[Feature] Investigate leveraging `napari-vedo-bridge`

This issue is to track how we could make use of [`napari-vedo-bridge`](https://github.com/jo-mueller/napari-vedo-bridge), and to give some more context to [this conversation on X](https://x.com/jm_mightypirate/status/1815334303288508657).

To state the current situation:
- We provide napari plugins for a variety of computational neuroanatomy tasks (e.g. [registration](https://github.com/brainglobe/brainreg), [segmentation](https://github.com/brainglobe/brainglobe-segmentation), [cell detection](https://github.com/brainglobe/cellfinder))
- We provide a vedo-based tool for visualisation of mesh data in atlas space - [brainrender](https://github.com/brainglobe/brainrender)
- We would like to:
a) Provide a GUI for this atlas-based visualisation
b) Allow users to carry out the entire loading/preprocessing/analysis/visualisation workflow within a single environment (napari)

This repo aims to port brainrender to napari. However, there are some outstanding issues:
- napari doesn't have as many tools to visualise/manipulate meshes
- Visualisation of meshes unfortunately doesn't look as visually appealing as vedo, and this is a serious issue for publications etc
- We don't want to maintain two separate code-bases forever

[`napari-vedo-bridge`](https://github.com/jo-mueller/napari-vedo-bridge) seems like it could potentially help in a few ways:
- Allow vedo-based mesh manipulation within napari
- Possibly allow us to go from a napari canvas to a vedo plotter instance. This could allow more intuitive building of what we call a brainrender _scene_, but then export to vedo for the final visualisation
- Provide the building blocks for a common napari/vedo brainrender code-base

We should look into [`napari-vedo-bridge`](https://github.com/jo-mueller/napari-vedo-bridge) more and see how we could best leverage it.

Start by reviewing napari-vedo-bridge alongside the existing brainrender-napari project and the linked brainrender context. Determine whether it supports mesh manipulation, napari-to-vedo plotting, and a shared codebase, then record a concrete integration direction or follow-up work.

Written by the indexing model from the issue text.