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Table 3 The 11 top performing features obtained from the feature selection scheme from the learning set D 2 that included 3T T2w, ADC MRI sequences

From: Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI

# mpMRI sequence feature
1 T2w Signal intensity
2 T2w Standard deviation of signal intensity
3 T2w Sobel gradient (x)
4 T2w Haralick correlation
5 T2w Laws energy (kernel = R5E5)
6 ADC Signal intensity
7 ADC Haralick energy
8 ADC Haralick correlation
9 ADC Haralick differential entropy
10 ADC Laws energy (kernel = L5W5)
11 ADC Laws energy (kernel = W5L5)