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Compound ROIs

A ROI may consist of multiple shapes combined in different ways. The result is also a shape.

Set primitives

Shapes may combined using set operators:

  • union
  • intersection
  • difference
  • symmetric difference

The shape is the result of the set operation.


Restrict to combinations of 2D or 3D shapes only?


J-M Burel Union in the mathematical sense or aggregation.


A simple collection of shapes. There is no implied relationship unless used with the set operators.


Name Type Description
S1 ShapeID Shape
R1 RepID Representation
NSHAPE Count Number of shapes
SHAPE1 Shape First shape
Shape Further shapes
SHAPEn Shape Last shape


Produce the union of the shapes in the provided set.


Name Type Description
S1 ShapeID Shape
R1 RepID Representation
SET Set* Set of shapes


Produce the intersection of the shapes in the provided set.


Name Type Description
S1 ShapeID Shape
R1 RepID Representation
SET Set* Set of shapes


Produce the set difference of the shapes in the provided set.


Name Type Description
S1 ShapeID Shape
R1 RepID Representation
SET Set* Set of shapes

Symmetric difference

Produce the symmetric difference of the shapes in the provided set.


Name Type Description
S1 ShapeID Shape
R1 RepID Representation
SET Set* Set of shapes
  • Restrict to either 2D or 3D, but not both?

How do we detect if shapes intersect? Edge cases for set operations using masks-false positives for partially occupied pixels.

Event/Events: A simple list of points.
The point size/style/colour may be changed to permit different sets to be distinguished.
Caliper/Distance/Multi-Caliper/Multi-Distance. These are all the same
measurement(s), a baseline followed by a list of points. The measurement is the distance from each point to the baseline. The differences between the types are solely the visual presentation of the measurements.
Angle3/Angle4. These measure the angle between two lines. Angle4 is
two separate lines, while Angle3 is two lines with a common point (i.e. a special case of Angle4). Angle3 could be represented with a three-point polyline. Angle4 would need to be two separate lines. Given that Angle3 is a special case of Angle4, it is not clear that it should be represented as a polyline.

Circle. While the OME model represents this as an ellipse with equal x and y radii, there are three ways to represent a circle here: - radius defined as a line from centre to edge - radius defined as a line from edge to centre (stored as the first type with the point order reversed) - circumference defined using three points. The first two are representable in the model as an ellipse plus a line. The latter is representable as an ellipse plus three points.

Polyline is directly translatable.

Aligned Rectangle is directly translatable as a rectangle (with some trivial differences in coordinates). However, additional tags define metadata to display inside the rectangle (optional) such as channel/slide/acquisition time/exposure time/etc. The verbatim text can be put into a Label, but the specific meaning would be lost–this is an overlay which would change as you navigate through a stack or timecourse etc, varying with the plane-specific parameters. While the specific tags would be retained, a more generic means to overlay image- and plane-specific OME metadata might be generally useful within the context of the OME model.

Ellipse is directly translatable.

Outline/closed polyline is directly translatable.

Text is convertible to Label. However, the OME Label type lacks the alignment attributes mentioned in my earlier mail. This makes it difficult to control the placement of text in complex compound ROIs.

Length is a single line distance measurement line like, but with additional end lines to make it like a technical drawing line outside the object itself, i.e.

|                   |
        50 µm

Representable in the model as a simple line, across OBJECT, but with loss of the other lines. It is representable as three separate lines, but with loss of the context of the specific measurement.

Open and closed splines: these are probably natural splines (not Bezier). ZVI currently stores them as polylines given that we don’t support splines. But having a spline type would permit them to be stored.

LUT and Profile: Covered in previous mail.

Storing and manipulating complex compound objects

With these measurements, one thing perhaps worth considering is that there are up to four types of object here:

  1. Result context: the object(s) representing the physical measurement. This is what we currently store in the model.
  2. Measurement context: line along radius of circle, points along circumference of circle etc. This is “how the measurement was made”
  3. Visual context: such as visual cues such as construction lines. This is the visual presentation of the measurement to the viewer.
  4. Editing context: values which control the placement of the above. Information for generation of UI manipulation handles, and of the other contexts while editing.

We can represent the actual measurements in most cases using the existing ROI types. However, if we store the additional types, it is no longer possible to distinguish between the measurement and the additional context.

If it was possible to distinguish between these in the model, it would be possible for the objects to be displayed without any advanced knowledge of how an object should be edited. It would also be possible to extract the primitive measurement values. However, the measurement context would provide additional information to editors for manipulation of the object, which would then be able to update all three contexts appropriately.

Doing this would provide a simple but effective means for additional ROI types to be added without requiring support in all programs displaying/modifying ROIs. This does not of course replace the need for namespaces to identify ROI categories, but it does supplement it by allowing programs to selectively display different contexts without any knowledge of the underlying type.

As an example, using this length measurement:

|                   |
        50 µm
  1. Result context

(where the #s are the start and end points of a Line at either end
of the object.  This is the value of the physical measurement.)
  1. Measurement context

    No additional information needed in this case.

  2. Visual context

 |                   |
 |                   |
         50 µm

Three lines, one with arrow end markers, plus text label.
This is the visual representation of the measurement.
  1. Editing context

(where the #s represent a distance between the measured line and
the drawn line in the visual context.  This information is used to
generate the visual context from the measurement context.)

I hope the above does not sound too way out. But the current system is limited to storing only the first of these four contexts, which loses information. While it is possible to delegate all of the presentation and editing to the viewer, the reality is that this is stuff people want. If I’m annotating an image for a paper, I want the annotations to appear exactly the same as I see them if I send them to someone else. And if I’m doing physical measurements, I want the specifics of how I made the measurement to be recorded. All we are doing here is providing additional information to the viewer/editor that it is free to use and/or ignore as it chooses.

Thinking about this a little more, in many cases it will be possible to omit some contexts and infer them from the others. For example, if I have a simple line I will store a line in the result context. The measurement context is the same two points, and so we may simply use the result context points in its place. Likewise, if the measurement is a simple one, the visual context may be omitted and inferred from the result context also. The different contexts really only come into play when we want a more sophisticated visual representation (for example with overlaid textual representations of the measurement value or to visualise the measurement in a more complex manner than the result context alone can provide). And they are essential when using more complex compound ROIs as the last example attached shows.

In the last example, all the information is provided to allow the user to edit the object in a UI. For example, they can adjust the end points of the baseline, and the start points of the lines in the measurement context can be retriangulated from the end points and baseline. The measurement context can be inferred from the endpoints of the lines in the result context. And the endpoints can also be adjusted independently. Following any adjustment, the updated baseline can be stored in the editing context, the measurement lines in the measurement context, and the visual representation in the visual context. The visual context is shown here to include end markers on the distance lines, and text labels with the measured values. But these could be toggled on or off and the settings stored in an annotation specific for this measurement type–there’s really no limit to the “extra stuff” you can add here, but the basic measurement remains the same in the result context.

(In this example, the baseline could actually be in the measurement context, since it’s part of the measurement; the first example is a better illustration of the editing context.)

The important point is that anyone should be able to open the file and display the visual representation without any knowledge of the specifics of the ROI type or measurements being made. Likewise they can also look at the measured distances in the results context and use them without any knowledge of how they were measured. Only a UI which supports the ROI type in question will need to use the editing and/or measurements context, and they will know how to regenerate the other contexts when editing.

Compound types

Line Profile LUT Scale bar

LUT/gradient boxes are quite specialist. However, they are also quite common in published figures, so it would make sense to have a general implementation. These are particularly useful when you have false colour heat maps where you need a visual scale to interpret the figure. We already support LUTs, so this is really just a view of the LUT for a given channel inside a rectangle.

Line profiles are quite common. But I guess supporting this would depend upon whether you classify the profile as the result of analysis of a ROI, or part of a ROI. It might be handy to be able to overlay a line profile as a set of coloured polylines, for example.

Zeiss AxioVision ROI types

For the Zeiss types, we can represent these in the model using:

Zeiss type ROI model type
Event Point2D
Events Point2D (union of points)
Line Line2D
Caliper Line2D (union of lines)
Multiple caliper Line2D (union of lines)
Distance Line2D (union of lines)
Multiple distance Line2D (union of lines)
Angle3 Line2D and Arc2D
Angle4 Line2D and Arc2D
Circle Circle2D and Line2D
Scale Bar Line2D (with end markers)
Polyline [open] Polyline2D
Aligned Rectangle AlignedRectangle2D
Rotated Rectangle Rectangle2D
Ellipse AlignedEllipse2D
Polyline [closed] Polygon2D
Text Label2D
Length Line2D (union of lines)
Spline [open] PolylineSpline2D
Spline [closed] PolygonSpline2D
LUT AlignedRectangle2D and Label2D
Line profile Line2D and Polyline2D/Rectangle2D

Annotations don’t typically have labels (with the exception of scale bars). Measurements would have one or more labels in the union as well displaying the value(s) of the measurement.