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Python implementation of the ENABLE quality-based volume selection algorithm for ASL-MRI data

Project description

ENABLE - ENhancement of Automated Blood fLow Estimates

ENABLE is a technique to evaulate image quality in multi-PLD ASL data.

Shirzadi et al, "Enhancement of Automated Blood Flow Estimates (ENABLE) From Arterial Spin-Labelled MRI" J Magn Reson Imaging. 2017 Jul 6. doi: 10.1002/jmri.25807

ENABLE performs the following steps:

  1. A preprocessing step, consisting of tag/control differencing, brain extraction, T1 co-registration and segmentation

  2. A sorting step in which quality measures are calculated for each PLD image, namely:

  • Contrast:Noise ratio in GM (CNR)
  • Detectibility metric (DETECT, proportion of voxels with significantly greater than zero signal in GM)
  • Coefficient of variation of difference data (COV, spatial standard deviation divided by spatial mean in GM)
  • Temporal SNR (TSNR, spatial mean of ASL image divided by temporal STD image in GM)
  1. A selection step in which a combined quality measure is calculated and the best image is identified:
  • 0.1CNR + 1.8DETECT - COV - TSNR
  1. A CBF generation step in which a CBF image is generated from the best image


oxasl_enable -i <ASL input file> -t1 <T1 image> -n <Noise ROI image> -o <Output dir>

oxasl_enable can also be used as a plug-in for the OXASL ASL processing pipeline - see documentation for this tool at:


--version      show program's version number and exit
-h, --help     show this help message and exit
-i INFILE      ASL data file
--t1=T1        T1 map
-n NOISE       Noise ROI
-o OUTPUT      Output dir
--debug=DEBUG  Debug mode

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