Discrete Mereotopology in Histological Imaging
Gabriel Landini, David Randell, and Antony Galton
In Ela Claridge, Andrew D. Palmer and William T. E. Pitkeathly (editors), Medical Image Understanding and Analysis, Proceedings of the 17th Conference on Medical Image Understanding and Analysis, 17th-19th July 2013, Birmingham, UK, pages 101-106.
ISBN: 1-901725-48-0
Available at http://events.cs.bham.ac.uk/miua2013/MIUAproceedings.pdf
Abstract
In this paper we describe methods suited for developing intelligent
histological imaging procedures based on mathematical morphology and a
discrete version of the Region Connection Calculus (RCC) known as
Discrete Mereotopology. The implementation of the discrete versions
of RCC5 and RCC8 relation sets enables computation of the spatial
relationships between image regions and reasoning about those
relations in segmented digitised images. It also opens the
possibility of defining histologically relevant models of biological
structures (cells and tissues) so the relations of their components
can be assessed algorithmically. A Java plugin implementing the RCC5D
and RCC8D relations sets for the popular imaging tool ImageJ was
developed. We illustrate an application for automated cell sorting on
cultured fibroblasts.
Antony Galton
Last modified: Thu Aug 1 09:59:50 BST 2013