# Merge CT volume node with a model node in python

**URL:** https://discourse.slicer.org/t/merge-ct-volume-node-with-a-model-node-in-python/9457
**Category:** Development
**Created:** [December 10, 2019, 4:17am UTC](https://discourse.slicer.org/t/merge-ct-volume-node-with-a-model-node-in-python/9457 "2019-12-10T04:17:08Z")
**Posts on this page:** 1
**Showing post:** 6

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### Author: ![lassoan](https://sea2.discourse-cdn.com/flex002/user_avatar/discourse.slicer.org/lassoan/32/13_2.png) [@lassoan](https://discourse.slicer.org/u/lassoan)
#### Post date: [December 18, 2019, 1:25am UTC](https://discourse.slicer.org/t/merge-ct-volume-node-with-a-model-node-in-python/9457/6 "2019-12-18T01:25:20Z")

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> [@talmazov](#):
>
> I’m working on an extension that builds around panoramic reconstruction which essentially straightens a volume: [Slice rotation in viewport when using SetSliceToRASByNTP in python](https://discourse.slicer.org/t/slice-rotation-in-viewport-when-using-setslicetorasbyntp-in-python/7191/2)  
> but i also want this reconstruction to incorporate mesh models so im trying to merge volumes - im not sure if this is the correct approach to this.

OK, this explains everything.

You can create 3D panoramic reconstructions using this recently added module: [How to implement CPR (curved planar reconstruction) from centerline? - #3 by lassoan](https://discourse.slicer.org/t/how-to-implement-cpr-curved-plannar-reconstruction-from-centerline/9456/3)

To display models in the same way, you can import the model to segmentation node, from there export as a labelmap volume node, and then apply curved planar reconstruction to the labelmap volume.

An alternative approach would be to create a grid transform from the transformed corner points of the slices, but this would require a little bit of Python scripting. This method would be particularly useful for transforming sparse point sets (landmark points, lines, curves), which cannot be well represented by image volumes. It would be nice if you could work on this we can help you to get started.

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