Background

• This repo provides deep-learning methods for EPI VDM corrention and EPI brain segmentaion.
• We also provided the stand-alone application working on Windows, Mac, and Linux.

Install stand-alone version

https://github.com/htylab/tigerepi/releases

Usage

tigerepi -bmawk c:\data\*.nii.gz -o c:\output

As a python package

pip install onnxruntime #for gpu version: onnxruntime-gpu
pip install https://github.com/htylab/tigerepi/archive/refs/heads/main.zip

Segmentation

As a python package

import tigerepi
tigerepi.seg('bmawk', r'C:\EPI_dir', r'C:\output_dir')
tigerepi.seg('bmawk', r'C:\EPI_dir\**\*.nii.gz', r'C:\output_dir')
tigerepi.seg('bmawk', r'C:\EPI_dir\**\*.nii.gz') # storing output in the same dir
tigerepi.seg('ag', r'C:\EPI_dir') # Producing aseg masks with GPU

** Mac and Windows are supported.**

** Ubuntu (version >20.04) are supported.**

>>tigerepi  c:\data\**\*epi.nii -o c:\outputdir -b -m -a -w -k
-b: producing extracted brain
-m: producing the brain mask
-a: producing the aseg mask
-w, Producing the white matter parcellation (work in progress)
-k, Producing the dkt mask (work in progress)

Virtual Displacement Mapping

As a python package

import tigerepi
tigerepi.vdm(r'C:\EPI_dir', r'C:\output_dir', b0_index=0)

** Mac and Windows are supported.**

** Ubuntu (version >20.04) are supported.**

>>tigerepi_vdm  c:\data\**\*epi.nii -o c:\outputdir

• For additional options type:

>>tigerepi_vdm -h

Citation

• If you use this application, cite the following paper:

1. Kuo CC, Huang TY, Lin YR, Chuang TC, Tsai SY, Chung HW, “Referenceless correction of EPI distortion with virtual displacement mapping” (2023)

Label definitions

For label definitions, please check here. Label definitions