Apply the MONAI tranforms as specified by the user input script and save output in the destination container
Project description
MONAI Transforms
Overview
Summary
Apply MONAI transforms to input file as specified by the user defined transform script and save the transformed output in the destination container.
Cite
https://doi.org/10.5281/zenodo.4323058 License: MIT
Classification
Category: converter
Gear Level:
- Project
- Subject
- Session
- Acquisition
- Analysis
Support
-
input-file
- Name: The input-file.
- Type: nifti, dicom, image
- Optional: False
- Description: Input NIfTI file for the transform.
-
transform-script
- Name: The transform module.py.
- Type: nifti
- Optional: False
- Description: The Python module containing the definition of the transforms to apply.
Config
-
debug
- Name: debug
- Type: boolean
- Description: Log debug messages
- Default: False
-
number-of-iterations
- Name: number-of-iterations
- Type: integer
- Description: Number of times the transform will be applied to the image.
- Default: False
Outputs
Files
- transformed-file
- Name: The transformed file
- Type: Whatever is specified in the
SaveImagedtransform
Usage
Description
This gear takes as input an image file (e.g. nii, nii.gz, dcm, png, jpg, bmp), loads
the transform defined by the input transform-script, applies this transform to the
input image and saved the transformed image in the destination acquisition container.
File Specifications
transform-script
The transform-script python file must:
- define an object called
transformfrom theComposeclass - start with a
LoadImagedtransform - end with a
SaveImagedtransform - apply the transformation(s) on the key
img
It is recommended to validate the transform first outside of the gear environment for faster/easier debugging/iteration. For example, the following code snippet will let you test your transform on a NIfTI file and inspect the saved output:
from monai.transforms import (
Compose, LoadImaged, EnsureChannelFirstd, RandGaussianNoised, SaveImaged
)
transform = Compose(
[
LoadImaged(["img"]),
EnsureChannelFirstd(["img"], channel_dim="no_channel"),
RandGaussianNoised(["img"]),
SaveImaged(["img"], output_postfix="t", output_ext=".nii.gz"),
]
)
transform({"img": "path/to/my/input/nifti.nii.gz"})
Examples of transforms can be found in the examples folder.
Workflow
A picture and description of the workflow
graph LR;
A[input-file]:::input --> E((Gear));
B[transform-script]:::input --> E((Gear));
E:::gear --> F[Transformed file]:::container;
classDef container fill:#57d,color:#fff
classDef input fill:#7a9,color:#fff
classDef gear fill:#659,color:#fff
Contributing
[For more information about how to get started contributing to that gear, checkout CONTRIBUTING.md.]
Project details
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