Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases

Table 7 Description of 58 texture and 6 metabolic features in Dataset S ₃, extracted from 1.5 Tesla T2w MRI and MRS for identifying prostate cancer (CaP) on a per-voxel basis

Texture features	#	Description
Kirsh Filters	4	X-direction, Y-direction, XY-diagonal, YX-diagonal
Sobel Filters	4	X-direction, Y-direction, XY-diagonal, YX-diagonal
Directional Filters	5	x-Gradient, y-Gradient, Magnitude of Gradient, 2 Diagonal Gradients
First order Gray Level	8	Mean, Median, Standard deviation, Range for window size = 3×3,5×5
Haralick features	13	Contrast Energy, Contrast Inverse Moment, Contrast Average, Contrast Variance, Contrast Entropy, Intensity Average for window size = 3×3, Intensity Variance, Intensity Entropy, Entropy, Energy, Correlation, info. Measure of Correlation 1, Info. Measure of Correlation 2
Gabor filters	24	Filterbank constructed for different combinations of scale and orientation
Metabolic features		Description
Metabolites Identified	6	Area under peaks for choline (A _ch), creatine (A _cr), citrate (A _cit), and ratios (A _ch/A _cr,A _ch/A _cit,A _ch+cr/A _cit)