# Optimal C-arm angulation along a plane from CT

**URL:** <https://discourse.slicer.org/t/optimal-c-arm-angulation-along-a-plane-from-ct/37200>\
**Category:** Support\
**Tags:** dicom\
**Created:** [July 4, 2024, 6:50pm UTC](https://discourse.slicer.org/t/optimal-c-arm-angulation-along-a-plane-from-ct/37200 "2024-07-04T18:50:34Z")\
**Posts on this page:** 1\
**Showing post:** 9

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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:** [July 16, 2024, 4:18pm UTC](https://discourse.slicer.org/t/optimal-c-arm-angulation-along-a-plane-from-ct/37200/9 "2024-07-16T16:18:09Z")

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> [@Miguel\_Nobre\_Menezes](#):
>
> I did the current angulation projection on purpose - I did have one at first like you suggested, but the way the module works is precisely replicating what we use in clinical practice for TAVI

I suggest implementing exactly what is shown in the paper you linked to. What is missing in the current implementation is the automatic physical spin of the detector (and 90/180 degrees image rotation in software) as you rotate the C-arm. The projection curve does not specify the detector spin. The spin is computed from simple rules that help the clinician orient himself, by aligning directions on screen with anatomical directions. For head first supine position the commonly used rules are:

- align screen up with patient superior direction
- align screen right with patient left direction (except near lateral images, in that case with patient anterior direction)

> [@Miguel\_Nobre\_Menezes](#):
>
> I’m not aware of any software that does this

Commercial software are generally a couple of years behind. This will be avaialable on most commercial software within a few years.

> [@Miguel\_Nobre\_Menezes](#):
>
> I have experimented with the MONAI and Total Segmentator. They’re very impressive, but even on a MacBook M3 Max with 64 Gb of RAM (what I’m running) seems pretty slow, as it takes a couple of minutes running the inference. Don’t know if that’s to be expected or not.

Apple’s AI support is still limited. Pytorch (the toolkit used by most medical image computing AI), is gradually getting some hardware accelaration features on Apple, but it is still quite slow. On CPU or Apple graphics hardware segmentation may take several minutes, so what you experienced is the expected behavior.

If you need speed then you can use a desktop computer with a strong NVIDIA GPU. Currently, the [Cardiac TS2 model runs in 20-25 seconds on an NVIDIA GPU](https://github.com/lassoan/SlicerMONAIAuto3DSeg/releases/tag/ModelsTestResults).

Even if processing takes a few minutes, it should be generally acceptable, because fully automatic processing does not take any time of the clinician. You could even configure a workflow in your hospital to automatically process the CT image right after it is acquired.

> [@Miguel\_Nobre\_Menezes](#):
>
> If they’re happy with it, I think it may make sense to either integrate it with a existing extension

Sounds great! By then hopefully the SlicerHeart cathlab simulator will be released, too, so your module could use/extend features provided by the simulator or features from your module could be integrated into the simulator.

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