Towards a Structured Analysis of Quantitative Descriptors from Segmented Biological Image Data

Abstract

Topological and morphological descriptions of (sub-)cellular structures play a central role in the understanding of biological processes. Deriving such descriptions from image data, however, is a challenging task that has so far only been addressed for individual objects at a coarse resolution with small numbers of samples. For larger samples, the structured analysis is highly challenging as little a priori knowledge exists. In this paper, we address the design of a generic parameter space for segmented objects that forms the basis for subsequent structural analysis. We detail theoretical considerations, discuss the proposed model using examples from electron microscopy, and summarize lessons learned for subsequent implementation and analysis.