Image Structure Representation and Processing: A Discussion of Some Segmentation Methods in Cytology

TLDR

Image segmentation methods are examined in the context of modeling image structure, where images are represented by primitives defined by type, abstraction level, and attributes, and entities such as regions are described as subsets of these primitives following specific rules. The study compares the potential efficacy of these segmentation methods when applied to cytologic image analysis.

Abstract

Image processing methods (segmentation) are presented in connection with a modeling of image structure. An image is represented as a set of primitives, characterized by their type, abstraction level, and a list of attributes. Entities (regions for example) are then described as a subset of primitives obeying particular rules. Image segmentation methods are discussed, according to the associated image modeling level. Their potential efficacity is compared, when applied to cytologic image analysis.