Extracts a list of objects of class ImageAnnotaion.

getImageAnnotations(
  object,
  ids = NULL,
  tags = NULL,
  test = "any",
  add_barcodes = TRUE,
  strictly = FALSE,
  add_image = TRUE,
  expand = 0,
  square = FALSE,
  flatten = FALSE,
  check = FALSE
)

Arguments

object

An object of class spata2.

ids

Character vector or NULL. If character, specifies the IDs of the image annotations of interest. If numeric, the image annotations are picked by number. If NULL, all image annotations are included - subsequent selection with tags and test is possible.

tags

Character vector or NULL. If character, the tags for the image annotation selection. See section Selection of image annotation with tags for more information.

test

Character value. One of any. all, identical, not_identical and none. Specifies how input for tags is used to select image annotations. See section Selection of image annotation with tags for more information.

add_barcodes

Logical. If TRUE, barcodes of spots that fall into the area of an image annotation are identified and added to slot @misc$barcodes of the output image annotations.

strictly

Logical. If TRUE, only barcodes of spots that are strictly interior to the area of an image annotation are added to the output. If FALSE, barcodes of spots that are on the relative interior of the area or are vertices of the border are added, too.

add_image

Logical. If TRUE, the area of the histology image that is occupied by the annotated structure is added to the ImageAnnotation object in slot @image. Dimensions of the image can be adjusted with square and expand.

expand

Specifies image expansion. An image that is cropped based on an image annotation centers around the image annotation. If expand = 0, the default, the dimensions of the image, that is width/x-axis and height/y-axis, are set to include only the image annotation area and nothing more. Using expand, the cropped image section can be adjusted. See section Expansion of cropped image sections for more information.

square

Logical value. Most image annotations come in variable shapes and have different horizontal and vertical diameters. Therefore, height and width of the image section are usually not equal. If square = TRUE, the cropped section of the image that contains the annotated structure is forced into a square: the bigger diameter of both is taken as default. E.g. if the horizontal diameter of the image annotation is 1mm and the vertical diameter is 1.5mm, the output image will have height and width of 1.5mm. That is, in terms of coordinates, an x-range and a y-range of 1.5mm.

Processing of the image output depending on argument expand happens afterwards.

Value

A list of objects of class ImageAnnotation.

Note

To test how the extracted image section looks like depending on input for argument square and expand use plotImageAnnotations(..., encircle = FALSE).

Expansion of cropped image sections

The argument expand is a versatile way, to specify how a cropped image section is extracted. If you want the cropped image as is, specify expand = 0. Else, there are multiple options. In general, expand takes three kinds of values, namely percentages, distances and distance exclamations.

  • Percentage: A string suffixed with %. E.g. expand = '50%' adds 50% of the distance from the center to the border of the image annotation to the image frame.

  • Distance measures: In pixel or European units of length. E.g. expand = list(x = '1mm') expands the x-axis on both sides with 1mm. expand = list(x = c('0.5mm', 1.5mm') expands the x-axis on the left side with 0.5mm and on the right side with 1.5mm.

  • Exclam distance measures: Distance measure with an exclamation mark suffix. E.g. expand = '1mm!' centers the image and forces an axis length of 1 millimeter. (Example 5)

Depending on how the values are specified different parts of the image can be expanded.

Single values, like expand = 50, are recycled: Every end of each image axis is expanded by 50 pixel. (Example 2)

Vectors of length two, like expand = c('1mm', '2mm'), are recycled: The beginning of each axis is expanded by 1 millimeter. The end of each axis is expanded by 2mm. (Example 3)

Named lists can be more precise. expand = list(x = c('1mm', '0.5mm'), y = c('0.25mm', '1mm')). Applies the vectors to expand the corresponding axis. (Example 4)

Using exclam input the side of the axis must not be specified as the axis is fixed as a whole. E.g expand = list(x = '1mm!', y = '2mm!') results in the same output as expand = list(x = c('1mm!', '1mm!'), y = c('2mm!', '2mm!').

Selection of image annotations with tags

Input for argument tags specifies the tags of interest. Argument test decides about how the specified tags are used to select the image annotations of interest. There are multiple options:

  1. Argument test set to 'any' or 1: To be included, an image annotation must be tagged with at least one of the input tags.

  2. Argument test set to 'all' or 2: To be included, an image annotation must be tagged with all of the input tags. Can contain tags that are not specified.

  3. Argument test set to 'identical' or 3: To be included, an image annotation must be tagged with all of the input tags. Can not be tagged with anything else.

  4. Argument test set to not_identical or 4: To be included, an image annotation must not be tagged with the combination of input tags.

  5. Argument test set to 'none' or 5: To be included, an image annotation must not contain any of the input tags.

Note that the filtering process happens after the filtering by input for argument ids. You can first select a group of image annotations by naming their IDs and then select among them via tags and test. If ids is NULL, you select among all image annotations via tags and test. And if tags is also NULL, the function uses all image annoations.