textureFeatures

Radiomics texture features

Since R2023b

Syntax

T = textureFeatures(R)

T = textureFeatures(R,Name=Value)

Description

T = textureFeatures(R) computes the radiomics texture features T for the radiomics object R.

T = textureFeatures(R,Name=Value) specifies additional options using one or more optional name-value arguments.

Examples

Compute Texture Features for Multiple ROIs in 2-D X-Ray Image

Load an X-ray image into the workspace as a medicalImage object. Visualize the image.

data = medicalImage("forearmXrayImage1.dcm");
I = data.Pixels;
figure
imshow(I,[])

Draw two regions of interest (ROI) in the X-ray image. Create masks from the ROIs.

roi1 = drawassisted(Color="g");
roi2 = drawassisted(Color="r");

mask1 = createMask(roi1,I);
mask2 = createMask(roi2,I);

Create an ROI label matrix, using different labels for the two ROIs. Create a medicalImage object of the ROI label data.

mask = zeros(size(I));
mask(mask1) = 1;
mask(mask2) = 2;
info = dicominfo("forearmXrayImage1.dcm");
roi = medicalImage(mask,info);

Create a radiomics object from the X-ray image data and ROI label data.

R = radiomics(data,roi)

R = 
  radiomics with properties:

                             Data: [1×1 medicalImage]
                         ROILabel: [1×1 medicalImage]
                         Resample: 0
                        Resegment: 1
                       Discretize: 1
                    DiscretizeIVH: 1
            ResampledVoxelSpacing: []
               DataResampleMethod: []
               MaskResampleMethod: []
              ResegmentationRange: []
                  ExcludeOutliers: 1
       DiscreteBinSizeOrBinNumber: []
                   DiscreteMethod: 'FixedBinNumber'
    DiscreteIVHBinSizeOrBinNumber: []
                DiscreteIVHMethod: 'FixedBinNumber'

Compute texture features for both ROIs.

T = textureFeatures(R)

T=2×137 table
    LabelID    JointMaximumAveraged2D    JointAverageAveraged2D    JointVarianceAveraged2D    JointEntropyAveraged2D    DifferenceAverageAveraged2D    DifferenceVarianceAveraged2D    DifferenceEntropyAveraged2D    SumAverageAveraged2D    SumVarianceAveraged2D    SumEntropyAveraged2D    AngularSecondMomentAveraged2D    ContrastAveraged2D    DissimilarityAveraged2D    InverseDifferenceAveraged2D    NormalisedInverseDifferenceAveraged2D    InverseDifferenceMomentAveraged2D    NormalisedInverseDifferenceMomentAveraged2D    InverseVarianceAveraged2D    CorrelationAveraged2D    AutoCorrelationAveraged2D    ClusterTendencyAveraged2D    ClusterShadeAveraged2D    ClusterProminenceAveraged2D    InformationCorrelation1Averaged2D    InformationCorrelation2Averaged2D    JointMaximumSliceMerged2D    JointAverageSliceMerged2D    JointVarianceSliceMerged2D    JointEntropySliceMerged2D    DifferenceAverageSliceMerged2D    DifferenceVarianceSliceMerged2D    DifferenceEntropySliceMerged2D    SumAverageSliceMerged2D    SumVarianceSliceMerged2D    SumEntropySliceMerged2D    AngularSecondMomentSliceMerged2D    ContrastSliceMerged2D    DissimilaritySliceMerged2D    InverseDifferenceSliceMerged2D    NormalisedInverseDifferenceSliceMerged2D    InverseDifferenceMomentSliceMerged2D    NormalisedInverseDifferenceMomentSliceMerged2D    InverseVarianceSliceMerged2D    CorrelationSliceMerged2D    AutoCorrelationSliceMerged2D    ClusterTendencySliceMerged2D    ClusterShadeSliceMerged2D    ClusterProminenceSliceMerged2D    InformationCorrelation1SliceMerged2D    InformationCorrelation2SliceMerged2D    ShortRunsEmphasisAveraged2D    LongRunsEmphasisAveraged2D    LowGrayLevelRunEmphasisAveraged2D    HighGrayLevelRunEmphasisAveraged2D    ShortRunLowGrayLevelEmphasisAveraged2D    ShortRunHighGrayLevelEmphasisAveraged2D    LongRunLowGrayLevelEmphasisAveraged2D    LongRunHighGrayLevelEmphasisAveraged2D    GrayLevelNonUniformityAveraged2D    NormalisedGrayLevelNonUniformityAveraged2D    RunLengthNonUniformityAveraged2D    NormalisedRunLengthNonUniformityAveraged2D    RunPercentageAveraged2D    GrayLevelVarianceAveraged2D    RunLengthVarianceAveraged2D    RunEntropyAveraged2D    ShortRunsEmphasisSliceMerged2D    LongRunsEmphasisSliceMerged2D    LowGrayLevelRunEmphasisSliceMerged2D    HighGrayLevelRunEmphasisSliceMerged2D    ShortRunLowGrayLevelEmphasisSliceMerged2D    ShortRunHighGrayLevelEmphasisSliceMerged2D    LongRunLowGrayLevelEmphasisSliceMerged2D    LongRunHighGrayLevelEmphasisSliceMerged2D    GrayLevelNonUniformitySliceMerged2D    NormalisedGrayLevelNonUniformitySliceMerged2D    RunLengthNonUniformitySliceMerged2D    NormalisedRunLengthNonUniformitySliceMerged2D    RunPercentageSliceMerged2D    GrayLevelVarianceSliceMerged2D    RunLengthVarianceSliceMerged2D    RunEntropySliceMerged2D    SmallZoneEmphasis2D    LargeZoneEmphasis2D    LowGrayLevelZoneEmphasis2D    HighGrayLevelZoneEmphasis2D    SmallZoneLowGrayLevelEmphasis2D    SmallZoneHighGrayLevelEmphasis2D    LargeZoneLowGrayLevelEmphasis2D    LargeZoneHighGrayLevelEmphasis2D    GrayLevelNonUniformity2D    NormalisedGrayLevelNonUniformity2D    ZoneSizeNonUniformity2D    NormalisedZoneSizeNonUniformity2D    ZonePercentage2D    GrayLevelVariance2D    ZoneSizeVariance2D    ZoneSizeEntropy2D    SmallDistanceEmphasis2D    LargeDistanceEmphasis2D    LowGrayLevelDistanceZoneEmphasis2D    HighGrayLevelDistanceZoneEmphasis2D    SmallDistanceLowGrayLevelEmphasis2D    SmallDistanceHighGrayLevelEmphasis2D    LargeDistanceLowGrayLevelEmphasis2D    LargeDistanceHighGrayLevelEmphasis2D    GrayLevelDistanceNonUniformity2D    NormalisedGrayLevelDistanceNonUniformity2D    ZoneDistanceNonUniformity2D    NormalisedZoneDistanceNonUniformity2D    ZoneDistancePercentage2D    GrayLevelDistanceVariance2D    ZoneDistanceVariance2D    ZoneDistanceEntropy2D    Coarseness2D    Contrast2D    Busyness2D    Complexity2D    Strength2D    LowDependenceEmphasis2D    HighDependenceEmphasis2D    LowGrayLevelCountEmphasis2D    HighGrayLevelCountEmphasis2D    LowDependenceLowGrayLevelEmphasis2D    LowDependenceHighGrayLevelEmphasis2D    HighDependenceLowGrayLevelEmphasis2D    HighDependenceHighGrayLevelEmphasis2D    GrayLevelDependenceNonUniformity2D    NormalisedGrayLevelDependenceNonUniformity2D    DependenceCountNonUniformity2D    NormalisedDependenceCountNonUniformity2D    DependenceCountPercentage2D    GrayLevelDependenceVariance2D    DependenceCountVariance2D    DependenceCountEntropy2D    DependenceCountEnergy2D
    _______    ______________________    ______________________    _______________________    ______________________    ___________________________    ____________________________    ___________________________    ____________________    _____________________    ____________________    _____________________________    __________________    _______________________    ___________________________    _____________________________________    _________________________________    ___________________________________________    _________________________    _____________________    _________________________    _________________________    ______________________    ___________________________    _________________________________    _________________________________    _________________________    _________________________    __________________________    _________________________    ______________________________    _______________________________    ______________________________    _______________________    ________________________    _______________________    ________________________________    _____________________    __________________________    ______________________________    ________________________________________    ____________________________________    ______________________________________________    ____________________________    ________________________    ____________________________    ____________________________    _________________________    ______________________________    ____________________________________    ____________________________________    ___________________________    __________________________    _________________________________    __________________________________    ______________________________________    _______________________________________    _____________________________________    ______________________________________    ________________________________    __________________________________________    ________________________________    __________________________________________    _______________________    ___________________________    ___________________________    ____________________    ______________________________    _____________________________    ____________________________________    _____________________________________    _________________________________________    __________________________________________    ________________________________________    _________________________________________    ___________________________________    _____________________________________________    ___________________________________    _____________________________________________    __________________________    ______________________________    ______________________________    _______________________    ___________________    ___________________    __________________________    ___________________________    _______________________________    ________________________________    _______________________________    ________________________________    ________________________    __________________________________    _______________________    _________________________________    ________________    ___________________    __________________    _________________    _______________________    _______________________    __________________________________    ___________________________________    ___________________________________    ____________________________________    ___________________________________    ____________________________________    ________________________________    __________________________________________    ___________________________    _____________________________________    ________________________    ___________________________    ______________________    _____________________    ____________    __________    __________    ____________    __________    _______________________    ________________________    ___________________________    ____________________________    ___________________________________    ____________________________________    ____________________________________    _____________________________________    __________________________________    ____________________________________________    ______________________________    ________________________________________    ___________________________    _____________________________    _________________________    ________________________    _______________________

      "1"            0.0024655                   57.173                    675.82                     11.068                      8.6729                          46.565                         4.5233                      114.35                  2580.4                   7.4309                    0.00059926                    122.85                  8.6729                       0.19708                             0.94922                                0.11252                                    0.9951                               0.11632                    0.90898                    3883.2                       2580.4                    1.3078e+05                  2.3618e+07                         -0.29751                              0.98931                         0.001644                      57.174                        675.85                       11.596                          8.6687                             47.58                              4.548                        114.35                      2580.7                     7.4877                        0.00046409                      122.73                      8.6687                         0.19713                                0.94925                                   0.11255                                       0.9951                                  0.11635                       0.90921                        3883.3                          2580.7                       1.3082e+05                     2.3623e+07                            -0.21644                                0.96957                             0.97102                        1.1229                         0.00098018                              4026.2                                0.0009635                                     3914                                   0.0010494                                  4515.4                                 36.557                                  0.013495                                  2509.3                                  0.92621                              0.96166                      695.41                        0.041421                     6.7308                      0.97106                           1.1227                             0.00098015                                4026.1                                   0.00096349                                      3914.1                                     0.0010493                                     4514.8                                    146.12                                     0.013485                                      10037                                      0.92622                                0.96166                          695.39                           0.041415                       6.7564                   0.89606                1.5878                   0.0010299                       4044.5                         0.00097106                            3647.6                            0.0013676                            6380.2                          31.872                          0.013203                          1842                           0.76303                     0.85694                692.9                0.22607               7.1293                  0.10493                    148.22                         0.0010299                               4044.5                               4.2891e-05                                687.52                                 0.25647                               3.5734e+05                              31.872                                  0.013203                               111.25                             0.046084                           0.85694                        692.9                       44.223                   10.151             0.0057315       0.36515       0.026994        41509          53.247              0.80061                     2.0302                     0.00096438                        4022.6                           0.00085099                                3251.6                                0.0015501                                 8140.3                                  38.259                                    0.013582                                  1686.2                                0.59857                                  1                            696.64                         0.32268                      7.3893                    0.0080629       
      "2"            0.0020617                   95.454                    1035.3                     11.429                      7.9161                          41.032                         4.4079                      190.91                  4036.8                   7.7995                    0.00046008                    104.57                  7.9161                       0.21086                              0.9534                                0.12386                                   0.99582                               0.12644                    0.94946                     10095                       4036.8                   -1.9066e+05                  4.8383e+07                         -0.32989                              0.99441                         0.001596                      95.454                        1035.4                       11.899                          7.9126                            41.871                             4.4312                        190.91                      4036.9                     7.8439                        0.00036457                      104.48                      7.9126                         0.21092                                0.95342                                   0.12391                                      0.99583                                  0.12649                       0.94954                         10095                          4036.9                      -1.9069e+05                     4.8387e+07                            -0.26141                                0.98594                             0.96734                        1.1406                          0.0025825                               10034                                0.0025562                                   9680.6                                   0.0026925                                   11556                                 37.312                                  0.010109                                  3385.9                                  0.91727                              0.95671                        1070                        0.047944                     7.0955                      0.96737                           1.1405                              0.0025823                                 10034                                     0.002556                                      9680.9                                     0.0026925                                      11555                                    149.12                                       0.0101                                      13543                                      0.91728                                0.95671                            1070                           0.047939                         7.12                   0.87894                1.6924                   0.0028339                       9925.6                          0.0027386                            8633.6                            0.0034115                             17474                          31.832                         0.0098705                          2354                           0.72991                     0.83593               1076.5                0.26132               7.5598                 0.088426                     218.2                         0.0028339                               9925.6                                0.0013534                                 674.8                                 0.05072                               2.5181e+06                              31.832                                 0.0098705                               121.73                             0.037744                           0.83593                       1076.5                       66.086                   10.766             0.0059013       0.39908       0.010539        44586          60.208              0.77294                     2.1524                       0.002505                         10068                            0.0023228                                7628.5                                0.0034117                                  22598                                  39.306                                    0.010188                                  2164.5                                0.56105                                  1                            1067.5                          0.3399                      7.8224                    0.0056895       

Compute Texture Features for 3-D Computed Tomography (CT) Image

Import a computed tomography (CT) image volume and the corresponding ROI mask volume from the IBSI validation data set [1][2][3] as medicalVolume objects.

unzip("CTImageMaskNIfTI.zip")
data = medicalVolume("CT_image.nii.gz");
roi = medicalVolume("CT_mask.nii.gz");

Visualize a slice of the CT image volume and the corresponding ROI.

figure
imshowpair(data.Voxels(:,:,20),roi.Voxels(:,:,20),"montage")

Create a radiomics object, using the CT image volume and ROI mask volume, with default preprocessing options.

R = radiomics(data,roi)

R = 
  radiomics with properties:

                             Data: [1×1 medicalVolume]
                         ROILabel: [1×1 medicalVolume]
                         Resample: 1
                        Resegment: 1
                       Discretize: 1
                    DiscretizeIVH: 1
            ResampledVoxelSpacing: 1
               DataResampleMethod: 'linear'
               MaskResampleMethod: 'linear'
              ResegmentationRange: []
                  ExcludeOutliers: 1
       DiscreteBinSizeOrBinNumber: []
                   DiscreteMethod: 'FixedBinNumber'
    DiscreteIVHBinSizeOrBinNumber: []
                DiscreteIVHMethod: 'FixedBinNumber'

Compute the grey level co-occurrence matrix (GLCM) texture features of the ROI in the 2-D resampled CT image volume.

I = textureFeatures(R,Type=["GLCM","GLRLM"],SubType="2D")

I=1×83 table
    LabelID    JointMaximumAveraged2D    JointAverageAveraged2D    JointVarianceAveraged2D    JointEntropyAveraged2D    DifferenceAverageAveraged2D    DifferenceVarianceAveraged2D    DifferenceEntropyAveraged2D    SumAverageAveraged2D    SumVarianceAveraged2D    SumEntropyAveraged2D    AngularSecondMomentAveraged2D    ContrastAveraged2D    DissimilarityAveraged2D    InverseDifferenceAveraged2D    NormalisedInverseDifferenceAveraged2D    InverseDifferenceMomentAveraged2D    NormalisedInverseDifferenceMomentAveraged2D    InverseVarianceAveraged2D    CorrelationAveraged2D    AutoCorrelationAveraged2D    ClusterTendencyAveraged2D    ClusterShadeAveraged2D    ClusterProminenceAveraged2D    InformationCorrelation1Averaged2D    InformationCorrelation2Averaged2D    JointMaximumSliceMerged2D    JointAverageSliceMerged2D    JointVarianceSliceMerged2D    JointEntropySliceMerged2D    DifferenceAverageSliceMerged2D    DifferenceVarianceSliceMerged2D    DifferenceEntropySliceMerged2D    SumAverageSliceMerged2D    SumVarianceSliceMerged2D    SumEntropySliceMerged2D    AngularSecondMomentSliceMerged2D    ContrastSliceMerged2D    DissimilaritySliceMerged2D    InverseDifferenceSliceMerged2D    NormalisedInverseDifferenceSliceMerged2D    InverseDifferenceMomentSliceMerged2D    NormalisedInverseDifferenceMomentSliceMerged2D    InverseVarianceSliceMerged2D    CorrelationSliceMerged2D    AutoCorrelationSliceMerged2D    ClusterTendencySliceMerged2D    ClusterShadeSliceMerged2D    ClusterProminenceSliceMerged2D    InformationCorrelation1SliceMerged2D    InformationCorrelation2SliceMerged2D    ShortRunsEmphasisAveraged2D    LongRunsEmphasisAveraged2D    LowGrayLevelRunEmphasisAveraged2D    HighGrayLevelRunEmphasisAveraged2D    ShortRunLowGrayLevelEmphasisAveraged2D    ShortRunHighGrayLevelEmphasisAveraged2D    LongRunLowGrayLevelEmphasisAveraged2D    LongRunHighGrayLevelEmphasisAveraged2D    GrayLevelNonUniformityAveraged2D    NormalisedGrayLevelNonUniformityAveraged2D    RunLengthNonUniformityAveraged2D    NormalisedRunLengthNonUniformityAveraged2D    RunPercentageAveraged2D    GrayLevelVarianceAveraged2D    RunLengthVarianceAveraged2D    RunEntropyAveraged2D    ShortRunsEmphasisSliceMerged2D    LongRunsEmphasisSliceMerged2D    LowGrayLevelRunEmphasisSliceMerged2D    HighGrayLevelRunEmphasisSliceMerged2D    ShortRunLowGrayLevelEmphasisSliceMerged2D    ShortRunHighGrayLevelEmphasisSliceMerged2D    LongRunLowGrayLevelEmphasisSliceMerged2D    LongRunHighGrayLevelEmphasisSliceMerged2D    GrayLevelNonUniformitySliceMerged2D    NormalisedGrayLevelNonUniformitySliceMerged2D    RunLengthNonUniformitySliceMerged2D    NormalisedRunLengthNonUniformitySliceMerged2D    RunPercentageSliceMerged2D    GrayLevelVarianceSliceMerged2D    RunLengthVarianceSliceMerged2D    RunEntropySliceMerged2D
    _______    ______________________    ______________________    _______________________    ______________________    ___________________________    ____________________________    ___________________________    ____________________    _____________________    ____________________    _____________________________    __________________    _______________________    ___________________________    _____________________________________    _________________________________    ___________________________________________    _________________________    _____________________    _________________________    _________________________    ______________________    ___________________________    _________________________________    _________________________________    _________________________    _________________________    __________________________    _________________________    ______________________________    _______________________________    ______________________________    _______________________    ________________________    _______________________    ________________________________    _____________________    __________________________    ______________________________    ________________________________________    ____________________________________    ______________________________________________    ____________________________    ________________________    ____________________________    ____________________________    _________________________    ______________________________    ____________________________________    ____________________________________    ___________________________    __________________________    _________________________________    __________________________________    ______________________________________    _______________________________________    _____________________________________    ______________________________________    ________________________________    __________________________________________    ________________________________    __________________________________________    _______________________    ___________________________    ___________________________    ____________________    ______________________________    _____________________________    ____________________________________    _____________________________________    _________________________________________    __________________________________________    ________________________________________    _________________________________________    ___________________________________    _____________________________________________    ___________________________________    _____________________________________________    __________________________    ______________________________    ______________________________    _______________________

      "1"             0.025292                   10.263                    9.9482                     6.9415                      2.6834                          4.353                          2.8719                      20.525                   27.92                   4.3458                     0.011452                     11.872                  2.6834                       0.39071                             0.8891                                 0.3042                                    0.97287                               0.30871                    0.39971                    111.04                        27.92                     -17.682                      2401.8                           -0.10434                              0.66674                         0.021298                      10.262                        9.9491                       7.1238                          2.678                             4.5887                             2.9277                        20.525                      27.962                     4.3981                        0.0098741                       11.835                      2.678                          0.39129                                 0.8893                                    0.3049                                      0.97295                                  0.30908                       0.40201                        111.06                          27.962                        -18.094                         2408.5                             -0.052692                                0.55415                             0.91083                        1.4376                          0.023078                               119.32                                 0.021376                                   108.52                                   0.030767                                   173.59                                 75.51                                   0.087674                                  710.23                                  0.79414                               0.896                       12.076                         0.15199                     4.243                       0.91189                           1.4316                              0.023109                                 119.34                                    0.021486                                       108.64                                      0.030465                                     172.87                                    301.76                                     0.087414                                     2836.1                                      0.79414                                 0.896                           12.083                           0.15192                        4.2827         

[1] Vallières, Martin, Carolyn R. Freeman, Sonia R. Skamene, and Issam El Naqa. “A Radiomics Model from Joint FDG-PET and MRI Texture Features for the Prediction of Lung Metastases in Soft-Tissue Sarcomas of the Extremities.” The Cancer Imaging Archive, 2015. https://doi.org/10.7937/K9/TCIA.2015.7GO2GSKS.

[2] Vallières, M, C R Freeman, S R Skamene, and I El Naqa. “A Radiomics Model from Joint FDG-PET and MRI Texture Features for the Prediction of Lung Metastases in Soft-Tissue Sarcomas of the Extremities.” Physics in Medicine and Biology 60, no. 14 (July 7, 2015): 5471–96. https://doi.org/10.1088/0031-9155/60/14/5471.

[3] Clark, Kenneth, Bruce Vendt, Kirk Smith, John Freymann, Justin Kirby, Paul Koppel, Stephen Moore, et al. “The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository.” Journal of Digital Imaging 26, no. 6 (December 2013): 1045–57. https://doi.org/10.1007/s10278-013-9622-7.

Input Arguments

R — Data and ROI for feature computation

radiomics object

Data and ROI for feature computation, specified as a radiomics object. The radiomics object R contains details of the preprocessed data and region of interest (ROI) from which to compute the features.

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Example: textureFeatures(R,Type="GLCM",SubType="2D") computes the GLCM texture features as the average over 2-D slices in the 2-D resampled data.

Type — Category of texture features

"all" (default) | string scalar | character vector | string array | cell array of character vectors

Category of texture features to compute, specified as one or more of these options.

• "GLCM" — Grey level co-occurrence matrix

• "GLRLM" — Grey level run length matrix

• "GLSZM" — Grey level size zone matrix

• "GLDZM" — Grey level distance zone matrix

• "NGTDM" — Neighbourhood grey tone difference matrix

• "NGLDM" — Neighbourhood grey level dependence matrix

• "all"

If you specify "all", the function computes every category of texture features. For more information on which specific texture features each category includes, see IBSI Standard and Radiomics Function Feature Correspondences.

Data Types: char | string

SubType — Resampling from which to compute texture features

"2D" | "2.5D" | "3D" | "all"

Resampling from which to compute texture features, specified as one of these options.

• "2D" — Computes features for each 2-D slice in the 2-D resampled data and averages them. This is the default option for 2-D data, when the Data and ROILabel properties of the radiomics object R are 2-D matrices or medicalImage objects.

• "2.5D" — Computes features after merging all 2-D slices in the 2-D resampled data.

• "3D" — Computes features for the entire 3-D volume in the 3-D resampled data. This is the default option for 3-D data, when the Data and ROILabel properties of the radiomics object R are 3-D arrays or medicalVolume objects. 3-D resampling is not applicable for 2-D data.

• "all" — Computes features for all applicable options.

For 3-D data, when you perform 3-D resampling of the volume, the function makes the voxel spacing along all three spatial dimensions isotropic. However, when you perform 2-D resampling of the volume, the function makes the voxel spacing along only the x- and y-dimensions isotropic, while retaining the voxel spacing of the input volume along the z-dimension.

Data Types: char | string

Output Arguments

T — Texture features

table

Texture features, returned as a table. The first column in T is LabelID. The subsequent columns are the texture features. Each row of the table corresponds to an ROI. For more details on which texture features are computed in each Type and SubType, see IBSI Standard and Radiomics Function Feature Correspondences.

Version History

Introduced in R2023b

R2025a: Compute texture features for multiple ROIs

Compute texture features for multiple regions of interest (ROIs) in a medical image or medical volume.

R2024b: Compute one or more types of texture features

Compute one or more types of texture features by specifying one or more options in the name-value argument Type.