Add support for 5ttgen deep_atropos to enable 5TT image generation with ANTsPyNet Atropos segmentation

[LucSam]

This PR introduces a new option to the 5ttgen script: 5ttgen deep_atropos.

Summary of Changes:

A new script: lib/mrtrix3/_5ttgen/deep_atropos.py.
This option leverages ANTsPyNet’s antspynet.deep_atropos for tissue segmentation, addressing challenges with lesion-affected T1-weighted images.
Tissue intensity mappings in the generated deep_atropos.nii.gz are as follows:
1 = CSF
2 = GM
3 = WM
4 = SCGM
5 = Brainstem (BS)
6 = Cerebellum (CER)
Brainstem (BS) and Cerebellum (CER) are treated as white matter (WM) to align with the nature of the segmentation results.
Why This Is Useful:

Lesion-affected brain images often produce poor results with existing 5ttgen options such as:

5ttgen fsl
5ttgen freesurfer
5ttgen hsvs
These methods can fail to correctly segment grey matter (GM) due to lesion intensity changes, resulting in incorrect tissue assignments.
The deep_atropos option provides a robust alternative for T1 images in such cases.

Testing and Feedback:
The changes have been tested, but further validation and review by others would be highly appreciated to confirm reliability across various datasets.

[Lestropie]

Hi Lucius,

As per contributing guidelines, the change will need to be proposed as an addition to the dev branch rather than master. It looks like the commit you have generated also erroneously includes deletion of a whole lot of unrelated files, which will need to be rectified. Rather than trying to rescue this PR, you are likely better off making a fresh feature branch off of the current dev branch, manually adding just that one file in a new commit, and then creating a new PR with dev as the target branch.

There's been some structural and syntax Python changes on dev, so see how you go getting your code working there. If you get stuck, just commit what you've got and create a PR, and I can help from there.

Cheers
Rob