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Description
Is your feature request related to a problem? Please describe.
There are currently two ways to store 2.5D data (points, images, labels) in a SpatialData object (as far as I can tell):
- Option 1. one 3D Element (e.g., image with XYZ axes and points with XYZ coordinates)
- Option 2. multiple 2D Elements (e.g., image with XY axes and points with XY coordinates)
Which of these options should be preferred/suggested? What are the limitations?
There are different limitations in each of these cases.
- Limitation of Option 1: Distinguishing 2.5D vs. 3D semantics. For a downstream application such as Vitessce, if a user points to a 3D image, should this be visualized as a volume? or as 2D slices in 3D space? It can be challenging to distinguish if they are stored on-disk in the same manner in both cases (2.5D and 3D).
- One solution here is to check whether the Z-dimension contains a transform, such as scale+translate, which can help a downstream application to infer that it is the 2.5D case.
- Limitation of Option 1: Downsampling along Z dimension. Z-axis is currently treated the same way as X/Y axes when downsampling (Option to delay scale_factors downsampling along Z dimension for 3D images #954)
- Solution 1: Support
delay_z_scaling(or similar) option Add delayed Z-dimension scaling option for 3D image multiscales #955 - Solution 2: Downstream libraries can do better to anticipate this Support downsampled Z (/T/C) hms-dbmi/viv#901
- Solution 1: Support
- Limitation of Option 2: Could make it much more difficult to perform 3D operations or render in 3D if needed.
- Limitation of Option 2: No way to specify a Z-dimension transform if the Spatial Element lacks a Z dimension.
- One solution here would be to store the 2D data as 3D data with a Z-dimension of size
1. Once the data has a Z dimension, transform parameters for this axis can be specified incoordinateTransformations
- One solution here would be to store the 2D data as 3D data with a Z-dimension of size
- Limitation of Option 2: Challenging to infer which 2D Spatial Elements are slices/members of the same 2.5D dataset/group.
- Solution 1: Use a naming convention, like
images/image_slice_0,images/image_slice_1, etc. - Solution 2: If all Elements can be mapped into the same coordinate system, check whether their positions in this target coordinate system would result in being 2.5D slices
- Solution 3: (If it is known that a SpatialData object stores a 2.5D dataset) assume one SpatialData object only contains 2.5D slices from a single 2.5D dataset.
- Solution 1: Use a naming convention, like
Describe the solution you'd like
- Document recommended way to store 2.5D data in a SpatialData object.
Describe alternatives you've considered
- Do nothing differently, assume 2.5D data will be stored as 3D. Downstream tools such as Vitessce should always allow rendering 2D slices of a 3D volume, and vice-versa. Perhaps I am overthinking this.
- Add
Image2DSlicesModel,Labels2DSlicesModel,Points2DSlicesModel, etc. so that semantics are more clear upon creation of Spatial Elements. Downstream tools should use metadata produced by these Model classes to distinguish 2.5D from 3D.
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