A learning-free approach to whole spine vertebra localization in MRI

Abstract

In recent years,analysis of magnetic resonance images of the spine gained considerable interest with vertebra localization being a key step for higher level analysis. Approaches based on trained appearance - which are de facto standard - may be inappropriate for certain tasks,because processing usually takes several minutes or training data is unavailable. Learning-free approaches have yet to show there competitiveness for whole-spine localization. Our work fills this gap. We combine a fast engineered detector with a novel vertebrae appearance similarity concept. The latter can compete with trained appearance,which we show on a data set of 64 T1- and 64 T2-weighted images. Our detection took 27.7 ± 3.78 s with a detection rate of 96.0% and a distance to ground truth of 3.45 ± 2.2 mm,which is well below the slice thickness.