  Nowadays, registration methods are typically evaluated based on
sub-resolution tracking error differences. In an effort to reinfuse this
evaluation process with clinical relevance, we propose to reframe image
registration as a landmark detection problem. Ideally, landmark-specific
detection thresholds are derived from an inter-rater analysis. To approximate
this costly process, we propose to compute hit rate curves based on the
distribution of errors of a sub-sample inter-rater analysis. Therefore, we
suggest deriving thresholds from the error distribution using the formula:
median + delta * median absolute deviation. The method promises differentiation
of previously indistinguishable registration algorithms and further enables
assessing the clinical significance in algorithm development.

Image and Video Processing;Computer Vision and Pattern Recognition;Medical Physics