try:
weight = cc.LoadMHA(imagedir +
'block{0}_as_MRI_weight_{1}.mha'.format(i, sz))
except IOError:
print 'Warning, weight block does not exist'
weight = ca.Image3D(blk.grid(), blk.memType())
ca.Copy(weight, blk, 0) # take red
cc.SetRegionGTE(weight, weight, .1, 1)
for i in xrange(3):
ca.Copy(weight3, weight, i)
weights += weight3
print ca.MinMax(weights)
for i in xrange(3):
ca.Copy(weight, weights, i)
cc.SetRegionLT(weight, weight, 1, 1)
ca.Copy(weights, weight, i)
print ca.MinMax(weights)
ca.Div_I(blocks, weights)
else: # best
imagedir = '/home/sci/crottman/korenberg/results/'
blocks = cc.LoadMHA(
imagedir + 'BFI_2D_Reg/block1_as_MRI_' + col + '_256.mha', ca.MEM_HOST)
blk = cc.LoadMHA(imagedir + 'BFI_2D_Reg/block2_as_MRI_' + col + '_256.mha',
ca.MEM_HOST)
blocks += blk
blk = cc.LoadMHA(imagedir + 'landmark/block3_as_MRI_' + col + '.mha',
ca.MEM_HOST)
blocks += blk
import PyCA.Core as ca
import numpy as np
import sys
import PyCACalebExtras.Common as cc
import PyCACalebExtras.Display as cd
import matplotlib.pyplot as plt
plt.close('all')
block = 3 # 1, 2, 3, 4
dir_in = '/home/sci/crottman/korenberg/results/landmark/'
dir_out = '/home/sci/crottman/korenberg/results/ve_reg/'
Imri = cc.LoadMHA('/home/sci/crottman/korenberg/results/MRI/brain_seg.mha')
cc.SetRegionLT(Imri, Imri, 1.0, 20000)
VEmri = ca.Image3D(Imri.grid(), Imri.memType())
cc.VarianceEqualize(VEmri, Imri, sigma=2.0)
# # load landmark registered blocks
# Ibfi = cc.LoadMHA(dir_in + 'block' + str(block) + '_as_MRI_bw.mha')
# ca.Neg_I(Ibfi)
# VEbfi = ca.Image3D(Imri.grid(), Imri.memType())
# cc.VarianceEqualize(VEbfi, Ibfi, sigma=2.0)
# cd.DispImage(VEbfi, ca.MinMax(VEmri))
# load landmark registered pre-VEd block
VEbfi = cc.LoadMHA(dir_in + 'block' + str(block) + '_as_MRI_ve.mha')
ca.Neg_I(VEbfi)
# cc.WritePNG(VEbfi, 'VEbfi_block' + str(block) + 'new.png', rng = [-2.8, 2.8])
# cd.DispImage(Ibfi)