Table 2.
The quantitative MRI texture features used to build classification and regression models
| Treatment Effects | Overall Survival | Trichrome | CK19 marker | Ki67 marker | ||
|---|---|---|---|---|---|---|
| Features | 1 | FoS mean (h) | FoS mean | FA fractal dimension | RM LRE | RM LGLE |
| 2 | FoS mean (a) | RM SRE | LBP | FoS kurtosis (h) | RM LGLE of GD | |
| 3 | RM nonuniformity (v) | FoS 3rd moment (d) | RM SRE (a) | FoS contrast (a) | FA fractal dimension | |
| 4 | FoS contrast (a) | RM LGLRE | RM SRE (a) | FoS entropy (h) | ||
| 5 | RM LGLRE (v) | FoS kurtosis of HoG | RM RLE (a) | RM SRE (d) |
Abbreviations: CM: co-occurrence matrix; FA: fractal anisotropy; FoS: first-order statistics; GD: gradient image; HoG: histogram of oriented gradients; LBP: local binary patterns; LRE: long-run emphasis; LGLE: low gray-level emphasis; LGLRE: low gray level run emphasis; RLE: run-length emphasis; RM: run-length matrix; SRE: short-run emphasis. (a): approximate wavelet coefficients; (v): vertical wavelet coefficients; (h): horizontal wavelet coefficients; (d): diagonal wavelet coefficients.