Conv3D model 输入张量

Question

I am new to PyTorch and I want to make a classifier for 3D DICOM MRIs. I want to use the pretrained resnet18 from monai library but I am confused with the input dimensions of the tensor. The shape of the images in my dataloader is [2,160,256,256] where 2 is the batch_size, 160 is the number of dicom images for each patient and 256x256 is the dimension of the images. When I try to run the model I get this error: Expected 5-dimensional input for 5-dimensional weight [64, 3, 7, 7, 7], but got 4-dimensional input of size [2, 160, 256, 256] instead

If I unsqueeze the tensor before feeding it to the model I get: Given groups=1, weight of size [64, 3, 7, 7, 7], expected input[1, 2, 160, 256, 256] to have 3 channels, but got 2 channels instead Can anybody help me figure this out?

Answer 1

you need to add the channel dimension for each slice (which is one for MRIs). Eg your input should be of shape (2,1,160,256,256)