Comparisons of two microscopy images can be accomplished in many different ways. This paper presents a system that recommends appropriate similarity metrics for microscopy image comparisons based on biological application requirements. The motivation stems from the fact that task requirements can drive the automatic selection of a similarity metric. The suitability of a particular image similarity metric is modeled as the sensitivity and invariance of the metric to microscopy image content and the associated dynamic changes of this content.. In this paper, we describe a mathematical and experimental basis of an image similarity metric recommendation system. In this system, we build a database of sensitivity signatures, and query this reference database to retrieve a similarity metric based on given biological requirements. We illustrate a prototype recommendation system based on synthetic and measured images for spectral calibration and spatial registration applications.
P. Bajcsy, J. Chalfoun, and M. Brady,
Proc. BCB, pp.613-615, 2012.
Proceeding BCB ‘12 Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine