HistogramFeatures¶
-
MLModule
¶ genre Histogram
author Jan Hendrik Moltz
package FMEstable/ReleaseMeVis
dll MLHistogramFeatures
definition MLHistogramFeatures.def see also HistogramParameters
keywords energy
,mean
,absolute
,deviation
,root
,mean
,squared
,skewness
,kurtosis
Purpose¶
Computes advanced first-order features from a histogram.
Usage¶
Connect a HistogramObject (as computed by Histogram
) to inHistogram
and press Update
.
Details¶
This modules implements the first-order features from pyradiomics (http://pyradiomics.readthedocs.io/en/latest/features.html#module-radiomics.firstorder) that are not included in HistogramParameters
. The input is a histogram, which has to be non-normalized and non-weighted, i.e., it has to contain actual counts of values. The bin width may differ from 1.
In the formulas below let P be the histogram,
and
and let i iterate over all bins.
Parameter Fields¶
Field Index¶
[] : Trigger |
On Input Change Behavior : Enum |
Update : Trigger |
Clear : Trigger |
Range : Float |
|
doNotClearOnFailedUpdate : Bool |
Robust Mean Absolute Deviation : Float |
|
Energy : Float |
Root Mean Squared : Float |
|
Entropy (log2) : Float |
Skewness : Float |
|
Has Valid Output : Bool |
Status Code : Enum |
|
Kurtosis : Float |
Status Message : String |
|
Mean Absolute Deviation : Float |
Uniformity : Float |
Visible Fields¶
On Input Change Behavior¶
-
name:
onInputChangeBehavior
, type:
Enum
, default:
Clear
, deprecated name:
shouldUpdateAutomatically,shouldAutoUpdate
¶ Declares how the module should react if a value of an input field changes.
Values:
Title | Name | Deprecated Name |
---|---|---|
Update | Update | TRUE |
Clear | Clear | FALSE |
Status Code¶
-
name:
statusCode
, type:
Enum
, persistent:
no
¶ Reflects module’s status (successful or failed computations) as one of some predefined enumeration values.
Values:
Title | Name |
---|---|
Ok | Ok |
Invalid input object | Invalid input object |
Invalid input parameter | Invalid input parameter |
Internal error | Internal error |
Status Message¶
-
name:
statusMessage
, type:
String
, persistent:
no
¶ Gives additional, detailed information about status code as human-readable message.
Has Valid Output¶
-
name:
hasValidOutput
, type:
Bool
, persistent:
no
¶ Indicates validity of output field values (success of computation).
[]¶
-
name:
updateDone
, type:
Trigger
, persistent:
no
¶ Notifies that an update was performed (Check status interface fields to identify success or failure).
Energy¶
-
name:
outEnergy
, type:
Float
, persistent:
no
¶ Energy (measure of the magnitude of voxel values in an image)
Mean Absolute Deviation¶
-
name:
outMeanAbsoluteDeviation
, type:
Float
, persistent:
no
¶ MAD (mean distance of all intensity values from the mean value)
Robust Mean Absolute Deviation¶
-
name:
outRobustMeanAbsoluteDeviation
, type:
Float
, persistent:
no
¶ Robust MAD (mean distance of all intensity values from the mean value calculated on the subset of image array with gray levels in between, or equal to the 10th and 90th percentile)
where P_{10-90} is the histogram reduced to all bins between the 10th and 90th percentile of P. The percentile computation was reimplemented to match numpy’s version which differs from the
Histogram
.
Root Mean Squared¶
-
name:
outRootMeanSquared
, type:
Float
, persistent:
no
¶ RMS (square-root of the mean of all the squared intensity values, another measure of the magnitude of the image values.)
Skewness¶
-
name:
outSkewness
, type:
Float
, persistent:
no
¶ Skewness (measures the asymmetry of the distribution of values about the Mean value. Depending on where the tail is elongated and the mass of the distribution is concentrated, this value can be positive or negative.)
Kurtosis¶
-
name:
outKurtosis
, type:
Float
, persistent:
no
¶ Kurtosis (measure of the ‘peakedness’ of the distribution of values. A higher kurtosis implies that the mass of the distribution is concentrated towards the tail(s) rather than towards the mean. A lower kurtosis implies the reverse: that the mass of the distribution is concentrated towards a spike near the mean value.)