Table 1.
Textural features considered in this study.
Fig 1.
Resized and discretized images for the same slice using 432x432 and 256x256 as matrix sizes and 64, 32 and 16 as dynamic ranges.
Running title of each image identifies the matrix size and dynamic range considered.
Table 2.
Mean (and standard deviation) of the CV computed for the 20 patients.
Results are shown for each combination of spatial resolution and slice thickness considered. CV was computed for each feature considering different dynamic range values, i.e. 16, 32 and 64 grey levels.
Fig 2.
Values of several textural features (normalized to the maximum value obtained in each subplot) for different spatial resolutions (432x432 ST 1mm, 432x432 ST 2 mm, 256x256 ST 1 mm, 256x256 ST 2 mm) and dynamic range values (16, 32 and 64 grey levels).
Shown are results for a) co-occurence (CM) Entropy, b) CM Homogeneity, c) run-length matrix (RLM) SRE, d) RLM LRE.
Table 3.
Mean (and standard deviation) of the CV of the 20 patients’ regarding each dynamic range considered.
CV was computed for each feature considering different combinations of matrix size and slice thickness, that is, matrix sizes of 432x432 and 256x256 pixels and slice thickness of 1 mm and 2 mm. Shaded cells correspond to those combinations obtaining a CV below 10%.
Fig 3.
Values of several textural features (normalized to the maximum value obtained in each subplot) for different dynamic range values (16, 32 and 64 grey levels) and spatial resolutions (432x432 ST 1mm, 432x432 ST 2 mm, 256x256 ST 1 mm, 256x256 ST 2 mm).
Shown are results for a) CM Entropy, b) CM Homogeneity, c) RLM SRE, d) RLM LRE.