Usage: 3dAnhist [options] dataset
Input dataset is a T1-weighted high-res of the brain (shorts only).
Output is a list of peaks in the histogram, to stdout, in the form
  ( datasetname #peaks peak1 peak2 ... )
In the C-shell, for example, you could do
  set anhist = `3dAnhist -q -w1 dset+orig`
Then the number of peaks found is in the shell variable $anhist[2].

  -q  = be quiet (don't print progress reports)
  -h  = dump histogram data to Anhist.1D and plot to Anhist.ps
  -F  = DON'T fit histogram with stupid curves.
  -w  = apply a Winsorizing filter prior to histogram scan
         (or -w7 to Winsorize 7 times, etc.)
  -2  = Analyze top 2 peaks only, for overlap etc.

  -label xxx = Use 'xxx' for a label on the Anhist.ps plot file
                instead of the input dataset filename.
  -fname fff = Use 'fff' for the filename instead of 'Anhist'.

If the '-2' option is used, AND if 2 peaks are detected, AND if
the -h option is also given, then stdout will be of the form
  ( datasetname 2 peak1 peak2 thresh CER CJV count1 count2 count1/count2)
where 2      = number of peaks
      thresh = threshold between peak1 and peak2 for decision-making
      CER    = classification error rate of thresh
      CJV    = coefficient of joint variation
      count1 = area under fitted PDF for peak1
      count2 = area under fitted PDF for peak2
      count1/count2 = ratio of the above quantities
* If the input is a T1-weighted MRI dataset (the usual case), then
   peak 1 should be the gray matter (GM) peak and peak 2 the white
   matter (WM) peak.
* For the definitions of CER and CJV, see the paper
   Method for Bias Field Correction of Brain T1-Weighted Magnetic
   Resonance Images Minimizing Segmentation Error
   JD Gispert, S Reig, J Pascau, JJ Vaquero, P Garcia-Barreno,
   and M Desco, Human Brain Mapping 22:133-144 (2004).
* Roughly speaking, CER is the ratio of the overlapping area of the
   2 peak fitted PDFs to the total area of the fitted PDFS.  CJV is
   (sigma_GM+sigma_WM)/(mean_WM-mean_GM), and is a different, ad hoc,
   measurement of how much the two PDF overlap.
* The fitted PDFs are NOT Gaussians.  They are of the form
   f(x) = b((x-p)/w,a), where p=location of peak, w=width, 'a' is
   a skewness parameter between -1 and 1; the basic distribution
   is defined by b(x)=(1-x^2)^2*(1+a*x*abs(x)) for -1 < x < 1.

-- RWCox - November 2004

++ Compile date = May 11 2021 {AFNI_21.1.07:linux_ubuntu_16_64}