A co-occurrence texture semi-invariance to direction, distance, and patient size
Ruchaneewan Susomboon, Daniela Stan Raicu, Jacob David Furst, Timothy Ben Johnson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
Texture-based models are intensively used in medical image processing to quantify the homogeneity and consistency of soft tissues across different patients. Several research studies have shown that the co-occurrence texture model and its Haralick descriptors can be successfully applied to capture the statistical properties of the soft tissues' patterns. Given that the calculation of the co-occurrence texture model is a computationally-intensive task, in this paper we investigate the usefulness of using all possible angles and all displacements for capturing the texture properties of an organ of interest, specifically, the liver. Based on the Analysis of Variance (ANOVA) technique and multiple pair-wise comparisons, we found that using only the "near" and "far" displacements is enough to capture the spatial properties of the texture for the liver.