Optimal landmarks selection and fiducial marker placement for minimal target registration error in image-guided neurosurgery

Author(s):  
Reuben R. Shamir ◽  
Leo Joskowicz ◽  
Yigal Shoshan
2020 ◽  
Vol 10 (6) ◽  
pp. 1466-1472
Author(s):  
Hakje Yoo ◽  
Ahnryul Choi ◽  
Hyunggun Kim ◽  
Joung Hwan Mun

Surface registration is an important factor in surgical navigation in determining the success rate and stability of surgery by providing the operator with the exact location of a lesion. The problem of surface registration is that point cloud in the patient space is acquired at irregular intervals due to the operator’s tracking speed and method. The purpose of this study is to analyze the effect of irregular intervals of point cloud caused by tracking speed and method on the registration accuracy. For this study, we created the head phantom to obtain a point cloud in the patient space with a similar object to that of a patient and acquired a point cloud in a total of ten times. In order to analyze the accuracy of registration according to the interval, cubic spline interpolation was applied to the existing point cloud. Additionally, irregular intervals of the point cloud were regenerated into regular intervals. As a result of applying the regenerated point cloud to the surface registration, the surface registration error was not statistically different from the existing point cloud. However, the target registration error significantly lower (p < 0.01). These results indicate that the intervals of point cloud affect the accuracy of registration, and that point cloud with regular intervals can improve the surface registration accuracy.


2010 ◽  
Vol 66 (suppl_1) ◽  
pp. ons-143-ons-151
Author(s):  
Wang Manning ◽  
Song Zhijian

Abstract Background: Point-pair registration is widely used in an image-guided neurosurgery system. Poor distribution of the fiducial points leads to an increase in the target registration error (TRE). Objective: This study aimed to provide templates consisting of optimized positioning of the fiducial points to reduce the TRE in image-guided neurosurgery. Methods: We divided the head into 6 regions and provided distribution templates of the fiducial points for each of them. A variable termed TREM(r) was used to express the approximate expected square of the TRE at the target point with a specified distribution of fiducial points. We randomly selected 85 patients from 5 hospitals who underwent image-guided neurosurgery and compared the TREM(r) of the real fiducial points with that of the templates. Results: We grouped the patients by hospitals and regions. The mean TREM(r)s of the templates were much smaller than those of the real fiducial points. In each group, the range of the TREM(r) values of the templates was much smaller than that of the real fiducial points. Conclusion: This study provides an easy method to implement a good distribution of the fiducial points to help reduce TRE in image-guided neurosurgery. The templates are simple and exact and can be easily integrated into current workflow.


Author(s):  
Marzieh Ershad ◽  
Alireza Ahmadian ◽  
Nassim Dadashi Serej ◽  
Hooshang Saberi ◽  
Keyvan Amini Khoiy

2011 ◽  
Vol 39 (6) ◽  
pp. 407-411 ◽  
Author(s):  
Wenbin Zhang ◽  
Chenhao Wang ◽  
Hongbo Yu ◽  
Yuncai Liu ◽  
Guofang Shen

2004 ◽  
Vol 9 (4) ◽  
pp. 145-153 ◽  
Author(s):  
Robert F. Labadie ◽  
Rohan J. Shah ◽  
Steve S. Harris ◽  
Ebru Cetinkaya ◽  
David S. Haynes ◽  
...  

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