Resize transform produces aliasing artifacts

[lemairecarl]

Describe the bug
The Resize transform produces aliasing artifacts. It uses the F.interpolate function from PyTorch, which has an antialiasing option, but that does not support 3D downsampling of volumes (5D tensors). The Resize transforms does not use the antialiasing option at all:

MONAI/monai/transforms/spatial/array.py

Line 676 in a676e38

resized = torch.nn.functional.interpolate(

This line in PyTorch source code confirms that the antialiasing option is not available for 3D volumes (trilinear interpolation):
https://github.com/pytorch/pytorch/blob/8ed6cb42ba2635319b67417b9ee2f1a0142d2c25/torch/nn/functional.py#L3851

The issue of ignoring aliasing in deep learning research is covered in this paper: https://arxiv.org/abs/2104.11222

To Reproduce
Steps to reproduce the behavior:

1. Resize an image or volume down to a small size, e.g. using a factor of 8
2. Observe the aliasing artifacts in the resized tensor

Expected behavior
The downsampled image should look like a smaller version of the original (no aliasing).

[Nic-Ma]

Hi @lemairecarl ,

Thanks for your finding and feedback!
@wyli , I think maybe it's necessary to add the antialias arg to Resize, Zoom, RandZoom transforms based on:
https://github.com/pytorch/pytorch/blob/v1.11.0/torch/nn/functional.py#L3780
What do you think?

Thanks.

[wyli]

Yes there's also a related p1 milestone but I don't have the bandwidth to implement it https://github.com/Project-MONAI/MONAI/milestone/44

[Nic-Ma]

Hi @wyli ,

OK, as you and @yiheng-wang-nv are busy with other bugs, let me self-assign this ticket later.

Thanks.

[lemairecarl]

Hi, thanks for taking this seriously.

I see that you added this to the "label downsampling with antialiasing" milestone. Maybe you should rename the milestone as just "downsampling with antialiasing" ?

[dongyang0122]

hi @lemairecarl, thanks for reporting the issue! Do you have sampling images (before and after the down-sampling) showing the undesired artifacts? That would be helpful for us to understand and resolve the issue.

[wyli]

hi @lemairecarl, thanks for reporting the issue! Do you have sampling images (before and after the down-sampling) showing the undesired artifacts? That would be helpful for us to understand and resolve the issue.

Hi @dongyang0122 the appendix section 6.4 figure 12 of the paper is a good demo https://arxiv.org/pdf/2104.11222.pdf