<title>Computation of morphological texture features for medical imaging applications</title>

Abstract

Texture is an important attribute which is widely used in various image analysis applications. Among texture features, morphological texture features are least utilized in medical image analysis. From a computational standpoint, extracting morphological texture features from an image is a challenging task. The computational problem is made even greater in medical imaging applications where large images such as mammograms are to be analyzed. This paper discusses an efficient method to compute morphological texture features for any geometry of a structuring element corresponding to a texture type. A benchmarking of the code on three machines (Sun SPARC 20, Pentium II based Dell 400 workstation, and SGI Power Challenge 10000XL) as well as a parallel processing implementation was performed to obtain an optimum processing configuration. A sample processed mammogram is shown to illustrate the code outcome.