The distribution of target registration error in rigid-body point-based registration

By J. Michael Fitzpatrick, Jay B. West. IEEE Transactions on Medical Imaging, 2001

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A review of 3D/2D registration methods for image-guided interventions (2012, methodology): “Furthermore, error analysis and error prediction for these methods has been thoroughly studied (Fitzpatrick et al., 1998; Fitzpatrick and West, 2001).”
Brain Functional Localization: A Survey of Image Registration Techniques (2007, background): “evaluation and validation of many multimodality brain image registration studies, for example [91]–[93], [103], [117]–[119], [125], [130], [136], [137], [139], [145], [146], and [149].”
Deformable Medical Image Registration: A Survey (2013, background): “Some resent studies regarding the errors in the process are given in [284]–[286].”
Non-rigid image registration: theory and practice. (2004, background): “For rigid-registration this form of error analysis has been studied intensively and it has been found that an average target registration error for the whole volume can be estimated from knowledge of the landmark positions [83].”
Image Registration Techniques: A Survey (2017, methodology): “rse features while remaining unaffected by noise. 3. Transform model assessment: For alignment of the sensed image with the reference image the parameters of the mapping functions are to be estimated [37, 38, 39, 40, 41, 42, 43]. These parameters are computed with the established feature corresponde”