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This version mirrors the attenuation map generation and reconstruction algorithms that were used on Aether. We recommend to use this version only for continuation studies. This version mirrors the attenuation map generation and reconstruction algorithms that were used on Aether. We recommend to use this version only for continuation studies. Scripts are located inside: '' /autofs/cluster/petcore/PET_computer_backup/brainPET_code/Aether-Mirror''. You will have to ''cd'' to this folder before running any of the functions below.
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(!) For full instructions type: '''perl brainPET_pCT_AeMir.pl''' -h
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This function performs thresholding-based denoising for the MPRAGE image to clean it for better pseudo-CT results! Use it only if the mprage is noisy. This function performs thresholding-based denoising for the MPRAGE image to clean it for better pseudo-CT results. Use it only if the mprage is noisy.
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{{{
#!python
}}}
(!) For full instructions type: ''' perl brainPET_denoise_mprage.pl -h '''
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This function converts brainPET ifile to nifit format.

(!) For full instructions type: ''' perl brainPET_ifile2nifti.pl -h '''

Index

BrainPET

HI


/!\ This page is only to process PET-MR data acquired using BrainPET (Bay 6) scanner at the Athinoula A. Martinos Center for Biomedical Imaging.


Aether-Mirror Version

This version mirrors the attenuation map generation and reconstruction algorithms that were used on Aether. We recommend to use this version only for continuation studies. Scripts are located inside: /autofs/cluster/petcore/PET_computer_backup/brainPET_code/Aether-Mirror. You will have to cd to this folder before running any of the functions below.

PseudoCT mu-map generation

This function generates pseudoCT mu-map using SPM8 atlas-based method (David Izquierdo-Garcia et al.)

(!) For full instructions type: perl brainPET_pCT_AeMir.pl -h

  • For DICOM input:

perl brainPET_pCT_AeMir.pl -i /<DIR>/<SUJID>/MR/MPRAGE -f 107000-000005-000001.dcm -c 0
  • For NIFTI input

perl brainPET_pCT_AeMir.pl -i /<DIR>/<SUJID>/MR_PET -f cp_iso_mprage.nii -c 0
  • IMP1: The r-l flip is applied only to .dcm input but not to .nii input (see Imp2)
  • IMP2: If you input a nifti file, it should be named as cp_iso_mprage.nii and it should be r-l flipped (i.e., it is the output of a previously ran pesudo CT).

Supporting Functions

Download and Organize MR and PET Data

This function to creates subject directory and its PET/MR/MR_PET sub-directories, download its MR and/or PET data, and unpack & organize MR data. You can download old and recently acquired data (see the note below for old data download). It also allows you to QC TOI/ScanID/ScanDate/PI through termainal output.

perl brainPET_mrpet_dwnld_unpack.pl -d /<DIR> -s <SubjID> -id <ScanID> -mr 1 -pet 1

To download an old subject (acquired more than 4 years ago), please do the following:

  1. ssh to pinto.nmr.mgh.harvard.edu

  2. cd to where the code is located
  3. type: bash (and hit enter)
  4. re-run the script

The script automatically detects if the subject is old or recently acquired and an error message will pop up with instructions in case of an old subject.

Denoise MPRAGE

This function performs thresholding-based denoising for the MPRAGE image to clean it for better pseudo-CT results. Use it only if the mprage is noisy. It works only with nifti (.nii) file as input. It takes a denoising threshold (intensity) to remove noise in the image, and a Gauss smoothing factor (mm) to facilitate denoising.

(!) For full instructions type: perl brainPET_denoise_mprage.pl -h

perl brainPET_denoise_mprage.pl -i /<DIR>/<SUBJID>/MR_PET/cp_iso_mprage.nii -t 25 -s 0

Outputs: cp_iso_mprage_denoised_thres<>_smooth<>mm.nii and scp_iso_mprage.nii (this is the smoothed version of the input image, it should be identical to the input if the smoothing was set to 0). The output is saved in the same folder as the input.

ifile2nifti

This function converts brainPET ifile to nifit format.

(!) For full instructions type: perl brainPET_ifile2nifti.pl -h

perl brainPET_ifile2nifti.pl -i /<DIR>/file.i

Development Version

BrainPET (last edited 2021-11-09 12:13:59 by MeenaMakary)