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Paper
26 March 2008 A co-occurrence texture semi-invariance to direction, distance, and patient size
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Abstract
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ruchaneewan Susomboon, Daniela Raicu, Jacob Furst, and Timothy Ben Johnson M.D. "A co-occurrence texture semi-invariance to direction, distance, and patient size", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69141Y (26 March 2008); https://doi.org/10.1117/12.771068
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CITATIONS
Cited by 15 scholarly publications.
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KEYWORDS
Liver

Tissues

Statistical analysis

Computed tomography

Matrices

Tumor growth modeling

Statistical modeling

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