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Process T1-weighted Brain MRI Data with FSL and Register to EVE Atlas

eve_T1.Rd

This function takes a T1-weighted brain MRI image, performs bias correction, reorientation to standard space, brain extraction using FSL's BET, and registration to the EVE brain template. It then segments the brain volume into different tissue types, calculates intracranial volume and outputs the results as an Rdata file.

Usage

eve_T1(
  fpath,
  outpath,
  fsl_path = "/Users/jinyaotian/fsl",
  fsl_outputtype = "NIFTI_GZ"
)

Arguments

fpath

Character string specifying the path to one T1-weighted MRI file. The file should be in NIFTI file format (.nii.gz).

outpath

Character string specifying the output directory where the results will be saved as an Rdata file.

fsl_path

Character string specifying the directory where FSL is installed.

fsl_outputtype

Character string specifying the FSL output file type. Defaults to "NIFTI_GZ".

Value

Saves the image data after processing to the specified output path. Outputs an Rdata file containing three components: image intensities array, segmented tissues array, and brain volume metrics.

Details

The function begins by loading the EVE brain template for image registration. It then reads the T1-weighted MRI file and reorients it to standard space using FSL's fslreorient2std. Following reorientation, it applies bias correction with FSL's fsl_biascorrect, which is necessary to correct for field inhomogeneities that can affect quantitative analysis. The next step involves using FSL’s Brain Extraction Tool (BET) to isolate the brain from non-brain tissue which is crucial for accurate subsequent analysis. After brain extraction, the image is registered to the EVE brain atlas using FLIRT, ensuring that the image is aligned with a standard coordinate space for comparable anatomical analysis. Subsequent to registration, the function uses FSL's FAST tool to segment the brain into white matter, grey matter, and cerebrospinal fluid, which are essential for studying brain structure and pathology. Finally, it calculates the volume of these tissues, providing key data points for clinical and research applications. Each step logs its progress with timestamps, aiding in debugging and optimization of processing times.

Examples

## Not run:
eve_T1("path/to/your/image.nii.gz", "path/to/output", "/usr/local/fsl",  "NIFTI_GZ")
#> [1] "2025-01-27 22:07:47.480962 Reading image: path/to/your/image.nii.gz"
#> Error in oro.nifti::readNIfTI(..., reorient = reorient): File(s) not found!
## End(Not run)