Literature DB >> 22681460

Effect of registration mode on neuronavigation precision: an exploration of the role of random error.

Asem Salma1, Orphée Makiese, Steffen Sammet, Mario Ammirati.   

Abstract

The aim of this paper is to analyze the variations in registration accuracy for computer-assisted surgical navigation using three different modes of registration, in order to explore the behavior of random error, and to highlight the precision of neuronavigation as a concept distinct from accuracy. The operational accuracy of three different registration modes (bone fiducials, scalp adhesive fiducials and an auto-registration mask) was evaluated in a total of 20 fresh cadaveric heads. The precision of the neuronavigation system was then assessed by evaluating the variation in the accuracy measurements associated with each registration mode. The coefficient of variation was employed to quantify the degree of variation in the attained accuracy using the following formula: Coefficient of variation = standard deviation/mean * 100. For external targets, the precision of the neuronavigation system was greatest with mask registration (43.75 and 51.41 for anterior and posterior external targets, respectively) and lowest with bone registration (65.30 and 67.17 for anterior and posterior external targets, respectively). For internal targets, the precision of the neuronavigation system was greatest with bone registration (47.69 and 42.6 for anterior and posterior internal targets, respectively) and lowest with mask registration (62.9 and 58.67 for anterior and posterior internal targets, respectively). The precision (reproducibility) of the neuronavigation system is another important quantity besides accuracy that characterizes the performance of the system. Understanding both of these quantities for a given registration mode enhances the use of a neuronavigation system in neurosurgery.

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Year:  2012        PMID: 22681460     DOI: 10.3109/10929088.2012.691992

Source DB:  PubMed          Journal:  Comput Aided Surg        ISSN: 1092-9088


  2 in total

1.  Autonomous neuro-registration for robot-based neurosurgery.

Authors:  Abhishek Kaushik; T A Dwarakanath; Gaurav Bhutani
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-07-20       Impact factor: 2.924

2.  Quantitative comparison of cranial approaches in the anatomy laboratory: A neuronavigation based research method.

Authors:  Francesco Doglietto; Jimmy Qiu; Mayoorendra Ravichandiran; Ivan Radovanovic; Francesco Belotti; Anne Agur; Gelareh Zadeh; Marco Maria Fontanella; Walter Kucharczyk; Fred Gentili
Journal:  World J Methodol       Date:  2017-12-26
  2 in total

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