Nvidia GeForce setting (and relative 3d Slicer setting)

Good morning everyone, I am a young researcher and I have recently started to use 3D slicer for fossil vertebrate reconstruction.

I use the following main functions:

  • automatic and manual segmentation
  • ISLAND extension for model cleaning
  • WRAP SOLIDIFY extension for volume filling of the brain cavity.

regarding the starting CT images, I have been using both low resolution images and microCTs that are extremely heavy to process.
Because of this, I found that the software allows a choice of processing tool: i.e. CPU, GPU, multicore.
I realized that the rendering processing of the 3D model is done through the use of CPU and RAM; instead, I think it is more convenient to use GPU and dedicated card given the following features of the workstation:
Processor → Intel core i9 14900KF 3.2GHz
Ram → 128Gb
video card → Nvidia GeForce 4090 RTX

I am asking if in addition to the setting shown in the image, there are other types of settings to maximize the power of the machine.
also I would like to understand if the video card settings themselves can be maximized for slicer use.
I remain available for any clarification. Thank you.

This setting only has an effect on volume rendering. Most algorithms in Slicer run on the CPU, some on the GPU (like some AI-based segmentations), however Slicer does not have a setting that influences it. Slicer is a research platform, so performance has not been a priority. Contributions to parallelise algorithms are, however, always welcome. A few years ago there was an effort to run some Segment Editor effects on teh GPU, but it was never integrated.

Make sure you are using GPU Raycasting as default (you have a good video card), and the default quality is set to Normal (the setting below default rendering method), not Adaptive.

Also if your computer has a integrated GPU, make sure windows is configured to use your Nvidia RTX gpu for Slicer. You can search the forum and internet for that.

These should take care of your rendering speed issues. Other slowdowns might be related to data size, processing pipeline and some other settings.