Literature DB >> 34054190

Effect of Uncertainty on Target Registration Error in Image-guided Renal Interventions: From Simulation to in-vitro Assessment.

Peter Jackson1, Richard Simon2, Cristian Linte1,2.   

Abstract

It is imperative that image-guided intervention (IGI) systems provide accurate and precise navigation information to enable the user to trust the system and not place unwarranted confidence in the guidance capabilities of the system. Unfortunately, the actual error associated with the overall targeting capabilities of an IGI system is not readily known. Here we are primarily interested in the application of image-guided surgery in the context of renal interventions. We built a simulation pipeline to study the uncertainty propagation through an optically tracked IGI system to gain insight into the overall accuracy of the system. Our simulation pipeline models several stages, including stylus calibration, tool tracking, patient tracking, and image to patient registration. In the effort to realistically estimate tracking noise and user-associated fiducial localization error (FLE), we conducted several experiments using the optical tracking system. Our simulation suggested that a wider cone angle results in a more accurate tool calibration, which improves further with the collection of additional samples. Furthermore, our simulations also suggested that the image-to-patient registration was the most significant contributor to navigation uncertainty, followed by the fiducial localization error. Lastly, we also observed a 0.72 correlation between the Target Registration Error (TRE) estimated at target fiducials and the distance between the the centroids of the registration and target fiducial landmarks. To validate the simulation predictions, we also conducted several in vitro experiments using a 3D printed patient specific kidney phantom and compared the simulation-based registration predictions with those observed experimentally in vitro. The experiments confirmed the registration metrics (Fiducial Registration Error and TRE) predicted by the simulations, given several specific combinations of fiducial landmarks used to perform the image to patient registration.

Entities:  

Keywords:  Error Analysis; Image-guided Navigation; Registration; Simulation

Year:  2021        PMID: 34054190      PMCID: PMC8163595          DOI: 10.1117/12.2581854

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  6 in total

1.  3D Slicer as an image computing platform for the Quantitative Imaging Network.

Authors:  Andriy Fedorov; Reinhard Beichel; Jayashree Kalpathy-Cramer; Julien Finet; Jean-Christophe Fillion-Robin; Sonia Pujol; Christian Bauer; Dominique Jennings; Fiona Fennessy; Milan Sonka; John Buatti; Stephen Aylward; James V Miller; Steve Pieper; Ron Kikinis
Journal:  Magn Reson Imaging       Date:  2012-07-06       Impact factor: 2.546

2.  A statistical model for point-based target registration error with anisotropic fiducial localizer error.

Authors:  Andrew D Wiles; Alexander Likholyot; Donald D Frantz; Terry M Peters
Journal:  IEEE Trans Med Imaging       Date:  2008-03       Impact factor: 10.048

3.  Computation and visualization of uncertainty in surgical navigation.

Authors:  Amber L Simpson; Burton Ma; Edward M Vasarhelyi; Dan P Borschneck; Randy E Ellis; A James Stewart
Journal:  Int J Med Robot       Date:  2013-10-03       Impact factor: 2.547

4.  Predicting error in rigid-body point-based registration.

Authors:  J M Fitzpatrick; J B West; C R Maurer
Journal:  IEEE Trans Med Imaging       Date:  1998-10       Impact factor: 10.048

Review 5.  Open-source platforms for navigated image-guided interventions.

Authors:  Tamas Ungi; Andras Lasso; Gabor Fichtinger
Journal:  Med Image Anal       Date:  2016-06-15       Impact factor: 8.545

6.  The role of registration in accurate surgical guidance.

Authors:  J M Fitzpatrick
Journal:  Proc Inst Mech Eng H       Date:  2010       Impact factor: 1.617

  6 in total
  1 in total

1.  Integrating Real-time Video View with Pre-operative Models for Image-guided Renal Navigation: An in vitro Evaluation Study.

Authors:  Peter Jackson; Richard Simon; Cristian Linte
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2021-11
  1 in total

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