SubImageStatistics¶
-
MLModule
¶ genre Statistics
author MeVis Medical Solutions AG
package MeVisLab/Standard
dll MLMiscModules
definition MLMiscModules.def see also ImageStatistics
keywords average
,mean
,absolute
,standard
,deviation
,minimum
,maximum
,weight
,interval
,voxels
,count
Purpose¶
The module SubImageStatistics
computes some statistics of the input image voxels.
Statistics are calculated along the dimensions the user selected. Default is computation along the X, Y, and Z axis. The results are returned in the output image where the first dimension along which statistics were computed contains the various statistical values, all other reduced dimensions are one and the remaining dimensions are unchanged. Which values are returned can be controlled through the emit… fields.
A subset of voxels can be selected by providing an interval of gray values. Voxels with values outside this interval are ignored if this feature is activated.
A subset can also be defined by providing a mask image at the second input to this module. Voxels will only be considered if the mask image at this place contains a non-zero value (if the image has an integer type) or greater than zero (if the image has a floating point type).
It is also possible to use multiple region in one mask image, by giving each region its own value in the mask. The statistics will be gathered per region if Use Mask Id
is set to true. The maximum number of regions should be specified by the Max Mask Ids
field (if it is set to 1, only the first region is output, if it is set to 2, the first two region statistics are output, etc).
The mask does not need to have the same size as the data image, everything outside the mask image area is treated as if the mask was zero. But a special handling occurs if the mask has size one in any direction: In this case, the mask is replicated along these axes to infinity.
If you do not want this behavior, bring the mask image size to the data image size with an SubImage
module before connecting it to SubImageStatistics
(or at least to size 2 in the affected dimension).
There is a read-only field that indicates if a valid image mask is connected to the second input. If this field is unchecked, the mask is not considered even if an image is connected (e.g., because it is invalid).
If both an mask image and a gray value interval is specified, both are combined, i.e., only voxels where the mask is set and whose gray values lie inside the interval are considered.
Parameter Fields¶
Field Index¶
Auto apply : Bool |
Fold T axis : Bool |
Minimum Voxel Value : Double |
Auto update : Bool |
Fold U axis : Bool |
Only consider voxels in interval : Bool |
Emit average : Bool |
Fold X axis : Bool |
outputIsValid : Bool |
Emit maximum : Bool |
Fold Y axis : Bool |
Update : Trigger |
Emit minimum : Bool |
Fold Z axis : Bool |
Use Mask Id : Bool |
Emit std.dev. : Bool |
Mask image is valid and used : Bool |
|
Emit voxel count : Bool |
Max Mask Ids : Integer |
|
Fold C axis : Bool |
Maximum Voxel Value : Double |
Visible Fields¶
Only consider voxels in interval¶
-
name:
useInterval
, type:
Bool
, default:
FALSE
¶ If checked, only voxel with a value in the interval specified by
Minimum Voxel Value
andMaximum Voxel Value
are investigated.
Fold X axis¶
-
name:
foldXDim
, type:
Bool
, default:
TRUE
¶ If checked, the statistics are applied along the x-axis.
Fold Y axis¶
-
name:
foldYDim
, type:
Bool
, default:
TRUE
¶ If checked, the statistics are applied along the y-axis.
Fold Z axis¶
-
name:
foldZDim
, type:
Bool
, default:
TRUE
¶ If checked, the statistics are applied along the z-axis.
Fold C axis¶
-
name:
foldCDim
, type:
Bool
, default:
FALSE
¶ If checked, the statistics are applied along the c-axis.
Fold T axis¶
-
name:
foldTDim
, type:
Bool
, default:
FALSE
¶ If checked, the statistics are applied along the t-axis.
Fold U axis¶
-
name:
foldUDim
, type:
Bool
, default:
FALSE
¶ If checked, the statistics are applied along the u-axis.
Emit average¶
-
name:
emitAverage
, type:
Bool
, default:
TRUE
¶ If checked, the average value is set to the first dimension of the output image.
Emit std.dev.¶
-
name:
emitStdDev
, type:
Bool
, default:
TRUE
¶ If checked, the standard deviation is set to the second dimension of the output image.
Emit minimum¶
-
name:
emitMinimum
, type:
Bool
, default:
TRUE
¶ If checked, the minimum value is set to the third dimension of the output image.
Emit maximum¶
-
name:
emitMaximum
, type:
Bool
, default:
TRUE
¶ If checked, the maximum value is set to the fourth dimension of the output image.
Emit voxel count¶
-
name:
emitCount
, type:
Bool
, default:
TRUE
¶ If checked, the number of voxels is set to the fifth dimension of the output image.
Use Mask Id¶
-
name:
useMaskId
, type:
Bool
, default:
FALSE
¶ Set this if you want statistics for each separate region in the mask. Each region has its own (non-zero) pixel value in the mask. The resulting statistics are output per region, for as many regions as are available, with a maximum of
Max Mask Ids
. IfMax Mask Ids
is larger than the number of regions, the remaining statistics are filled with zeros. The order of the output is: first all statistics of the first region, then all statistics of the second region, etc. The regions themselves are ordered based on the (numerical) value of the mask pixels, lowest pixel values first.
Max Mask Ids¶
-
name:
maxMaskIds
, type:
Integer
, default:
1
¶ Maximum number of regions for which statistics are output.
Mask image is valid and used¶
-
name:
maskIsValid
, type:
Bool
, persistent:
no
¶ Shows if the attached mask image is valid and used.