# Images in physical space in Python

**URL:** https://discourse.itk.org/t/images-in-physical-space-in-python/2124
**Category:** Engineering
**Tags:** python
**Created:** [August 5, 2019, 6:16pm UTC](https://discourse.itk.org/t/images-in-physical-space-in-python/2124 "2019-08-05T18:16:33Z")
**Posts on this page:** 1
**Showing post:** 25

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### Author: ![matt.mccormick](https://discourse.itk.org/user_avatar/discourse.itk.org/matt.mccormick/32/7_2.png) [@matt.mccormick](https://discourse.itk.org/u/matt.mccormick)
#### Post date: [August 15, 2019, 2:34am UTC](https://discourse.itk.org/t/images-in-physical-space-in-python/2124/25 "2019-08-15T02:34:08Z")

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> [@blowekamp](#):
>
> There was a [recent discussion](https://discourse.itk.org/t/making-a-3d-sequence-from-4d-volume/2070) of how to handle time. Similarly there are a couple different ways to order color. i.e. CXYZ, XYZTC etc.

> [@blowekamp](#):
>
> There is also the definition and order of an “index”. We mean `(i,j,k)` where i is the fasted changing index, but then `ndarrays` are indexed via `[k,j,i]` .

It is reasonable to apply [the conventions of scikit-image](https://scikit-image.org/docs/stable/user_guide/numpy_images.html) for indexing, space, channel, and time order. These are compatible with how data is natively organized in ITK and NumPy array interfaces to `itk.Image`. That is, `[k,j,i]` indexing,

 ![image](https://discourse.itk.org/uploads/default/original/1X/d92f5c499f7b942608d4d5c64226d00fa0624484.png)

 ![image](https://discourse.itk.org/uploads/default/original/1X/7306c5363ac8f9c3930f63513cdfa1c07462f07b.png)

> [@blowekamp](#):
>
> I expect others from different domains will have additional concerns and comments to improve the specification too.

We can add documentation to a repository and use pull requests and line-based comments for additional discussion.

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