Watershed transformation of time series of medical thermal images

In this paper, we demonstrate how the watershed transform can be applied to series of thermal medical images to compute important features for physiological interpretation. Automatic physiological analysis of neural features can thereby be shown which was not possible otherwise. The transform as described in the literature has some minor algorithmic errors and inconsistencies which usually cause little trouble. These problems occur on flat plateaus where no unique watershed can be detected. After a short formal description of the transform we describe and eliminate these deficiencies and introduce a modified segmentation method which handles these plateaus as expected intuitively. In our particular medical applications, visible differences of the new segmentation with respect to the old one can be noticed. We contrast our results to those obtained by the detection of isothermic regions. Features of the segmented regions are evaluated as a function of time and used for medical and physiological interpretation. An outlook describes current research in sensor fusion of visual and thermal images for medical research.