| Name | CBCTCardiacSegmentation JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | Segment Cardiac structures in CBCT images |
| upload_time | 2024-08-19 00:29:57 |
| maintainer | None |
| docs_url | None |
| author | Mark Gardner |
| requires_python | >=3.6 |
| license | None |
| keywords |
|
| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# CBCTCardiacSegmentation
[](https://github.com/Image-X-Institute/CBCTCardiacSegmentation/actions/workflows/python-app.yml)
[](https://codecov.io/github/Image-X-Institute/CBCTCardiacSegmentation)
**Author:** *Mark Gardner*
This code will generate cardiac segmentations in CBCT images. The input is dicom or volume files of a CBCT image and an optional planning CT and will output dicom and nifti segmentations of cardiac segmentations that are compatible with the input CBCT image. **Currently this works in Linux only**
## Setup/Build/Install
The module can installed using pip:
```
pip install CBCTCardiacSegmentation
```
This code uses the platipy repo (https://github.com/pyplati/platipy). If the platipy module is not automatically installed when installing the CTHeadDeformation code, the platipy library can be installed separately using the installation instructions (https://pyplati.github.io/platipy/getting_started.html).
Install elastix (https://elastix.lumc.nl/index.php)
## Usage
Sample Data can be downloaded from the cancer imaging archive. For this example we will be using data from the 4d-lung dataset. (https://www.cancerimagingarchive.net/collection/4d-lung/)
### Download example data
Download the dicom data for one phase of the 4D-CBCT scan, and one phase of the 4D-CT. For example for patientID 100_HM10395, download the <P4^P100^S100^I0, Gated, 0.0%> CBCT dicom data from the Sep 14, 1997, and the <P4^P100^S300^I00003, Gated, 0.0%A> CT dicom data from the Jul 01, 2003.
The CBCT and CT directories can then be set to:
```
CBCTDicomDir = "<Directory where data was downloaded to>/4D-Lung/100_HM10395/09-15-1997-NA-p4-69351/500.000000-P4P100S100I0 Gated 0.0-90726"
CTDicomDir = "<Directory where data was downloaded to>/4D-Lung/100_HM10395/07-02-2003-NA-p4-14571/1.000000-P4P100S300I00003 Gated 0.0A-29193"
```
The directory where the created segmentations can also be set
```
OutputDir = "<Directory where data was downloaded to>/4D-Lung/100_HM10395/CardiacSegmentations
```
### Run in python script
See [DemonstrateCBCTSegmentation.py](https://github.com/Image-X-Institute/CBCTCardiacSegmentation/blob/master/CBCTCardiacSegmentation/DemonstrateCBCTSegmentation.py) for an example python script.
```
from CBCTCardiacSegmentation import CreateCBCTSegmentations
CreateCBCTSegmentations(CBCTDicomDir,OutputDir=OutputDir,PlanningCTDir=CTDicomDir)
```
### Run in a command line
In a command line (such as anaconda command prompt) navigate to the directory that the CTHeadDeformation repo was cloned to and run
```python CreateCBCTSegmentations.py <CBCTDicomDir> --OutputDir <OutputDir> --PlanningCTDir <CTDicomDir>```
### Function Options
A summary of the input options are shown below
```
--CBCTDir CBCTDIR Location of the Cone-beam CT that is to be segmented. Can be a Dicom Series or Volume file.
--OutputDir OUTPUTDIR
Directory where the created segmentations will be created. Default is ./CBCTSegmentations. (Optional)
--SegmentationMethod SEGMENTATIONMETHOD
The method used to segment the CBCT image {Synthetic|Transform|Direct}. Default is Synthetic. (Optional)
--PlanningCTDir PLANNINGCTDIR
Location of the Planning CT that is to be segmented. Can be a Dicom Series or Volume file.
Default is None. (Optional)
--ElastixParamDir ELASTIXPARAMDIR
Location of the elastix parameter files used for the registrations. Default is the parameters
is the provided ElastixParameterFiles. (Optional)
--StructFile STRUCTFILE
Location of the structures contoured from the planning CT File. Default is None
--KeepTempFiles If true the temporary files and directories created will not be deleted. If False these files
will be deleted. (Optional)
```
The different segmentation methods are:
- Synthetic: A synthetic CT is created by deforming a planning CT to match the CBCT. CT cardiac segmentation is then applied to this image.
- Transform: The Planning CT is first segmented. The planning CT and CBCT are deformably registered and the output transformation is used to map the planning CT segmentations to the CBCT.
- Direct: The CT segmentation method is directly applied to the CBCT image. May perform unreliably, particularly for noisy CBCT images.
## Directory Structure
CBCTCardiacSegmentation - Main code directory.
ElastixParameterFiles - Contains parameter files required for elastix.
docs - Files and info for the wiki.
examples - Files and data for examples of how to run the code.
tests - Files for testing the code.
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"description": "# CBCTCardiacSegmentation\r\n\r\n[](https://github.com/Image-X-Institute/CBCTCardiacSegmentation/actions/workflows/python-app.yml)\r\n[](https://codecov.io/github/Image-X-Institute/CBCTCardiacSegmentation)\r\n\r\n**Author:** *Mark Gardner*\r\n\r\n\r\n\r\nThis code will generate cardiac segmentations in CBCT images. The input is dicom or volume files of a CBCT image and an optional planning CT and will output dicom and nifti segmentations of cardiac segmentations that are compatible with the input CBCT image. **Currently this works in Linux only**\r\n\r\n\r\n## Setup/Build/Install\r\n\r\nThe module can installed using pip:\r\n\r\n```\r\npip install CBCTCardiacSegmentation\r\n```\r\n\r\nThis code uses the platipy repo (https://github.com/pyplati/platipy). If the platipy module is not automatically installed when installing the CTHeadDeformation code, the platipy library can be installed separately using the installation instructions (https://pyplati.github.io/platipy/getting_started.html). \r\n\r\nInstall elastix (https://elastix.lumc.nl/index.php)\r\n\r\n## Usage\r\n\r\nSample Data can be downloaded from the cancer imaging archive. For this example we will be using data from the 4d-lung dataset. (https://www.cancerimagingarchive.net/collection/4d-lung/)\r\n\r\n### Download example data\r\n\r\nDownload the dicom data for one phase of the 4D-CBCT scan, and one phase of the 4D-CT. For example for patientID 100_HM10395, download the <P4^P100^S100^I0, Gated, 0.0%> CBCT dicom data from the Sep 14, 1997, and the <P4^P100^S300^I00003, Gated, 0.0%A> CT dicom data from the Jul 01, 2003.\r\n\r\nThe CBCT and CT directories can then be set to:\r\n\r\n```\r\nCBCTDicomDir = \"<Directory where data was downloaded to>/4D-Lung/100_HM10395/09-15-1997-NA-p4-69351/500.000000-P4P100S100I0 Gated 0.0-90726\"\r\nCTDicomDir = \"<Directory where data was downloaded to>/4D-Lung/100_HM10395/07-02-2003-NA-p4-14571/1.000000-P4P100S300I00003 Gated 0.0A-29193\"\r\n```\r\nThe directory where the created segmentations can also be set\r\n```\r\nOutputDir = \"<Directory where data was downloaded to>/4D-Lung/100_HM10395/CardiacSegmentations\r\n```\r\n\r\n### Run in python script\r\nSee [DemonstrateCBCTSegmentation.py](https://github.com/Image-X-Institute/CBCTCardiacSegmentation/blob/master/CBCTCardiacSegmentation/DemonstrateCBCTSegmentation.py) for an example python script. \r\n```\r\nfrom CBCTCardiacSegmentation import CreateCBCTSegmentations\r\nCreateCBCTSegmentations(CBCTDicomDir,OutputDir=OutputDir,PlanningCTDir=CTDicomDir)\r\n```\r\n\r\n### Run in a command line\r\n\r\nIn a command line (such as anaconda command prompt) navigate to the directory that the CTHeadDeformation repo was cloned to and run \r\n```python CreateCBCTSegmentations.py <CBCTDicomDir> --OutputDir <OutputDir> --PlanningCTDir <CTDicomDir>``` \r\n\r\n### Function Options\r\n A summary of the input options are shown below\r\n ```\r\n --CBCTDir CBCTDIR Location of the Cone-beam CT that is to be segmented. Can be a Dicom Series or Volume file.\r\n --OutputDir OUTPUTDIR\r\n Directory where the created segmentations will be created. Default is ./CBCTSegmentations. (Optional)\r\n --SegmentationMethod SEGMENTATIONMETHOD\r\n The method used to segment the CBCT image {Synthetic|Transform|Direct}. Default is Synthetic. (Optional)\r\n --PlanningCTDir PLANNINGCTDIR\r\n Location of the Planning CT that is to be segmented. Can be a Dicom Series or Volume file.\r\n Default is None. (Optional)\r\n --ElastixParamDir ELASTIXPARAMDIR\r\n Location of the elastix parameter files used for the registrations. Default is the parameters\r\n is the provided ElastixParameterFiles. (Optional)\r\n --StructFile STRUCTFILE\r\n Location of the structures contoured from the planning CT File. Default is None\r\n --KeepTempFiles If true the temporary files and directories created will not be deleted. If False these files\r\n will be deleted. (Optional)\r\n ```\r\n \r\n The different segmentation methods are:\r\n - Synthetic: A synthetic CT is created by deforming a planning CT to match the CBCT. CT cardiac segmentation is then applied to this image.\r\n - Transform: The Planning CT is first segmented. The planning CT and CBCT are deformably registered and the output transformation is used to map the planning CT segmentations to the CBCT.\r\n - Direct: The CT segmentation method is directly applied to the CBCT image. May perform unreliably, particularly for noisy CBCT images. \r\n \r\n \r\n## Directory Structure\r\nCBCTCardiacSegmentation - Main code directory.\r\nElastixParameterFiles - Contains parameter files required for elastix.\r\ndocs - Files and info for the wiki. \r\nexamples - Files and data for examples of how to run the code.\r\ntests - Files for testing the code. \r\n",
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