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crop_zoom_to_roi_original_flywheel.py
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#!/usr/bin/env python
from matplotlib.path import Path
import matplotlib.pyplot as plt
import nibabel as nib
import numpy as np
from scipy import interpolate
import scipy.ndimage.interpolation as wezoom
import glob
import os
import sys
import argparse
import math
import logging as log
from scipy.ndimage.measurements import center_of_mass
def get_dimension(msid):
import pandas as pd
from subprocess import Popen,PIPE, check_output
cmd = ["/opt/fsl-5.0.10/bin/fslinfo",msid]
# cmd = ["fslinfo",msid]
proc = Popen(cmd, stdout=PIPE)
lines = [l.decode("utf-8").split() for l in proc.stdout.readlines()[5:]]
d={}
for i in lines[:20]:
d[i[0]]=i[1]
dim1=d['pixdim1']
dim2=d['pixdim2']
#tmp["a0"] = par_returner(x,ch[0][0],ch[0][1], ch[0][2], ch[0][3], ch[0][4], ch[0][5])[1]
return float(dim1),float(dim2)
def create_zoomed_files(psir, roi,outputs_path,slic=-1):
psir_affine, psir_data = load(psir)
x_res = psir_affine[0,0]
y_res = psir_affine[1,1]
x_res,y_res=get_dimension(psir)
#print(psir_data.shape)
if(len(psir_data.shape) == 2):
psir_data = psir_data[:,:,np.newaxis]
x_dim, y_dim, z_dim = psir_data.shape
# COMPUTE SCALE FACTOR AND CROP DISTANCE
scalefac = int(round(math.sqrt((abs(x_res*y_res)/(.078125**2)))))
cropdist = int(round(150/float(scalefac)))
# settings
numvox = cropdist*2*scalefac
bsp_order=2
pt_list = getpts(roi)
#print(pt_list[2])
# FLIP SIGN OF Y
flip_ysign_matrix=np.ones([pt_list.shape[0],pt_list.shape[1]])
flip_ysign_matrix[:,1]=-1
flip_ysign_pt_list = pt_list*flip_ysign_matrix
# TRANSFORM FROM JIM COORDINATES (0,0 at center of PSIR image) TO PSIR SPACE
x_multiplicative_factor = 1/(math.fabs(x_res))
y_multiplicative_factor = 1/(math.fabs(y_res))
x_additive_factor = x_dim/2
y_additive_factor = y_dim/2
psir_pt_list = flip_ysign_pt_list*(x_multiplicative_factor, y_multiplicative_factor)+(x_additive_factor,y_additive_factor)
# FIND CENTER OF MASS OF SPINAL CORD WM, THEN SET BORDERS
center_of_mass_psir_space = np.floor(psir_pt_list.mean(0))
xmin_psir_space = int(center_of_mass_psir_space[0]-cropdist)
xmax_psir_space = int(center_of_mass_psir_space[0]+cropdist)
ymin_psir_space = int(center_of_mass_psir_space[1]-cropdist)
ymax_psir_space = int(center_of_mass_psir_space[1]+cropdist)
xmin_JIM_space = (xmin_psir_space-x_additive_factor)/x_multiplicative_factor
xmax_JIM_space = (xmax_psir_space-x_additive_factor)/x_multiplicative_factor
ymin_JIM_space = (ymin_psir_space-y_additive_factor)/y_multiplicative_factor
ymax_JIM_space = (ymax_psir_space-y_additive_factor)/y_multiplicative_factor
#print 'xmin = %s; xmax = %s; ymin = %s; ymax = %s' % (xmin, xmax, ymin, ymax)
# MAKE PSIR CROP IMAGE
psir_crop = psir_data[xmin_psir_space:xmax_psir_space, ymin_psir_space:ymax_psir_space]
crop_aff = np.diag([-1*x_res*psir_crop.shape[0]/numvox,y_res*psir_crop.shape[1]/numvox,1,1])
if slic!=-1:
z = psir_crop[:,:,slic]
else:
z = psir_crop[:,:]
# MAKE PSIR CROP INTERP IMAGE
zoomed = wezoom.zoom(z, numvox/(xmax_psir_space-xmin_psir_space), order=bsp_order)
zoomed_file = psir[:-7]+'_zoomed.nii.gz'
#nib.save(nib.Nifti1Image(zoomed,crop_aff), zoomed_file)
# MAKE CORD MASK IMAGE
path = Path(flip_ysign_pt_list)
X = np.linspace(xmin_JIM_space,xmax_JIM_space,zoomed.shape[0])
Y = np.linspace(ymin_JIM_space,ymax_JIM_space,zoomed.shape[0])
cord_mask = np.zeros([len(X),len(Y)])
for i,x in enumerate(X):
for j,y in enumerate(Y):
cord_mask[i,j]=path.contains_point([x,y])
cord_mask_file = psir[:-7]+'_zoomed_cord_mask.nii.gz'
#cord_mask_img = nib.save(nib.Nifti1Image(cord_mask.astype("uint8"), crop_aff), cord_mask_file)
# MAKE CORD IMAGE
#print('cord_mask:{} zoomed: {}'.format(cord_mask.shape,zoomed.shape))
cord = np.multiply(cord_mask, zoomed[:,:,0])
if not os.path.isdir(outputs_path):
os.mkdir(outputs_path)
if not os.path.isdir(os.path.join(outputs_path, "final_output")):
os.mkdir(os.path.join(outputs_path,"final_output"))
try:
os.mkdir(outputs_path)
os.mkdir(outputs_path+'/final_output')
except:
pass
mini=np.amin(cord)
mask2yo=np.where(cord==0,cord,1)
if mini<0:
cord=cord+abs(mini)+50
cord=cord*mask2yo
cordpth=outputs_path+'/final_output/only_cord'+os.path.basename(psir)
cordsave=nib.save(nib.Nifti1Image(cord,crop_aff),cordpth)
return cord,crop_aff,cordpth
def create_nifti_zoomed(psir, cord_nifti, outputs_path, pre_samp_thresh, post_samp_thresh, slic=-1):
psir_affine, psir_data = load(psir)
psir_shape = np.shape(psir_data)
try:
tmp = int(np.ceil(psir_shape[2]/2))
psir_data = psir_data[:,:,tmp-1]
except:
pass
x_res = psir_affine[0,0]
y_res = psir_affine[1,1]
x_res,y_res=get_dimension(psir)
#print(psir_data.shape)
print(psir_data.shape)
x_dim, y_dim = psir_data.shape
# COMPUTE SCALE FACTOR AND CROP DISTANCE
scalefac = int(round(math.sqrt((abs(x_res*y_res)/(.078125**2)))))
cropdist = int(round(150/float(scalefac)))
# settings
numvox = cropdist*2*scalefac
bsp_order=1
# import pdbrace()
cord_nifti_affine, cord_nifti_data = load(cord_nifti)
cord_shape = np.shape(cord_nifti_data)
try:
tmp = int(np.ceil(cord_shape[2]/2))
cord_nifti_data = cord_nifti_data[:,:,tmp-1]
except:
pass
x_res_cord,y_res_cord=get_dimension(cord_nifti)
cord_nifti_data=wezoom.zoom(cord_nifti_data,x_res_cord/x_res).astype(np.float)
cord_nifti_data=np.logical_and(cord_nifti_data>0.1,cord_nifti_data>0.05).astype(np.float)
print(x_res_cord,y_res_cord)
scalefac_cord=int(round(math.sqrt((abs(x_res*y_res)/(.078125**2)))))
cropdist_cord=int(round(150/float(scalefac_cord)))
# FLIP SIGN OF Y
# TRANSFORM FROM JIM COORDINATES (0,0 at center of PSIR image) TO PSIR SPACE
x_multiplicative_factor = 1/(math.fabs(x_res))
y_multiplicative_factor = 1/(math.fabs(y_res))
x_additive_factor = x_dim/2
y_additive_factor = y_dim/2
# FIND CENTER OF MASS OF SPINAL CORD WM, THEN SET BORDERS
center_of_mass_psir_space = center_of_mass(cord_nifti_data)
center_of_mass_cord_space=center_of_mass(cord_nifti_data)
xmin_psir_space = int(center_of_mass_psir_space[0]-cropdist)
xmax_psir_space = int(center_of_mass_psir_space[0]+cropdist)
ymin_psir_space = int(center_of_mass_psir_space[1]-cropdist)
ymax_psir_space = int(center_of_mass_psir_space[1]+cropdist)
xmin_cord_space = int(center_of_mass_cord_space[0]-cropdist_cord)
xmax_cord_space = int(center_of_mass_cord_space[0]+cropdist_cord)
ymin_cord_space = int(center_of_mass_cord_space[1]-cropdist_cord)
ymax_cord_space = int(center_of_mass_cord_space[1]+cropdist_cord)
#print 'xmin = %s; xmax = %s; ymin = %s; ymax = %s' % (xmin, xmax, ymin, ymax)
# MAKE PSIR CROP IMAGE
psir_crop = psir_data[xmin_psir_space:xmax_psir_space, ymin_psir_space:ymax_psir_space]
crop_aff = np.diag([-1*x_res*psir_crop.shape[0]/numvox,y_res*psir_crop.shape[1]/numvox,1,1])
if slic!=-1:
z = psir_crop[:,:,slic]
else:
z = psir_crop[:,:]
#MAKE CORD CROP
cord_nifti_crop = cord_nifti_data[xmin_cord_space:xmax_cord_space, ymin_cord_space:ymax_cord_space]
print(numvox/(xmax_cord_space-xmin_cord_space))
# MAKE PSIR CROP INTERP IMAGE
zoomed = wezoom.zoom(z, numvox/(xmax_psir_space-xmin_psir_space), order=bsp_order)
zoomed_file = psir[:-7]+'_zoomed.nii.gz'
nib.save(nib.Nifti1Image(zoomed,crop_aff), zoomed_file)
# MAKE CORD MASK IMAGE
#nib.save(nib.Nifti1Image(cord_nifti_crop,crop_aff),psir[:-7]+'_zoomed_cord_mask_pre.nii.gz')
cord_nifti_crop=np.logical_and(cord_nifti_crop>float(pre_samp_thresh),cord_nifti_crop<3).astype(np.float)
area_of_cord=np.sum(cord_nifti_crop)
zoomed_cord_mask = wezoom.zoom(cord_nifti_crop, numvox/(xmax_cord_space-xmin_cord_space), order=bsp_order)
cord_mask_file = psir[:-7]+'_zoomed_cord_mask.nii.gz'
print(cord_mask_file)
cord_mask_img = nib.save(nib.Nifti1Image(zoomed_cord_mask.astype(np.float), crop_aff), cord_mask_file)
zoomed_cord_mask = np.logical_and(zoomed_cord_mask > float(post_samp_thresh), zoomed_cord_mask < 3).astype(np.float)
# MAKE CORD IMAGE
#print('cord_mask:{} zoomed: {}'.format(cord_mask.shape,zoomed.shape))
mask_shape = len(np.shape(zoomed_cord_mask))
cord_shape = len(np.shape(zoomed))
if mask_shape == 2 and cord_shape == 2:
cord = np.multiply(zoomed_cord_mask[:,:], zoomed[:,:])
elif mask_shape == 3 and cord_shape == 3:
cord = np.multiply(zoomed_cord_mask[:,:,0], zoomed[:,:,0])
elif mask_shape == 3 and cord_shape == 2:
cord = np.multiply(zoomed_cord_mask[:,:,0], zoomed[:,:])
else:
cord = np.multiply(zoomed_cord_mask[:,:], zoomed[:,:,0])
if not os.path.isdir(outputs_path):
os.mkdir(outputs_path)
if not os.path.isdir(os.path.join(outputs_path, "final_output")):
os.mkdir(os.path.join(outputs_path,"final_output"))
try:
os.mkdir(outputs_path)
os.mkdir(os.path.join(outputs_path, 'final_output'))
except:
pass
mini=np.amin(cord)
mask2yo=np.where(cord==0,cord,1)
if mini<0:
cord=cord+abs(mini)+50
cord=cord*mask2yo
cordpth=os.path.join(outputs_path, 'final_output/only_cord_'+os.path.basename(psir))
cordsave=nib.save(nib.Nifti1Image(cord,crop_aff),cordpth)
return cord,crop_aff,cordpth
def getpts(filepath):
rois = 0
cordlist=[]
cordxylist = []
roifile = open(filepath, 'r')
lines = roifile.readlines()
roifile.close()
for line in lines:
if "X=" in line:
cordlist.append(line.strip())
for pt in cordlist:
parts = pt.split('=')
x = parts[1][:-3]
y = parts[-1]
cordxylist += [[x, y]]
cord = np.array(cordxylist, dtype='float64')
return cord
def load(image):
img = nib.load(image)
img_affine = img.get_affine()
img_data = np.array(img.get_data())
return img_affine, img_data