MRI Texture Analysis in Multiple Sclerosis

Table 1

Overview of common texture analysis approaches in MS.

	Assessment	Utility
Statistical approach
First-order	Global assessment of pixel distribution	Self-explanatory yet lack of detail
Second-order
Gray-level cooccurrence matrix (GLCM)	Joint probability of two pixels having; cooccurring gray level values at a given; distance and direction	Multiple properties of a texture; (coarseness, correlation, contrast), less; sensitive to larger scales
Run length matrix (RLM)	The number of times two or more pixels; having the same value in a preset direction	Several properties of a texture; (coarseness), less sensitive to larger scales
Spectral approach
Fourier transform	Entire frequency profile, using sinusoid; basis functions	Useful for signals without temporal; changes
Wavelet transform	Scale-based frequency content, using a; deformable localizing “mother” wavelet as; basis function	Multiscale analysis; less intuitive and can; be computation-expensive
Stockwell transform	Scale-based frequency content, using fast; Fourier transform and a flexible Gaussian; localizing window	Fourier-based multiscale frequency content; computation time varies by; image size and algorithm