from nlmeans import nlmeans
import nibabel as nib
import os
files = ['dsi_cut_v2.nii.gz']
patch_size = 1
nbhood_size = 5
sigma = 0
for img in files:
temp, ext = str.split(os.path.basename(img), '.', 1)
filename = os.path.dirname(os.path.realpath(img)) + '/' + temp + '_denoised.nii.gz'
# '/data/' + temp + '_denoised_nlmeans_rician.nii.gz'
denoised = nlmeans(nib.load(img), std=sigma, nbhood_size=patch_size, search_size=nbhood_size) # './data/' + img))
# Patch the b0 to 32767 like it was before denoising
data_denoised = denoised.get_data()
# data_denoised[...,0] = 32767
img_denoised = nib.Nifti1Image(data_denoised, denoised.get_affine(), denoised.get_header())
nib.save(img_denoised, filename)
from nlmeans import nlmeans
import nibabel as nib
import os
files = ['DWIS_dsi-scheme_SNR-20.nii.gz']
for img in files:
temp, ext = str.split(os.path.basename(img), '.', 1)
filename = os.path.dirname(os.path.realpath(img)) + '/data/' + temp + '_denoised_nlmeans_rician.nii.gz'
denoised = nlmeans(nib.load('./data/' + img))
# Patch the b0 to 32767 like it was before denoising
data_denoised = denoised.get_data()
data_denoised[...,0] = 32767
img_denoised = nib.Nifti1Image(data_denoised, denoised.get_affine(), denoised.get_header())
nib.save(img_denoised, filename)
