def create_slices(imagePath, maskPath, cads):
# if os.path.isfile(imagePath.replace('original', SAVE_FOLDER_image)) == False:
img, origin, spacing = load_itk(imagePath)
mask, _, _ = load_itk(maskPath)
# determine the cads in a lung from csv file
imageName = os.path.split(imagePath)[1].replace('.mhd', '')
image_cads = cads[cads['seriesuid'] == imageName]
# calculate resize factor
resize_factor = spacing / RESIZE_SPACING
new_real_shape = img.shape * resize_factor
new_shape = np.round(new_real_shape)
real_resize = new_shape / img.shape
new_spacing = spacing / real_resize
# resize image & resize lung-mask
lung_img = scipy.ndimage.interpolation.zoom(img, real_resize)
lung_mask = scipy.ndimage.interpolation.zoom(mask, real_resize)
# print lung_mask.shape()
# lung_mask to 0-1
lung_mask[lung_mask > 0] = 1
# create nodule mask
nodule_mask = draw_circles(lung_img, image_cads, origin, new_spacing)
# Determine which slices contain nodules
sliceList = []
for z in range(nodule_mask.shape[2]):
if np.sum(nodule_mask[:, :, z]) > 0:
sliceList.append(z)
# save slices
for z in sliceList:
lung_slice = lung_img[:, :, z]
lung_mask_slice = lung_mask[:, :, z]
nodule_mask_slice = nodule_mask[:, :, z]
# padding to 512x512
original_shape = lung_img.shape
lung_slice_512 = np.zeros((512, 512)) - 3000
lung_mask_slice_512 = np.zeros((512, 512))
nodule_mask_slice_512 = np.zeros((512, 512))
offset = (512 - original_shape[1])
upper_offset = np.round(offset / 2)
lower_offset = offset - upper_offset
new_origin = voxel_2_world([-upper_offset, -lower_offset, 0], origin,
new_spacing)
lung_slice_512[upper_offset:-lower_offset,
upper_offset:-lower_offset] = lung_slice
lung_mask_slice_512[upper_offset:-lower_offset,
upper_offset:-lower_offset] = lung_mask_slice
nodule_mask_slice_512[upper_offset:-lower_offset,
upper_offset:-lower_offset] = nodule_mask_slice
# save the lung slice
savePath = imagePath.replace('original_lungs', SAVE_FOLDER_image)
f = gzip.open(savePath.replace('.mhd', '_slice{}.pkl.gz'.format(z)),
'wb')
pickle.dump(lung_slice_512, f, protocol=-1)
pickle.dump(new_spacing, f, protocol=-1)
pickle.dump(new_origin, f, protocol=-1)
f.close()
savePath = imagePath.replace('original_lungs', SAVE_FOLDER_lung_mask)
f = gzip.open(savePath.replace('.mhd', '_slice{}.pkl.gz'.format(z)),
'wb')
pickle.dump(lung_mask_slice_512, f, protocol=-1)
pickle.dump(new_spacing, f, protocol=-1)
pickle.dump(new_origin, f, protocol=-1)
f.close()
savePath = imagePath.replace('original_lungs', SAVE_FOLDER_nodule_mask)
f = gzip.open(savePath.replace('.mhd', '_slice{}.pkl.gz'.format(z)),
'wb')
pickle.dump(nodule_mask_slice_512, f, protocol=-1)
pickle.dump(new_spacing, f, protocol=-1)
pickle.dump(new_origin, f, protocol=-1)
f.close()
def create_slices(imagePath, maskPath, cads):
#if os.path.isfile(imagePath.replace('original',SAVE_FOLDER_image)) == False:
img, origin, spacing = load_itk(imagePath)
mask, _, _ = load_itk(maskPath)
#determine the cads in a lung from csv file
imageName = os.path.split(imagePath)[1].replace('.mhd','')
image_cads = cads[cads['seriesuid'] == imageName]
#calculate resize factor
resize_factor = spacing / RESIZE_SPACING
new_real_shape = img.shape * resize_factor
new_shape = np.round(new_real_shape)
real_resize = new_shape / img.shape
new_spacing = spacing / real_resize
#resize image & resize lung-mask
lung_img = scipy.ndimage.interpolation.zoom(img, real_resize)
lung_mask = scipy.ndimage.interpolation.zoom(mask, real_resize)
#print lung_mask.shape()
#lung_mask to 0-1
lung_mask[lung_mask >0] = 1
#create nodule mask
nodule_mask = draw_circles(lung_img,image_cads,origin,new_spacing)
#Determine which slices contain nodules
sliceList = []
for z in range(nodule_mask.shape[2]):
if np.sum(nodule_mask[:,:,z]) > 0:
sliceList.append(z)
#save slices
for z in sliceList:
lung_slice = lung_img[:,:,z]
lung_mask_slice = lung_mask[:,:,z]
nodule_mask_slice = nodule_mask[:,:,z]
#padding to 512x512
original_shape = lung_img.shape
lung_slice_512 = np.zeros((512,512)) - 3000
lung_mask_slice_512 = np.zeros((512,512))
nodule_mask_slice_512 = np.zeros((512,512))
offset = (512 - original_shape[1])
upper_offset = np.round(offset/2)
lower_offset = offset - upper_offset
new_origin = voxel_2_world([-upper_offset,-lower_offset,0],origin,new_spacing)
lung_slice_512[upper_offset:-lower_offset,upper_offset:-lower_offset] = lung_slice
lung_mask_slice_512[upper_offset:-lower_offset,upper_offset:-lower_offset] = lung_mask_slice
nodule_mask_slice_512[upper_offset:-lower_offset,upper_offset:-lower_offset] = nodule_mask_slice
#save the lung slice
savePath = imagePath.replace('original_lungs',SAVE_FOLDER_image)
file = gzip.open(savePath.replace('.mhd','_slice{}.pkl.gz'.format(z)),'wb')
pickle.dump(lung_slice_512,file,protocol=-1)
pickle.dump(new_spacing,file, protocol=-1)
pickle.dump(new_origin,file, protocol=-1)
file.close()
savePath = imagePath.replace('original_lungs',SAVE_FOLDER_lung_mask)
file = gzip.open(savePath.replace('.mhd','_slice{}.pkl.gz'.format(z)),'wb')
pickle.dump(lung_mask_slice_512,file,protocol=-1)
pickle.dump(new_spacing,file, protocol=-1)
pickle.dump(new_origin,file, protocol=-1)
file.close()
savePath = imagePath.replace('original_lungs',SAVE_FOLDER_nodule_mask)
file = gzip.open(savePath.replace('.mhd','_slice{}.pkl.gz'.format(z)),'wb')
pickle.dump(nodule_mask_slice_512,file,protocol=-1)
pickle.dump(new_spacing,file, protocol=-1)
pickle.dump(new_origin,file, protocol=-1)
file.close()