Leader-follower clustering algorithm for automatic segmentation of cardiac PET studies

Quantitative analysis of dynamic cardiac PET studies provides useful diagnostic information regarding different heart diseases. To correctly perform the kinetic analysis, tracer time-activity curves (TAC) must be precisely extracted from the chosen tissue on the imaging data. In this work we present an alternative clustering algorithm for segmentation of dynamic studies using a leader-follower clustering approach, in which the number of clusters is unknown.