#Load needed libraries
import numpy as np, nibabel as nib, nagini, sys, scipy.optimize as opt, scipy.interpolate as interp
from tqdm import tqdm
#########################
###Data Pre-Processing###
#########################
print('Loading images...')
#Load image headers
pet = nagini.loadHeader(args.pet[0])
brain = nagini.loadHeader(args.brain[0])
#Load in the idaif.
idaif = nagini.loadIdaif(args.idaif[0])
#Load in the info file
info = nagini.loadInfo(args.info[0])
#Check to make sure dimensions match
if pet.shape[0:3] != brain.shape[0:3] or pet.shape[3] != idaif.shape[
0] or pet.shape[3] != info.shape[0]:
print 'ERROR: Data dimensions do not match. Please check...'
sys.exit()
#Get the image data
petData = pet.get_data()
brainData = brain.get_data()
#Flatten the PET images and then mask
#Load needed libraries
import numpy as np, nibabel as nib, nagini, sys, scipy.optimize as opt, scipy.interpolate as interp
from tqdm import tqdm
#########################
###Data Pre-Processing###
#########################
print ('Loading images...')
#Load image headers
pet = nagini.loadHeader(args.pet[0])
brain = nagini.loadHeader(args.brain[0])
#Load in the idaif.
idaif = nagini.loadIdaif(args.idaif[0])
#Load in the info file
info = nagini.loadInfo(args.info[0])
#Check to make sure dimensions match
if pet.shape[0:3] != brain.shape[0:3] or pet.shape[3] != idaif.shape[0] or pet.shape[3] != info.shape[0]:
print 'ERROR: Data dimensions do not match. Please check...'
sys.exit()
#Get the image data
petData = pet.get_data()
brainData = brain.get_data()
#Flatten the PET images and then mask
petMasked = nagini.reshape4d(petData)[brainData.flatten()>0,:]