"Second order statistics via a grey-level co-occurrence matrix will explore similar parameters, however, will present how often pairs of pre-determined pixel values arise within a spatial range in the image."
"Explores the frequency distribution in the region of interest via a histogram, it does not consider pixels around the region of interest, the first order statistics measures parameters such as intensity, standard deviation, skewness, and kurtosis 2,4."
Expected headings
"Statistical based modelling"
"First-order statistics"
"Second-order statistics"
"Higher-order statistics"
"Traditionally, the interpretation of tumour bodies in medical imaging whether that be CT, MRI or x-ray will report on the size and parameter metrics 3. It is now well known that intratumor heterogeneity is a marker of malignancy; texture analysis attempts to provide a comprehensive quantitative analysis of heterogeneity via the assessment of pixels and voxels within a tumour image 2,3."
"Traditionally, the interpretation of tumour bodies in medical imaging whether that be CT, MRI or x-ray will report on the size and parameter metrics 3. It is now well known that intratumor heterogeneity is a marker of malignancy; texture analysis attempts to provide a comprehensive quantitative analysis of heterogeneity via the assessment of pixels and voxels within a tumour image 2,3."
"Texture analysis employs a plethora of models to achieve an accurate assessment of tumour heterogeneity, including model-based, transform-based, and statistical-based 2,4. The utilisation of statistical based modelling is the most common in texture analysis, involving three orders of measure parameters; first-order statistics, second-order statistics and higher-order statistics."
"Explores the frequency distribution in the region of interest via a histogram, it does not consider pixels around the region of interest, the first order statistics measures parameters such as intensity, standard deviation, skewness, and kurtosis 2,4."