hatch: hatch

In abdhigithub/hatch: Histogram-matching After Tissue Classification to a Healthy control

Description

Takes in subject input file and healthy control files to produce matched intensity histograms

Usage

hatch(infile, wm_pve, gm_pve, csf_pve, ctrl_vox, ctrl_img, i.min = 0.01,
  i.max = 0.99, i.s.min = 0, i.s.max = 1, h = seq(0.1, 0.9, by = 0.1),
  rangemax = 255, threshold = 0.99, samples = c(1500, 1200, 1000),
  outfile = NULL)

Arguments

infile	Patient Image Nifti file or path (T1, T2, T1gad or FLAIR)
wm_pve	White Matter partial volume probabilty map or path
gm_pve	Grey Matter partial volume probabilty map or path
csf_pve	CSF partial volume probabilty map or path
ctrl_vox	Control Mask created using healthy control of subsampled voxles
ctrl_img	Healthy Control image coreesponding to the modality of the subject
i.min	min for subj landmark
i.max	max for subj landmark
i.s.min	min for control landmark
i.s.max	max for control landmark
h	series or quantiles
rangemax	Range of intensities are between 0 and rangemax default=255
threshold	cutoff probabilty value to choose good quality tissues, default = 0.99
samples	vector of size 3 determining the subsample sizes for White Matter, Grey Matter and CSF respectively, default =c(1500,1200,1000)
outfile	path to save output matched class to a particular location

Value

The histogram matched normalized image

abdhigithub/hatch documentation built on May 15, 2019, 3:14 p.m.