s] vs. 32 s [range, 21-38 s]; P < 0.001] and complete (median, 34.0 s [range, 26-66 s] vs. 47.5 s [range, 32-90]; P = 0.001] image fusion. Registration error of Positioning auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0-84.6 mm] vs. 18.2 mm [6.7-73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7-9.9 mm] vs. 5.8 mm [range, 2.0-13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2-3] vs. 1 [range, 1-2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.
传统手动图像融合的一个主要缺点是该过程可能很复杂，尤其是对于经验较少的操作人员。最近，已经开发出两种自动图像融合技术，即定位自动配准和扫描自动配准。
比较定位自动配准和扫描自动配准在实时超声（US）与计算机断层扫描（CT）图像融合中的准确性和所需时间。
纳入连续18例因计划对肝脏局灶性病变进行射频消融或活检而行超声检查的患者。对每位患者使用两种自动配准方法进行图像融合。使用Wilcoxon符号秩检验比较配准误差、图像融合所需时间以及使用的点锁定数量。
所有患者的图像融合均成功。定位自动配准在初始（中位数，11秒[范围，3 - 16秒]对32秒[范围，21 - 38秒]；P < 0.001）和完整（中位数，34.0秒[范围，26 - 66秒]对47.5秒[范围，32 - 90秒]；P = 0.001）图像融合方面均显著快于扫描自动配准。定位自动配准在初始图像融合时的配准误差显著更高（中位数，38.8毫米[范围，16.0 - 84.6毫米]对18.2毫米[6.7 - 73.4毫米]；P = 0.029），但在完整图像融合时并非如此（中位数，4.75毫米[范围，1.7 - 9.9毫米]对5.8毫米[范围，2.0 - 13.0毫米]；P = 0.338）。使用定位自动配准细化初始融合图像所需的点锁定数量显著更多（中位数，2[范围，2 - 3]对1[范围，1 - 2]；P = 0.012）。
与扫描自动配准相比，定位自动配准在实时超声与术前CT图像之间提供了更快的图像融合。两种方法最终的配准误差相似。
