Commit e0effcfa authored by Vaanathi Sundaresan's avatar Vaanathi Sundaresan
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Update README.md

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## Brain Tumour Segmentation with TrUE-Net tool
### Preprint (to be updated)
### Won 5th highest score in MICCAI Brain Tumour Segmentation Challenge 2020
## Preprint (to be updated)
#### Software versions used for truenet:
- Python > 3.6
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## TrUE-Net architecture:
<img
src="images/main_architecture_final.png"
alt="Triplanar U-Net ensemble network (TrUE-Net). (a) U-Net model used in individual planes, (b) Overall TrUE-Net architecture."
src="images/Network_architecture.png"
alt="Proposed triplanar ensemble network architecture. (a) Input modalities in the axial plane along with manual segmentations for NCR/NET (blue), ET (yellow), ED (red) and TC (magenta), (b) the proposed network and (c) 3-layer deep U-Net blocks used in (b). Slices with 4 channels (input modalities) were provided to all U-nets."
/>
### Classes and the loss function:
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#### prepare_tumseg_data
```
Usage: prepare_tumseg_data <FLAIR_image_name> <T1_image_name> <output_basename>
Usage: prepare_tumseg_data <Base_modality_type> <output_basename> <FLAIR_image_name> <T1_image_name> <T1ce_image_name> <T2_image_name>
The script prepares the FLAIR and T1 data to be used in FSL truenet with a specified output basename
FLAIR_image_name name of the input unprocessed FLAIR image
T1_image_name name of the input unprocessed T1 image
output_basename name to be used for the processed FLAIR and T1 images (along with the absolute path);
output_basename_FLAIR.nii.gz, output_basename_T1.nii.gz and output_basename_WMmask.nii.gz will be saved
The script applies the preprocessing pipeline on FLAIR, T1, T1ce and T2 to be used in FSL truenet_tumseg with a specified output basename
Base_modality_name and output_basename are mandatory inputs
Remaining inputs are optional, image corresponding to Base_modality_name must be provided. Images to be provided in the given order.
In case you do not have a modality, provide 'None' for that modality.
Base_modality_name = name of the modality that the rest will be registered to (preferable ~1mm iso); valid options: flair, t1, t1ce, t2
output_basename = name to be used for the processed images (use absolute path); output_basename_FLAIR.nii.gz, output_basename_T1.nii.gz .... will be saved
FLAIR_image_name = name of the input unprocessed FLAIR image
T1_image_name = name of the input unprocessed T1 image
T1ce_image_name = name of the input unprocessed T1-contrast enhanced image
T2_image_name = name of the input unprocessed T2 image
For example, if you have flair, t1 and t2 and want to register everything to t1, use the following command
prepare_tumseg_data t1 path/to/outputbasename path/to/input_flair.nii.gz path/to/input_t1.nii.gz None path/to/input_t2.nii.gz
```
## Running truenet brain tumor segmentation
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