[DLMED] update according to Hans comments
"metadata": {},
"source": [
"## Setup transforms for training and validation\n",
- "Here we use several transforms to enhance and normalize the dataset:\n",
+ "Here we use several transforms to augment the dataset:\n",
"1. `LoadNiftid` loads the spleen 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. `Spacingd` adjusts the spacing by `pixdim=(1.5, 1.5, 2.)` based on the affine matrix.\n",
"5. `ScaleIntensityRanged` extracts intensity range [-57, 164] and scales to [0, 1].\n",
"6. `CropForegroundd` removes all zero borders to focus on the valid body area of the images and labels.\n",
"7. `RandCropByPosNegLabeld` randomly crop patch samples from big image based on pos / neg ratio. \n",
- " This transform can obviously enhance the dataset. The image centers of negative samples must be in valid body area.\n",
+ " The image centers of negative samples must be in valid body area.\n",
"8. `RandAffined` efficiently performs `rotate`, `scale`, `shear`, `translate`, etc. together based on PyTorch affine transform.\n",
"9. `ToTensord` converts the numpy array to PyTorch Tensor for further steps."
]
