Working with a dataset with different volumes

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Problem summary

I am working with BraTS 2021 dataset and I am not using patch-based training. The issue appears because I am feeding the model with volumes that have different heights and widths.

One solution is to use Resize. However, it causes deformation.

I tried using Resample to resample all the volumes in the dataset to one reference space. However, when plotting the results after resampling, it seems that the resampled volumes are also deformed.

given the code below,

Q1: did I do something wrong? Q2: is there a more robust way for unifying the height and width for all volumes?

PS: in the given code, I used two volumes with the same height and width to study the effect on the resulting shape.

Code for reproduction

import torchio as tio
import matplotlib.pyplot as plt

train_dir = "path" 
train_set = tio.datasets.RSNAMICCAI(train_dir, train=True)

# size of volume0 is (1, 512, 512, 400) and volume1 is (1, 512, 512, 129)

resample_transform = tio.Resample((train_set[1]['FLAIR'].spatial_shape, train_set[1]['FLAIR'].affine))
transformed = resample_transform(train_set[0]['FLAIR'])

# size after resampling is (1, 512, 512, 129) for both volumes as expected 

plt.figure("Before resampling")
plt.imshow(train_set[0]['FLAIR'].data[0, :, :, 200], aspect="auto")
plt.show()

plt.figure("After resampling")
plt.imshow(transformed.data[0, :, :, 65], aspect="auto")
plt.show()


# the slices are completely deformed

Actual outcome

the resampled slices are deformed

Error messages

No response

Expected outcome

I was expecting the the resampled volumes to have the same spatial structure but with lower resolution.

System info

No response

[romainVala]

I can not be sure, because I do not have the data, (strange, I just get the BraTS2021_Training_Data.tar with 1251 subject, but they are all at the same size, so I guess we do not have the same data …)

But from the dimension your first volume has 400 slices, you reslice it to 129 slices, so it makes sense that the z projection is changed … (but there is no deformation of the volume)

I advise you save the volume after resample (transformed.FLAIR.save(‘xx.nii’) ) and visualize it in a 3D viewer (itksnap, 3D slicer, fslview, mrview …) you will better understand what the resample do

[Ahmed93Saber]

I will try that. Thanks a lot for the support.