If you extract a thin surface from the volume (for example, using Probe model with volume module) then your signal to noise ratio will hugely decrease, because only a small fraction of voxels are sampled and if the surface extraction method has any imperfections then you might not even work with the most informative voxels. Instead, you can extract a thick slice around the papyrus sheet (unwrap the volume not a surface) thereby preserving all information that the image contains. You then may not even need much post-processing, because with the right transfer functions volume rendering may clearly show the ink.
3D Slicer is fully python scriptable, and most of newly added modules are implemented in Python. You can also pip install any Python package and use it in your Slicer modules. It should be easier to get started with Slicer than with napari, as you get a fully configured Python environment and GUI application in one, including Python console, slice and 3D views, and rich GUI. I would recommend napari if you work with 2D or 2.5D microscopy images, but for 3D images Slicer offers much more.