Python读取NIf格式医学图像及数据增强实战

# encoding=utf8
'''
查看和显示nii文件
'''
import matplotlib
matplotlib.use('TkAgg')
 
from matplotlib import pylab as plt
import nibabel as nib
from nibabel import nifti1
from nibabel.viewers import OrthoSlicer3D
 
example_filename = '../ADNI_nii/ADNI_002_S_0413_MR_MPR____N3__Scaled_2_Br_20081001114937668_S14782_I118675.nii'
 
img = nib.load(example_filename)
print (img)
print (img.header['db_name'])  #输出头信息
width,height,queue=img.dataobj.shape
OrthoSlicer3D(img.dataobj).show()
 
num = 1
for i in range(0,queue,10):
 
  img_arr = img.dataobj[:,:,i]
  plt.subplot(5,4,num)
  plt.imshow(img_arr,cmap='gray')
  num +=1
plt.show()
 

NIf图像数据增强与扩充实现

import os
import nibabel as nib
import numpy as np
import math
 
src_us_folder = 'F:/src/ori'
src_seg_folder = 'G:/src/seg'
 
aug_us_folder = 'G:/aug/ori'
aug_seg_folder = 'G:/aug/seg'
 
img_n= 10
rotate_theta = np.array([0, math.pi/2])
 
# augmentation
aug_cnt = 0
for k in range(img_n):
  src_us_file = os.path.join(src_us_folder, (str(k) + '.nii'))
  src_seg_file = os.path.join(src_seg_folder, (str(k) + '_seg.nii'))
  # load .nii files
  src_us_vol = nib.load(src_us_file)
  src_seg_vol = nib.load(src_seg_file)
  # volume data
  us_vol_data = src_us_vol.get_data()
  us_vol_data = (np.array(us_vol_data)).astype('uint8')
  seg_vol_data = src_seg_vol.get_data()
  seg_vol_data = (np.array(seg_vol_data)).astype('uint8')
  # get refer affine matrix
  ref_affine = src_us_vol.affine
 
  ############### flip volume ###############
  flip_us_vol = np.fliplr(us_vol_data)
  flip_seg_vol = np.fliplr(seg_vol_data)
  # construct new volumes
  new_us_vol = nib.Nifti1Image(flip_us_vol, ref_affine)
  new_seg_vol = nib.Nifti1Image(flip_seg_vol, ref_affine)
  # save
  aug_us_file = os.path.join(aug_us_folder, (str(aug_cnt) + '.nii'))
  aug_seg_file = os.path.join(aug_seg_folder, (str(aug_cnt) + '_seg.nii'))
  nib.save(new_us_vol, aug_us_file)
  nib.save(new_seg_vol, aug_seg_file)
 
  aug_cnt = aug_cnt + 1
 
  ############### rotate volume ###############
  for t in range(len(rotate_theta)):
    print 'rotating %d theta of %d volume...' % (t, k)
    cos_gamma = np.cos(t)
    sin_gamma = np.sin(t)
    rot_affine = np.array([[1, 0, 0, 0],
                [0, cos_gamma, -sin_gamma, 0],
                [0, sin_gamma, cos_gamma, 0],
                [0, 0, 0, 1]])
    new_affine = rot_affine.dot(ref_affine)
    # construct new volumes
    new_us_vol = nib.Nifti1Image(us_vol_data, new_affine)
    new_seg_vol = nib.Nifti1Image(seg_vol_data, new_affine)
    # save
    aug_us_file = os.path.join(aug_us_folder, (str(aug_cnt) + '.nii'))
    aug_seg_file = os.path.join(aug_seg_folder, (str(aug_cnt) + '_seg.nii'))
    nib.save(new_us_vol, aug_us_file)
    nib.save(new_seg_vol, aug_seg_file)
 
    aug_cnt = aug_cnt + 1