what will be the input image?

[ahmadmubashir]

should we give the input the whole 3D CT images? please explain it
the folder name
'train/ct' and 'train/seg'
please also explain it.

Thanks

[ahmadmubashir]

do we need any per processing? I prepare the dataset with your code. get_random_data.py
then i make the 3d patches of size 323232 and given it to the network. but loss is not decreasing. please help me. thanks

[mitiandi]

should we give the input the whole 3D CT images? please explain it
the folder name
'train/ct' and 'train/seg'
please also explain it.

Thanks

should we give the input the whole 3D CT images? please explain it
the folder name
'train/ct' and 'train/seg'
please also explain it.

Thanks

Hi,
the author uses 3D CT images as the input of network,but they should be pre-processed.
'train/ct' means the ct volumes of train set, while 'train/seg' means their ground truths.
Best wishes to you!

[ahmadmubashir]

should we give the input the whole 3D CT images? please explain it
the folder name
'train/ct' and 'train/seg'
please also explain it.
Thanks

should we give the input the whole 3D CT images? please explain it
the folder name
'train/ct' and 'train/seg'
please also explain it.
Thanks

Hi,
the author uses 3D CT images as the input of network,but they should be pre-processed.
'train/ct' means the ct volumes of train set, while 'train/seg' means their ground truths.
Best wishes to you!

Thank you. But for training, we need to give the whole volume? Or distribute it to 3D multiple equal size patches? This confuses me.

[mitiandi]

https://github.com/assassint2017/MICCAI-LITS2017/issues/5#issuecomment-434156126