1Assistant Professor,2,3,4 Final Year
Department of Computer Science and Engineering,
SreeSowdambika College of Engineering,
Aruppukottai,
Virudunagar,
kirubhavasan@gmail.com, ambikarenukakrishnan@gmail.com, jesima.cs@gmail.com, nagu.chandrasekar@gmail.com
Abstract
This paper presents a new approach for unsupervised segmentation of histopathological tissue images. This approach has two main contributions. First, it introduces a new set of high-level texture features to represent the prior knowledge of spatial organization of the tissue components. Second, it proposes to obtain multiple segmentations by multilevel partitioning of a graph constructed on the tissue objects and combine them by an ensemble function. This multilevel graph partitioning algorithm introduces randomization in graph construction and refinements in its multilevel scheme to increase diversity of individual segmentations, and thus, improve the final result.