Measurement
2D
3D
Note
Measurement nodes rely on the measurement features closely described here: Measurement Features.
All measurements include frame metadata to be able to include time filename from the same node.
Object measurement includes all features from frame measurement, eliminating the need to add a separate field measurement node to obtain data such as the measured area.
Select the measurement feature from the Add Feature list. Click on it when you see the + symbol next to its name. It is added to the right list showing all measured features. Use the down arrow next to the feature to further specify the measurement.
If a feature displays the channels selection bar
, first select on which channel the measurement will be done (green channel is selected in our example) and then 
add the feature. The channel can be changed later by clicking on the Change channels button next to the = icon.Adjust the name of the feature in the Custom Name column. This name is then passed in the Analysis Results table.
Set the resulting Format and the number of decimal units (dec).
Child is inside the parent - all child pixels are in the parent.
Child is intersecting with the parent - they have at least one common pixel.
Child nearest parent - closest parent measured border to border.
For the count feature the presence in a compartment is defined by the position of the center pixel.
For the area and intensity features the intersection of spots and a compartment is used.
Node input/output overview for all Basic nodes.
Table 26.
| Measurement node | Input | Output |
| Field | Channel, Mast? | Row per field |
| Object | Binary, Channel* | Row per object |
| Object Count | Binary+, Channel* | Row per field |
| Parent | Parent, Child, Channel* | Row per parent object |
| Children | Parent, Child, Channel* | Row per child object |
| Cell | Cells, Nuclei, Spots?, Channel* | Row cell |
where:
? ... optional,
+ ... at least one,
* ... zero or more.
In order to reduce the number of nodes required for a recipe all nodes include features from more generic measurements. These are repeated in every row if needed. For example:
The Field node measures the intensity features in the whole image field. The output is a table where every row corresponds to one field.
Optionally, a binary input (a mask) can be connected in order to reduce the measured area. Only the pixels under the mask are measured.
Figure 882. Field node.
All Basic measurement nodes are set in a similar way with variations in the list of measurement features depending on the node type and their dimension (2D/3D).
The 
Calculator (Calculated Column) feature is different than the other features as it displays a scientific calculator at the bottom with buttons for arithmetical operations, allowing the calculation of a new column using already inserted features (click on the 
icon to insert a feature into the formula).
Measurement of some features can be further specified in their Aggregation drop-down menu. Order of a feature can be changed by clicking and dragging the feature to a different row position in the list. To hide the selected feature in the Records table, click on the 
icon. To delete a feature, click on the 
icon. To remove all features in the list, click Remove all.
ObjectId and ObjectEntity are shown in the Analysis Results as {BinaryLayerName}Id and {BinaryLayerName}Entity. Naming the binary layers as Cell, Nuclei, Parent, etc., so that the columns are named CellId, CellEntity, NucleiId, etc., enhances the clarity for the user. Generally one row record is created per cell. Some nodes generate a varying number of rows compared to a classic measurement (e.g. a histogram produces one row for each pixel value or bin). Loop indexes are dependent on the input file and produce multiple columns in the analysis results table if the input file has multiple loops.
Measures all features of every object. The output is a table where every row corresponds to one object.
Optional channel inputs must be connected when intensity features are measured.
Field feature as well as field and global metadata can be measured in the same node. They are repeated for every object.
Figure 883.
The description of the dialog window behavior can be found in the Measurement > Basic > Field node.
Measures object features on the whole field. The output is a table where every row corresponds to one field.
The node measures typical binary features like Object count, Area fraction as well as all other object features as aggregates (mean, sum, max, ...).
Optionally, the node can measure more binary layers at once.
Optional channel inputs must be connected when intensity features are measured.
Figure 884.
The description of the dialog window behavior can be found in the Measurement > Basic > Field node.
Measures parent and children object features. The output is a table where every row corresponds to one parent object.
Optional channel inputs must be connected when intensity features are measured.
Parent-children relationship
Every parent may “have” zero (0) or more children. There are three methods for determining childhood:
The node measures features of the parent objects as well as aggregates (mean, sum, max, ...) of the children object features. Please see the aggregation statistics table (Data manipulation > Grouping > Aggregate Rows).
Figure 885.
Note
The Parent Id is always named ObjectId in the results. One row is created per parent. Child measurement is aggregated per parent (pick the Aggregation type for each child measurement).
The description of the dialog window behavior can be found in the Measurement > Basic > Field node.
Measures parent and children object features. The output is a table where every row corresponds to one children object.
Optional channel inputs must be connected when intensity features are measured (see Parent-children relationship in Measurement > Basic > Parent).
The node measures features of both parent and children objects. The parent features are repeated for its every child. Having all children features is useful in later downstream nodes where the parent ID can be used for grouping, reduction or sorting.
Children IDs can be “measured” and used for joining with other nested children nodes.
Figure 886.
Note
The Parent Id is always named ObjectId in the results. One row is created per child. Aggregation can be done using Data manipulation > Basic > Reduce Records.
The description of the dialog window behavior can be found in the Measurement > Basic > Field node.
Measures object features of cell, nucleus and few features of the cytoplasm. The output is a table where every row corresponds to one cell and nucleus.
Optional channel inputs must be connected when intensity features are measured.
Cell must be connected to MakeCell node which ensures that every cell has exactly one. It also gives the same ID to every cell and its nucleus.
Cytoplasm is internally calculated as complement of the nucleus inside cell. Consequently it is hollow and may be split in more than one object (having same object ID though). Because of this it does not make sense to measure most of the object features.
Optionally Spots objects can be connected to count their presence in each compartment.
Figure 887.
Node Inputs
Layer representing cells (“Cell” output).
Layer representing nuclei (“Nucleus” output).
Layer representing “Spots” inside the nucleus or cytoplasm area.
Channel used for intensity based measured features.
The description of the dialog window behavior can be found in the Measurement > Basic > Field node.
Outputs the X and Y shift estimates (in px and µm) for the checked correction method.
Estimates the Signal to Noise Ratio (“SNR”) value present in the connected color result.
Retrieves well plate information and thumbnail using Channel A and Binaries B1, ..., Bn and stores it in the table.
Thumbnail
Defines size (in microns if calibrated) of the center portion of the frame that is cropped and rendered.
Maximum size (in pixels) is a limit to which the rendered image is stretched down if being bigger.
Labeling
List of possible labels separated by comma. Listed values are used in the “Number Of” aggregation menu (e.g. in Data manipulation > Basic > Reduce Records node).
Calculates a histogram of all pixel values in the color image. If the connected color image has multiple channels they are averaged into a single value per pixel. If a binary is connected only pixels under it are taken.
or maximum for floats by default
or 65536 for floats by defaultReports all pixel values of the color image. If the connected color image has multiple channels they are averaged into a single value per pixel. If a binary is connected only pixels under it are taken.
Fourier Ring Correlation (FRC) is a technique used to measure the actual resolution of two independent images of the same scene. This method produces a numerical value that represents the resolution, providing a precise and reliable measurement. However, obtaining two independent images of the identical scene can often be challenging. Despite this, FRC is versatile and applicable across various imaging modalities.
This node implements the paper Measuring image resolution in optical nanoscopy.
This node is a modification of the Measurement > Resolution > Image Pair FRC node so that it can be used for only one image and two images are not needed. This is based on the paper Fourier ring correlation simplifies image restoration in fluorescence microscopy. Accuracy and reliability is lower than on the Measurement > Resolution > Image Pair FRC node. It is calibrated for AX and NSPARC images. Trying other modalities is not recommended.
Calculates histogram of all pixel values for every binary object.
Please see Measurement > Field pixel values > Histogram.
Calculates histogram of all voxel values for every binary object.
Please see Measurement > Field pixel values > Histogram.
Reports all pixel values along every line. If the object is not a line the order of pixel is undefined.
Measures the smallest distance to another 2D/3D object. Please see NearestObjDist .
Calculates the distance between objects in two binary layers.
calculates distance between the centers of two objects.
Figure 888.
calculates distance between the center of one object and the closest point on the border of the other object.
Figure 889.
calculates distance between the borders of objects (minimal distance between borders). When the objects are touching, the distance is 0.
Figure 890.
(requires: General Analysis 3) (requires: Local Option)
Calculates the focus criteria (values which estimate the image sharpness) for each slice in a Z-stack and estimates the focus position. For the bright field and fluorescence criteria, the x-y region of the image is divided into 3x3 crops. The focus criterion is calculated for each crop and Z-position, and the overall results are used to estimate the focus position. The calculated focus position corresponds to the value that would be obtained during (non-AI) live auto-focusing if the camera captured the same Z-stack.
Choose the type of the focus criterion.
Output columns
Z-position of each slice.
Validity of the focus estimation. Can be either OK (the focus position was found), Small range (the focus position is out of range) or Fail (focus position couldn't be estimated).
If the result of the validity check was OK, this column contains the found focus position. If the focus was found to be out of the Z-range, it contains the Z-value at the corresponding border of the range. If the focusing failed, it contains nothing.
Focus criteria calculated across Z for the whole image.
Focus criteria calculated across Z for each crop. Crops #1 - #3, #4 - #6 and #7 - #9 correspond, respectively, to the top, middle and bottom of the image.
If the result is OK, this column contains the focus criteria calculated across Z for the crop which had the most impact on the Z-position. Otherwise, this column is empty.
Calculates histogram of all voxel values. If the connected color volume has multiple channels they are averaged into a single value per voxel. If a binary is connected only pixels under it are taken.
Please see Measurement > Field pixel values > Histogram.