2D intensity features:
| Nyxus feature code | Description |
|---|---|
| INTEGRATED_INTENSITY | Integrated intensity of the region of interest (ROI) |
| MEAN | Mean intensity value of the ROI |
| MEDIAN | The median value of pixels in the ROI |
| MIN | Minimum intensity value in the ROI |
| MAX | Maximum intensity value in the ROI |
| RANGE | Range between the maximmu and minimum |
| COVERED_IMAGE_INTENSITY_RANGE | intensity range of the ROI to intensity range of all the ROIs |
| STANDARD_DEVIATION | Standard deviation (unbiased) |
| STANDARD_DEVIATION_BIASED | Biased standard deviation |
| COV | Coefficient of variation |
| STANDARD_ERROR | Standard error |
| SKEWNESS | Skewness - the 3rd standardized moment |
| KURTOSIS | Kurtosis - the 4th standardized moment (Pearson formula) |
| EXCESS_KURTOSIS | Excess kurtosis - the 4th standardized moment (Fisher-corrected formula, IBSI feature IPH6) |
| HYPERSKEWNESS | Hyperskewness - the 5th standardized moment |
| HYPERFLATNESS | Hyperflatness - the 6th standardized moment |
| MEAN_ABSOLUTE_DEVIATION | Mean absolute deviation |
| MEDIAN_ABSOLUTE_DEVIATION | Median absolute deviation |
| ENERGY | ROI energy |
| ROOT_MEAN_SQUARED | Root of mean squared deviation |
| ENTROPY | ROI entropy - a measure of the amount of information (that is, randomness) in the ROI |
| MODE | The mode value of pixels in the ROI - the value that appears most often in a set of ROI intensity values |
| UNIFORMITY | Uniformity - measures how uniform the distribution of ROI intensities is |
| UNIFORMITY_PIU | Percent image uniformity, another measure of intensity distribution uniformity |
| P01, P10, P25, P75, P90, P99 | 1%, 10%, 25%, 75%, 90%, and 99% percentiles of intensity distribution |
| QCOD | quartile coefficient of dispersion |
| INTERQUARTILE_RANGE | Distribution's interquartile range |
| ROBUST_MEAN_ABSOLUTE_DEVIATION | Robust mean absolute deviation |
| MASS_DISPLACEMENT | ROI mass displacement |
2D morphology features:
| Nyxus feature code | Description |
|---|---|
| AREA_PIXELS_COUNT | ROI area in the number of pixels |
| AREA_UM2 | ROI area in metric units |
| CENTROID_X | X-coordinate of the enter point of the ROI |
| CENTROID_Y | Y-coordinate of the center point of the ROI |
| COMPACTNESS | Mean squared distance of the object’s pixels from the centroid divided by the area. Compactness of a filled circle is 1, compactness of irregular objects or objects with holes is greater than 1 |
| BBOX_YMIN | Y-position and size of the smallest axis-aligned box containing the ROI |
| BBOX_XMIN | X-position and size of the smallest axis-aligned box containing the ROI |
| BBOX_HEIGHT | Height of the smallest axis-aligned box containing the ROI |
| BBOX_WIDTH | Width of the smallest axis-aligned box containing the ROI |
| MAJOR_AXIS_LENGTH | Length (in pixels) of the major axis of the ellipse that has the same normalized second central moments as the region |
| MINOR_AXIS_LENGTH | Length (in pixels) of the minor axis of the ellipse that has the same normalized second central moments as the region |
| ECCENTRICITY | Ratio of ROI's inertia ellipse focal distance over the major axis length |
| ORIENTATION | Angle between the 0th axis and the major axis of the ellipse that has same second moments as the region |
| ROUNDNESS | Represents how similar a ROI's inertia ellipse is to circle. Calculated based on the major and minor exis lengths |
| EXTENT | Proportion of the pixels (2D) or voxels (3D) in the bounding box that are also in the region. Computed as the area/volume of the object divided by the area/volume of the bounding box |
| ASPECT_RATIO | The ratio of the major axis to the minor axis of ROI's inertia ellipse |
| CONVEX_HULL_AREA | Area of ROI's convex hull |
| SOLIDITY | Ratio of pixels in the ROI common with its convex hull image |
| PERIMETER | Number of pixels in ROI's contour |
| EQUIVALENT_DIAMETER | Diameter of a circle with the same area as the ROI |
| EDGE_MEAN_INTENSITY | Mean intensity of ROI's contour pixels |
| EDGE_STDDEV_INTENSITY | Standard deviation of ROI's contour pixels |
| EDGE_MAX_INTENSITY | Maximum intensity of ROI's contour pixels |
| EDGE_MIN_INTENSITY | Minimum intensity of ROI's contour pixels |
| CIRCULARITY | Represents how similar a shape is to circle. Clculated based on ROI's area and its convex perimeter |
| EROSIONS_2_VANISH | Number of erosion operations for a ROI to vanish in its axis aligned bounding box |
| EROSIONS_2_VANISH_COMPLEMENT | Number of erosion operations for a ROI to vanish in its convex hull |
| FRACT_DIM_BOXCOUNT | Fractal dimension determined by the box counting method according to ISO 9276-6. If C is a fractal set, with fractal dimension DF < D, then the number N of boxes of size R needed to cover the set scales as R^(-DF). DF is known as the Hausdorf dimension, or Kolmogorov capacity, or Kolmogorov dimension, or simply box-counting dimension |
| FRACT_DIM_PERIMETER | Fractal dimension determined by the perimeter method according to ISO 9276-6. If we approximate ROI's contour with rulers of length lambda, the perimeter based fractal dimension is the slope of the best fit line of log ROI perimeter versus log lambda, subtracted from 1 |
| WEIGHTED_CENTROID_Y | X-coordinate of centroid |
| WEIGHTED_CENTROID_X | Y-coordinate of centroid |
| MIN_FERET_DIAMETER | Feret diameter (or maximum caliber diameter) is the longest distance between any two ROI points along the same (horizontal) direction. This feature is the minimum Feret diameter for angles ranging 0 to 180 degrees |
| MAX_FERET_DIAMETER | Maximum Feret diameter for angles ranging 0 to 180 degrees |
| MIN_FERET_ANGLE | Angle of the minimum Feret diameter |
| MAX_FERET_ANGLE | Angle of the maximum Feret diameter |
| STAT_FERET_DIAM_MIN | Minimum of Feret diameters of the ROI rotated at angles 0-180 degrees |
| STAT_FERET_DIAM_MAX | Maximum of Feret diameters of the ROI rotated at angles 0-180 degrees |
| STAT_FERET_DIAM_MEAN | Mean Feret diameter of the ROI rotated at angles 0-180 degrees |
| STAT_FERET_DIAM_MEDIAN | Median value of Feret diameters of the ROI rotated at angles 0-180 degrees |
| STAT_FERET_DIAM_STDDEV | Standard deviation of Feret diameter of the ROI rotated at angles 0-180 degrees |
| STAT_FERET_DIAM_MODE | Histogram mode of Feret diameters of the ROI rotated at angles 0-180 degrees |
| STAT_MARTIN_DIAM_MIN | Minimum of Martin diameters of the ROI rotated at angles 0-180 degrees |
| STAT_MARTIN_DIAM_MAX | Maximum of Martin diameters of the ROI rotated at angles 0-180 degrees |
| STAT_MARTIN_DIAM_MEAN | Mean of Martin diameter of the ROI rotated at angles 0-180 degrees |
| STAT_MARTIN_DIAM_MEDIAN | Median value of Martin diameters of the ROI rotated at angles 0-180 degrees |
| STAT_MARTIN_DIAM_STDDEV | Standard deviation of Martin diameter of the ROI rotated at angles 0-180 degrees |
| STAT_MARTIN_DIAM_MODE | Histogram mode of Martin diameters of the ROI rotated at angles 0-180 degrees |
| STAT_NASSENSTEIN_DIAM_MIN | Minimum of Nassenstein diameters of the ROI rotated at angles 0-180 degrees |
| STAT_NASSENSTEIN_DIAM_MAX | Maximum of Nassenstein diameters of the ROI rotated at angles 0-180 degrees |
| STAT_NASSENSTEIN_DIAM_MEAN | Mean of Nassenstein diameter of the ROI rotated at angles 0-180 degrees |
| STAT_NASSENSTEIN_DIAM_MEDIAN | Median value of Nassenstein diameters of the ROI rotated at angles 0-180 degrees |
| STAT_NASSENSTEIN_DIAM_STDDEV | Standard deviation of Nassenstein diameter of the ROI rotated at angles 0-180 degrees |
| STAT_NASSENSTEIN_DIAM_MODE | Histogram mode of Nassenstein diameters of the ROI rotated at angles 0-180 degrees |
| MAXCHORDS_MAX | Maximum of ROI's longest chords built at angles 0-180 degrees |
| MAXCHORDS_MAX_ANG | Angle of the chord referenced in MAXCHORDS_MAX |
| MAXCHORDS_MIN | Minimum of ROI's longest chords built at angles 0-180 degrees |
| MAXCHORDS_MIN_ANG | Angle of the chord referenced in MAXCHORDS_MIN |
| MAXCHORDS_MEDIAN | Median value of ROI's longest chords built at angles 0-180 degrees |
| MAXCHORDS_MEAN | Mean value of ROI's longest chords built at angles 0-180 degrees |
| MAXCHORDS_MODE | Histogram mode of ROI's longest chords built at angles 0-180 degrees |
| MAXCHORDS_STDDEV | Sndard deviation of ROI's longest chords built at angles 0-180 degrees |
| ALLCHORDS_MAX | Maximum of all the ROI's chords built at angles 0-180 degrees |
| ALLCHORDS_MAX_ANG | Angle of the chord referenced in ALLCHORDS_MAX |
| ALLCHORDS_MIN | Minimum of all the ROI's chords built at angles 0-180 degrees |
| ALLCHORDS_MIN_ANG | Angle of the chord referenced in ALLCHORDS_MIN |
| ALLCHORDS_MEDIAN | Median value of all the ROI's chords built at angles 0-180 degrees |
| ALLCHORDS_MEAN | Mean value of all the ROI's chords built at angles 0-180 degrees |
| ALLCHORDS_MODE | Histogram mode of all the ROI's chords built at angles 0-180 degrees |
| ALLCHORDS_STDDEV | Sndard deviation of all the ROI's chords built at angles 0-180 degrees |
| EULER_NUMBER | Euler characteristic of the ROI - the number of objects in the ROI minus the number of holes assuming the 8-neighbor connectivity of ROI's pixels |
| EXTREMA_P1_X | X-ccordinate of ROI's axis aligned bounding box extremum point #1 |
| EXTREMA_P1_Y | Y-ccordinate of ROI's axis aligned bounding box extremum point #1 |
| EXTREMA_P2_X | X-ccordinate of ROI's axis aligned bounding box extremum point #2 |
| EXTREMA_P2_Y | |
| EXTREMA_P3_X | X-ccordinate of ROI's axis aligned bounding box extremum point #3 |
| EXTREMA_P3_Y | |
| EXTREMA_P4_X | X-ccordinate of ROI's axis aligned bounding box extremum point #4 |
| EXTREMA_P4_Y | |
| EXTREMA_P5_X | X-ccordinate of ROI's axis aligned bounding box extremum point #5 |
| EXTREMA_P5_Y | |
| EXTREMA_P6_X | X-ccordinate of ROI's axis aligned bounding box extremum point #6 |
| EXTREMA_P6_Y | |
| EXTREMA_P7_X | X-ccordinate of ROI's axis aligned bounding box extremum point #7 |
| EXTREMA_P7_Y | |
| EXTREMA_P8_X | X-ccordinate of ROI's axis aligned bounding box extremum point #8 |
| EXTREMA_P8_Y | |
| POLYGONALITY_AVE | The score ranges from $ -infty $ to 10. Score 10 indicates the object shape is polygon and score $ -infty $ indicates the ROI shape is not polygon |
| HEXAGONALITY_AVE | The score ranges from $ -infty $ to 10. Score 10 indicates the object shape is hexagon and score $ -infty $ indicates the ROI shape is not hexagon |
| HEXAGONALITY_STDDEV | Standard deviation of hexagonality_score relative to its mean |
| DIAMETER_MIN_ENCLOSING_CIRCLE | Diameter of the minimum enclosing circle |
| DIAMETER_CIRCUMSCRIBING_CIRCLE | Diameter of the circumscribing circle |
| DIAMETER_INSCRIBING_CIRCLE | Diameter of inscribing circle |
| GEODETIC_LENGTH | Geodetic length approximated by a rectangle with the same area and perimeter: $ area = geodeticlength * thickness$; |
| THICKNESS | Thickness approximated by a rectangle with the same area and perimeter: $ area = geodeticlength * thickness$; |
| ROI_RADIUS_MEAN | Mean centroid to edge distance |
| ROI_RADIUS_MAX | Maximum of centroid to edge distances |
| ROI_RADIUS_MEDIAN | Median value of centroid to edge distances |
2D texture features:
| Nyxus feature code | Description |
|---|---|
| GLCM_ASM | GLCM, Angular second moment, IBSI # 8ZQL |
| GLCM_ACOR | GLCM, Autocorrelation, IBSI # QWB0 |
| GLCM_CLUPROM | GLCM, Cluster prominence, IBSI # AE86 |
| GLCM_CLUSHADE | GLCM, Cluster shade, IBSI # 7NFM |
| GLCM_CLUTEND | GLCM, Cluster tendency, IBSI # DG8W |
| GLCM_CONTRAST | GLCM, Contrast, IBSI # ACUI |
| GLCM_CORRELATION | GLCM, Correlation, IBSI # NI2N |
| GLCM_DIFAVE | GLCM, Difference average, IBSI # TF7R |
| GLCM_DIFENTRO | GLCM, Difference entropy, IBSI # NTRS |
| GLCM_DIFVAR | GLCM, Difference variance, IBSI # D3YU |
| GLCM_DIS | GLCM, Dissimilarity, IBSI # 8S9J |
| GLCM_ENERGY | GLCM, Energy |
| GLCM_ENTROPY | GLCM, Entropy |
| GLCM_HOM1 | GLCM, Homogeneity-1 |
| GLCM_HOM2 | GLCM, Homogeneity-2 |
| GLCM_ID | GLCM, Inverse difference, IBSI # IB1Z |
| GLCM_IDN | GLCM, Inverse difference normalized, IBSI # NDRX |
| GLCM_IDM | GLCM, Inverse difference moment, IBSI # WF0Z |
| GLCM_IDMN | GLCM, Inverse difference moment normalized, IBSI # 1QCO |
| GLCM_INFOMEAS1 | GLCM, Information measure of correlation 1, IBSI # R8DG |
| GLCM_INFOMEAS2 | GLCM, Information measure of correlation 2, IBSI # JN9H |
| GLCM_IV | GLCM, Inverse variance, IBSI # E8JP |
| GLCM_JAVE | GLCM, Joint average, IBSI # 60VM |
| GLCM_JE | GLCM, Joint entropy, IBSI # TU9B |
| GLCM_JMAX | GLCM, Joint maximum (aka max probability), IBSI # GYBY |
| GLCM_JVAR | GLCM, Joint variance (aka sum of squares), IBSI # UR99 |
| GLCM_SUMAVERAGE | GLCM, Sum average, IBSI # ZGXS |
| GLCM_SUMENTROPY | GLCM, Sum entropy, IBSI # P6QZ |
| GLCM_SUMVARIANCE | GLCM, Sum variance, IBSI # OEEB |
| GLCM_VARIANCE | GLCM, Variance |
| GLRLM_SRE | Grey level run-length matrix (GLRLM) based feature, Short Run Emphasis |
| GLRLM_LRE | GLRLM, Long Run Emphasis |
| GLRLM_GLN | GLRLM, Grey Level Non-Uniformity |
| GLRLM_GLNN | GLRLM, Grey Level Non-Uniformity Normalized |
| GLRLM_RLN | GLRLM, Run Length Non-Uniformity |
| GLRLM_RLNN | GLRLM, Run Length Non-Uniformity Normalized |
| GLRLM_RP | GLRLM, Run Percentage |
| GLRLM_GLV | GLRLM, Grey Level Variance |
| GLRLM_RV | GLRLM, Run Variance |
| GLRLM_RE | GLRLM, Run Entropy |
| GLRLM_LGLRE | GLRLM, Low Grey Level Run Emphasis |
| GLRLM_HGLRE | GLRLM, High Grey Level Run Emphasis |
| GLRLM_SRLGLE | GLRLM, Short Run Low Grey Level Emphasis |
| GLRLM_SRHGLE | GLRLM, Short Run High Grey Level Emphasis |
| GLRLM_LRLGLE | GLRLM, Long Run Low Grey Level Emphasis |
| GLRLM_LRHGLE | GLRLM, Long Run High Grey Level Emphasis |
| GLDZM_SDE | GLDZM, Small Distance Emphasis |
| GLDZM_LDE | GLDZM, Large Distance Emphasis |
| GLDZM_LGLE | GLDZM, Low Grey Level Emphasis |
| GLDZM_HGLE | GLDZM, High GreyLevel Emphasis |
| GLDZM_SDLGLE | GLDZM, Small Distance Low Grey Level Emphasis |
| GLDZM_SDHGLE | GLDZM, Small Distance High GreyLevel Emphasis |
| GLDZM_LDLGLE | GLDZM, Large Distance Low Grey Level Emphasis |
| GLDZM_LDHGLE | GLDZM, Large Distance High Grey Level Emphasis |
| GLDZM_GLNU | GLDZM, Grey Level Non Uniformity |
| GLDZM_GLNUN | GLDZM, Grey Level Non Uniformity Normalized |
| GLDZM_ZDNU | GLDZM, Zone Distance Non Uniformity |
| GLDZM_ZDNUN | GLDZM, Zone Distance Non Uniformity Normalized |
| GLDZM_ZP | GLDZM, Zone Percentage |
| GLDZM_GLM | GLDZM, Grey Level Mean |
| GLDZM_GLV | GLDZM, Grey Level Variance |
| GLDZM_ZDM | GLDZM, Zone Distance Mean |
| GLDZM_ZDV | GLDZM, Zone Distance Variance |
| GLDZM_ZDE | GLDZM, Zone Distance Entropy |
| GLSZM_SAE | GLDZM, Grey level size zone matrix (GLSZM) based feature, Small Area Emphasis |
| GLSZM_LAE | Large Area Emphasis |
| GLSZM_GLN | Grey Level Non - Uniformity |
| GLSZM_GLNN | Grey Level Non - Uniformity Normalized |
| GLSZM_SZN | Size - Zone Non - Uniformity |
| GLSZM_SZNN | Size - Zone Non - Uniformity Normalized |
| GLSZM_ZP | Zone Percentage |
| GLSZM_GLV | Grey Level Variance |
| GLSZM_ZV | Zone Variance |
| GLSZM_ZE | Zone Entropy |
| GLSZM_LGLZE | Low Grey Level Zone Emphasis |
| GLSZM_HGLZE | High Grey Level Zone Emphasis |
| GLSZM_SALGLE | Small Area Low Grey Level Emphasis |
| GLSZM_SAHGLE | Small Area High Grey Level Emphasis |
| GLSZM_LALGLE | Large Area Low Grey Level Emphasis |
| GLSZM_LAHGLE | Large Area High Grey Level Emphasis |
| GLDM_SDE | Grey level dependency matrix (GLDM) based feature, Small Dependence Emphasis(SDE) |
| GLDM_LDE | Large Dependence Emphasis (LDE) |
| GLDM_GLN | Grey Level Non-Uniformity (GLN) |
| GLDM_DN | Dependence Non-Uniformity (DN) |
| GLDM_DNN | Dependence Non-Uniformity Normalized (DNN) |
| GLDM_GLV | Grey Level Variance (GLV) |
| GLDM_DV | Dependence Variance (DV) |
| GLDM_DE | Dependence Entropy (DE) |
| GLDM_LGLE | Low Grey Level Emphasis (LGLE) |
| GLDM_HGLE | High Grey Level Emphasis (HGLE) |
| GLDM_SDLGLE | Small Dependence Low Grey Level Emphasis (SDLGLE) |
| GLDM_SDHGLE | Small Dependence High Grey Level Emphasis (SDHGLE) |
| GLDM_LDLGLE | Large Dependence Low Grey Level Emphasis (LDLGLE) |
| GLDM_LDHGLE | Large Dependence High Grey Level Emphasis (LDHGLE) |
| NGLDM_LDE | Low Dependence Emphasis |
| NGLDM_HDE | High Dependence Emphasis |
| NGLDM_LGLCE | Low Grey Level Count Emphasis |
| NGLDM_HGLCE | High Grey Level Count Emphasis |
| NGLDM_LDLGLE | Low Dependence Low Grey Level Emphasis |
| NGLDM_LDHGLE | Low Dependence High Grey Level Emphasis |
| NGLDM_HDLGLE | High Dependence Low Grey Level Emphasis |
| NGLDM_HDHGLE | High Dependence High Grey Level Emphasis |
| NGLDM_GLNU | Grey Level Non-Uniformity |
| NGLDM_GLNUN | Grey Level Non-Uniformity Normalised |
| NGLDM_DCNU | Dependence Count Non-Uniformity |
| NGLDM_DCNUN | Dependence Count Non-Uniformity Normalised |
| NGLDM_GLM | Grey Level Mean |
| NGLDM_GLV | Grey Level Variance |
| NGLDM_DCM | Dependence Count Mean |
| NGLDM_DCV | Dependence Count Variance |
| NGLDM_DCE | Dependence Count Entropy |
| NGLDM_DCENE | Dependence Count Energy |
| NGTDM_COARSENESS | Neighbouring Grey Tone Difference Matrix (NGTDM) Features, Coarseness |
| NGTDM_CONTRAST | NGTDM, Contrast |
| NGTDM_BUSYNESS | NGTDM, Busyness |
| NGTDM_COMPLEXITY | NGTDM, Complexity |
| NGTDM_STRENGTH | NGTDM, Strength |
2D radial intensity distribution features:
| Nyxus feature code | Description |
|---|---|
| ZERNIKE2D | Zernike features |
| FRAC_AT_D | Fraction of total intensity at a given radius |
| MEAN_FRAC | Mean fractional intensity at a given radius |
| RADIAL_CV | Coefficient of variation of intensity within a ring (band), calculated across |
2D frequency and orientational features:
| Nyxus feature code | Description |
|---|---|
| GABOR | A set of Gabor filters of varying frequencies and orientations |
2D shape image moments (calculated with constant pixel intensity 1.0 within the ROI segment):
| Nyxus feature code | Description |
|---|---|
| SPAT_MOMENT_<order> | Spatial (raw) moments of order 00, 01, 02, 03, 10, 11, 12, 20, 21, 30 |
| WEIGHTED_SPAT_MOMENT_<order> | Spatial moments weighted by pixel distance to ROI edge of order 00, 01, 02, 03, 10, 11, 20, 21, 30 |
| CENTRAL_MOMENT_<order> | Central moments of order 02, 03, 11, 12, 20, 21, 30 |
| WEIGHTED_CENTRAL_MOMENT_<order> | Central moments weighted by pixel distance to ROI edge of order 02, 03, 11, 12, 20, 21, 30 |
| NORM_CENTRAL_MOMENT_<order> | Normalized central moments of order 02, 03, 11, 12, 20, 21, 30 |
| NORM_SPAT_MOMENT_<order> | Normalized (standardized) spatial moments of order 00, 01, 02, 03, 10, 20, 30 |
| HU_M<1-7> | Hu's moments of order 1 to 7 |
| WEIGHTED_HU_M<1-7> | Weighted Hu's moment of order 1-7 |
2D intensity image moments (calculated with respect to pixels' actual intensities within the ROI segment):
| Nyxus feature code | Description |
|---|---|
| IMOM_RM_<order> | Spatial (raw) moments of order 00, 01, 02, 03, 10, 11, 12, 20, 21, 30 |
| IMOM_RM_01 | of order 00, 01, 02, etc |
| IMOM_WRM_<order> | Spatial moments weighted by pixel distance to ROI edge of order 00, 01, 02, 03, 10, 11, 12, 20, 21, 30 |
| IMOM_СM_<order> | Central moments of order 02, 03, 11, 12, 20, 21, 30 |
| IMOM_WСM_<order> | Central moments weighted by pixel distance to ROI edge of order 02, 03, 11, 12, 20, 21, 30 |
| IMOM_NСM_<order> | Normalized central moments of order 02, 03, 11, 20, 21, 30 |
| IMOM_NRM_<order> | Normalized (standardized) spatial moments of order 00, 01, 02, 03, 10, 20, 30 |
| IMOM_HU<1-7> | Hu's moment 1-7 |
| IMOM_WHU<1-7> | Weighted Hu's moment 1-7 |
2D neighbor features:
| Nyxus feature code | Description |
|---|---|
| NUM_NEIGHBORS | The number of neighbors bordering the ROI's perimeter within proximity radius specified by command line argument --pixelDistance. (Default value of --pixelDistance is 5.) Algorithmically calculating this feature invilves solving the nearest neighbors search problem that in turn involves the proximity measure and the proximity threshold. Particularly, this plugin uses the L_2 norm measure over Cartesian space of pixel coordinates and parameter --pixelDistance |
| PERCENT_TOUCHING | Percent of ROI's contour pixels located at distance 0 from neighboring other ROIs's contour |
| CLOSEST_NEIGHBOR1_DIST | Distance in pixels from ROI's centroid to the nearest neighboring ROI's centroid |
| CLOSEST_NEIGHBOR1_ANG | Angle in degrees between ROI's centroid and its nearest neighboring ROI's centroid |
| CLOSEST_NEIGHBOR2_DIST | Distance in pixels from ROI's centroid to the second nearest neighboring ROI's centroid |
| CLOSEST_NEIGHBOR2_ANG | Angle in degrees between ROI's centroid and its second nearest neighboring ROI's centroid |
| ANG_BW_NEIGHBORS_MEAN | Mean angle in degrees between ROI's centroid and centroids of its neighboring ROIs |
| ANG_BW_NEIGHBORS_STDDEV | Standard deviation in degrees of angles between ROI's centroid and centroids of its neighboring ROIs |
| ANG_BW_NEIGHBORS_MODE | Mode value in degrees of angles between ROI's centroid and centroids of its neighboring ROIs |
3D voxel intensity features:
| Nyxus feature code | Description |
|---|---|
| 3COV | Coefficient of variation |
| 3COVERED_IMAGE_INTENSITY_RANGE | intensity range of the ROI to intensity range of all the ROIs |
| 3ENERGY | ROI energy |
| 3ENTROPY | ROI entropy - a measure of the amount of information (that is, randomness) in the ROI |
| 3EXCESS_KURTOSIS | measure of how ROI intensity distribution's tails deviate from those of a normal distribution |
| 3HYPERFLATNESS | 6th standardized moment |
| 3HYPERSKEWNESS | 5th standardized moment |
| 3INTEGRATED_INTENSITY | total signal within the ROI |
| 3INTERQUARTILE_RANGE | difference between the 75th and 25th percentiles |
| 3KURTOSIS | 4th standardized moment |
| 3MAX, 3MEAN, 3MEDIAN, 3MIN | minimum, mean, median, and minimum signal value within the ROI |
| 3MEAN_ABSOLUTE_DEVIATION | measure of dispersion around the mean value |
| 3MEDIAN_ABSOLUTE_DEVIATION | measure of dispersion around the median value |
| 3MODE | mode value of voxels signal within the ROI (the most abundant signal value within the ROI) |
| 3P01, 3P10, 3P25, 3P75, 3P90, 3P99 | 1%, 10%, 25%, 75%, 90%, and 99% percentiles of intensity distribution |
| 3QCOD | quartile coefficient of dispersion - measure of statistical dispersion that focuses on the middle 50% of the data, making it robust to outliers |
| 3RANGE | range between the 3MAX and 3MIN |
| 3ROBUST_MEAN | the mean calculated after discarding outliers |
| 3ROBUST_MEAN_ABSOLUTE_DEVIATION | the mean absolute deviation calculated after discarding outliers |
| 3ROOT_MEAN_SQUARED | root of mean squared deviation |
| 3SKEWNESS | 3rd standardized moment |
| 3STANDARD_DEVIATION | standard deviation (unbiased) |
| 3STANDARD_DEVIATION_BIASED | biased standard deviation |
| 3STANDARD_ERROR | standard error |
| 3UNIFORMITY | measure of how uniform the distribution of ROI intensities is |
| 3UNIFORMITY_PIU | the uniformity expressed in the units of percent image uniformity (PIU) |
| 3VARIANCE | variance |
| 3VARIANCE_BIASED | variance calculated with respect to biased sample mean |
3D shape features:
3D texture features:
| Nyxus feature code | Description |
|---|---|
| 3GLCM_<name> | 3-dimensional version of the GLCM feature (name = ACOR, ASM, CLUPROM, CLUSHADE, CLUTEND, CONTRAST, CORRELATION, DIFAVE, DIFENTRO, DIFVAR, DIS, ID, IDN, IDM, IDMN, INFOMEAS1, INFOMEAS2, IV, JAVE, JE, JMAX, JVAR, SUMAVERAGE, SUMENTROPY, or SUMVARIANCE) |
| 3GLDM_<name> | 3-dimensional version of the GLDM feature (name = SDE, LDE, LGLE, HGLE, SDLGLE, SDHGLE, LDLGLE, LDHGLE, GLN, DN, DNN, GLV, DV, or DE) |
| 3GLDZM_<name> | 3-dimensional version of the GLDZM feature (name = SDE, LDE, LGLZE, HGLZE, SDLGLE, SDHGLE, LDLGLE, LDHGLE, GLNU, GLNUN, ZDNU, ZDNUN, ZP, GLM, GLV, ZDM, ZDV, or ZDE) |
| 3GLRLM_<name> | 3-dimensional version of the GLRLM feature (name = SRE, LRE, LGLRE, HGLRE, SRLGLE, SRHGLE, LRLGLE, LRHGLE, GLN, GLNN, RLN, RLNN, RP, GLV, RV, or RE) |
| 3GLSZM_<name> | 3-dimensional version of the GLSZM feature (name = SAE, LAE, LGLZE, HGLZE, SALGLE, SAHGLE, LALGLE, LAHGLE, GLN, GLNN, SZN, SZNN, ZP, GLV, ZV, or ZE) |
| 3NGLDM_<name> | 3-dimensional version of the NGLDM feature (name = LDE, HDE, LGLCE, HGLCE, LDLGLE, LDHGLE, HDLGLE, HDHGLE, GLNU, GLNUN, DCNU, DCNUN, DCP, GLM, GLV, DCM, DCV, DCENT, or DCENE) |
| 3NGTDM_<name> | 3-dimensional version of the NGTDM feature (name = COARSENESS, CONTRAST, BUSYNESS, COMPLEXITY, or STRENGTH) |