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xmengli / H-DenseUNet

TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
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question about testing scheme #11

Closed Wang-Shuo closed 5 years ago

Wang-Shuo commented 5 years ago

Hi. Thanks for your code. The test.py script is for H-DenseUNet. In that script, it seems that you slide a box sized 1x512x512x8x1 along the z-axis to make the prediction. the step size is 2.

Recently I'm implementing your code in pytorch, I want to test on 2D DenseUNet, I'm wondering that if testing on 2D DenseUNet follows the similar scheme, that is to say:
Find leftmost and rightmost z coordinates based on the coarse liver mask, Then slide a box sized 1x512x512x3 along the z-axis to make the prediction on the middle slice. the step size is set up to 1.

is that correct? thanks!

xmengli commented 5 years ago

Yes, you are correct. Using the coarse liver mask aims to increase the test efficiency.