Skip to content

update 3d_registration tutorial #806

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 4 commits into from
Jul 19, 2022
Merged

update 3d_registration tutorial #806

Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
031ced2
update 3d_registration
KumoLiu Jul 19, 2022
d2e75a4
fix pep8 error
KumoLiu Jul 19, 2022
d0c332c
fix pep8 error
KumoLiu Jul 19, 2022
19adaa3
Merge branch 'main' into update-3d_registration-tutorial
wyli Jul 19, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 11 additions & 23 deletions 3d_registration/paired_lung_ct.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -129,13 +129,11 @@
"from monai.networks.blocks import Warp\n",
"from monai.networks.nets import LocalNet\n",
"from monai.transforms import (\n",
" AddChanneld,\n",
" Compose,\n",
" LoadImaged,\n",
" RandAffined,\n",
" Resized,\n",
" ScaleIntensityRanged,\n",
" EnsureTyped,\n",
")\n",
"from monai.utils import set_determinism, first\n",
"\n",
Expand Down Expand Up @@ -302,12 +300,10 @@
"source": [
"## Setup transforms for training and validation\n",
"Here we use several transforms to augment the dataset:\n",
"1. LoadImaged loads the lung CT images and labels from NIfTI format files.\n",
"2. AddChanneld as the original data doesn't have channel dim, add 1 dim to construct \"channel first\" shape.\n",
"3. ScaleIntensityRanged extracts intensity range [-285, 3770] and scales to [0, 1].\n",
"4. RandAffined efficiently performs rotate, scale, shear, translate, etc. together based on PyTorch affine transform.\n",
"5. Resized resize images to the same size.\n",
"6. EnsureTyped converts the numpy array to PyTorch Tensor for further steps."
"1. LoadImaged loads the lung CT images and labels from NIfTI format files. \"ensure_channel_first=True\" ensure that the first dim is channel.\n",
"2. ScaleIntensityRanged extracts intensity range [-285, 3770] and scales to [0, 1].\n",
"3. RandAffined efficiently performs rotate, scale, shear, translate, etc. together based on PyTorch affine transform.\n",
"4. Resized resize images to the same size."
]
},
{
Expand All @@ -324,10 +320,8 @@
"train_transforms = Compose(\n",
" [\n",
" LoadImaged(\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"]\n",
" ),\n",
" AddChanneld(\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"]\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"],\n",
" ensure_channel_first=True\n",
" ),\n",
" ScaleIntensityRanged(\n",
" keys=[\"fixed_image\", \"moving_image\"],\n",
Expand All @@ -345,18 +339,13 @@
" align_corners=(True, True, None, None),\n",
" spatial_size=(96, 96, 104)\n",
" ),\n",
" EnsureTyped(\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"]\n",
" ),\n",
" ]\n",
")\n",
"val_transforms = Compose(\n",
" [\n",
" LoadImaged(\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"]\n",
" ),\n",
" AddChanneld(\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"]\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"],\n",
" ensure_channel_first=True\n",
" ),\n",
" ScaleIntensityRanged(\n",
" keys=[\"fixed_image\", \"moving_image\"],\n",
Expand All @@ -369,9 +358,6 @@
" align_corners=(True, True, None, None),\n",
" spatial_size=(96, 96, 104)\n",
" ),\n",
" EnsureTyped(\n",
" keys=[\"fixed_image\", \"moving_image\", \"fixed_label\", \"moving_label\"]\n",
" ),\n",
" ]\n",
")"
]
Expand Down Expand Up @@ -693,6 +679,7 @@
"\n",
" val_ddf, val_pred_image, val_pred_label = forward(\n",
" val_data, model)\n",
" val_pred_label[val_pred_label > 1] = 1\n",
"\n",
" val_fixed_image = val_data[\"fixed_image\"].to(device)\n",
" val_fixed_label = val_data[\"fixed_label\"].to(device)\n",
Expand Down Expand Up @@ -723,6 +710,7 @@
" optimizer.zero_grad()\n",
"\n",
" ddf, pred_image, pred_label = forward(batch_data, model)\n",
" pred_label[pred_label > 1] = 1\n",
"\n",
" fixed_image = batch_data[\"fixed_image\"].to(device)\n",
" fixed_label = batch_data[\"fixed_label\"].to(device)\n",
Expand Down Expand Up @@ -1281,7 +1269,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.8.13"
}
},
"nbformat": 4,
Expand Down