How can I convert a 3D CNN model trained for Nifti images to 2d so that I can inference on 2D nifti slices?

You could either:

- create a “depth” dimension in your inputs and
`repeat`

the data`D`

times to match the expected input to the original 3D model - try to reduce the parameters from the 3D model to 2D ones

For the 2nd approach: I don’t know which approach would work at all, but e.g. you could reuse the kernels from the `nn.Conv3d`

layers, apply a `mean`

(or `sum`

or slice) in the depth dimension of the kernel and load it into a newly created `nn.Conv2d`

layer.

Depending on the actual model architecture this model “surgery” might not be trivial so the 1st approach might be easier.