def test_dicom_class_validate(self): mu = mudicom.load(self.fnames[0]) dcm = mu.validate() self.assertEqual(len(dcm['errors']), 6) self.assertEqual(len(dcm['warnings']), 18) mu = mudicom.load(self.fnames[1]) dcm = mu.validate() self.assertEqual(len(dcm['errors']), 7) self.assertEqual(len(dcm['warnings']), 18)
def test_dicom_class_validate(self):
mu = mudicom.load(self.fnames[0])
dcm = mu.validate()
self.assertEqual(len(dcm['errors']), 6)
self.assertEqual(len(dcm['warnings']), 18)
mu = mudicom.load(self.fnames[1])
dcm = mu.validate()
self.assertEqual(len(dcm['errors']), 7)
self.assertEqual(len(dcm['warnings']), 18)
def test_get_numpy(self):
for fname in self.fnames:
mu = mudicom.load(fname)
img = mu.image
gnp = img.numpy
self.assertIsInstance(gnp, numpy.ndarray)
self.assertEqual(gnp.dtype, numpy.float)
def test_get_numpy(self):
for fname in self.fnames:
mu = mudicom.load(fname)
img = mu.image
gnp = img.numpy
self.assertIsInstance(gnp, numpy.ndarray)
self.assertEqual(gnp.dtype, numpy.float)
def test_get_element(self):
for fname in self.fnames:
mu = mudicom.load(fname)
#reader = mu.read()
self.assertIsInstance(mu.find(0x004, 0x1220), list)
self.assertIsInstance(mu.find(name="Modality"), list)
self.assertIsInstance(mu.find(VR="PN"), list)
def test_walk_dataset(self):
for fname in self.fnames:
mu = mudicom.load(fname)
#reader = mu.read()
tags = list(mu.walk(lambda ds: ds.GetTag()))
self.assertIsInstance(tags, list)
self.assertIsNot(len(tags), 0)
for tag in tags:
self.assertIsInstance(tag, gdcm.Tag)
tags = list(mu.walk(lambda ds: None))
self.assertIsInstance(tags, list)
for tag in tags:
self.assertEqual(tag, None)
tags = list(mu.walk(lambda ds: False))
self.assertIsInstance(tags, list)
for tag in tags:
self.assertFalse(tag)
tags = list(mu.walk(lambda ds: True))
self.assertIsInstance(tags, list)
for tag in tags:
self.assertTrue(tag)
def test_walk_dataset(self):
for fname in self.fnames:
mu = mudicom.load(fname)
#reader = mu.read()
tags = list(mu.walk(lambda ds: ds.GetTag()))
self.assertIsInstance(tags, list)
self.assertIsNot(len(tags), 0)
for tag in tags:
self.assertIsInstance(tag, gdcm.Tag)
tags = list(mu.walk(lambda ds: None))
self.assertIsInstance(tags, list)
for tag in tags:
self.assertEqual(tag, None)
tags = list(mu.walk(lambda ds: False))
self.assertIsInstance(tags, list)
for tag in tags:
self.assertFalse(tag)
tags = list(mu.walk(lambda ds: True))
self.assertIsInstance(tags, list)
for tag in tags:
self.assertTrue(tag)
def test_get_element(self):
for fname in self.fnames:
mu = mudicom.load(fname)
#reader = mu.read()
self.assertIsInstance(mu.find(0x004, 0x1220), list)
self.assertIsInstance(mu.find(name="Modality"), list)
self.assertIsInstance(mu.find(VR="PN"), list)
def dcm2thumbnail(source_path, target_path, resize_row=128, resize_col=128):
# define output
dict_return = {}
dict_return['status'] = 1
dict_return['paths'] = target_path
filename = source_path.split(os.path.sep)[-1]
if filename.split('.')[-1] == 'dcm':
filename = filename[0:len(filename) - 4]
if target_path[-1] != os.path.sep:
target_path += os.path.sep
# get usefull dicom information
try:
dcm_head = dicom.read_file(source_path)
except IOError:
dict_return['status'] = 0
print('read dicom error')
return dict_return
rescale_intercept = dcm_head.RescaleIntercept
rescale_slope = dcm_head.RescaleSlope
# get original pixel
try:
mud = mudicom.load(source_path)
except mudicom.exceptions.InvalidDicom:
dict_return['status'] = 0
print('read mudicom error')
return dict_return
pixel_ori = (mud.image).numpy
pixel_ori = pixel_ori.astype(np.int16)
# pixel to HU value
pixel_hu = copy.deepcopy(pixel_ori)
pixel_hu = (rescale_slope * pixel_hu.astype(np.float64)).astype(np.int16)
pixel_hu += np.int16(rescale_intercept)
pixel_hu = np.array(pixel_hu, dtype=np.int16)
# adjust window
default_img = adjust_window(pixel_hu, *(40, 400))
default_img = scipy.misc.imresize(default_img, (resize_row, resize_col),
'nearest')
# return status
try:
scipy.misc.imsave(target_path + filename + '.jpg', default_img)
except IOError:
dict_return['status'] = 0
return dict_return
dict_return['paths'] = target_path + filename + '.jpg'
return dict_return
def test_get_dataset(self):
for fname in self.fnames:
mu = mudicom.load(fname)
ds = mu.read()
self.assertIsInstance(ds, list)
self.assertIsNot(len(ds), 0)
for element in ds:
self.assertTrue(hasattr(element, "name"))
self.assertTrue(hasattr(element, "value"))
self.assertTrue(hasattr(element, "VR"))
self.assertTrue(hasattr(element, "VL"))
self.assertTrue(hasattr(element, "tag"))
self.assertTrue("group" in element.tag)
self.assertTrue("element" in element.tag)
self.assertTrue("str" in element.tag)
def test_get_dataset(self):
for fname in self.fnames:
mu = mudicom.load(fname)
ds = mu.read()
self.assertIsInstance(ds, list)
self.assertIsNot(len(ds), 0)
for element in ds:
self.assertTrue(hasattr(element, "name"))
self.assertTrue(hasattr(element, "value"))
self.assertTrue(hasattr(element, "VR"))
self.assertTrue(hasattr(element, "VL"))
self.assertTrue(hasattr(element, "tag"))
self.assertTrue("group" in element.tag)
self.assertTrue("element" in element.tag)
self.assertTrue("str" in element.tag)
def GetPixelByTransferSyntax(self):
if self.ts == uid.ImplicitVRLittleEndian or self.ts == uid.JPEGLossless:
self.ds.decompress()
self.pixel = self.ds.pixel_array
elif self.ts == uid.ExplicitVRLittleEndian or self.ts == uid.JPEG2000Lossy:
import mudicom
mu = mudicom.load(self.fPath)
# returns array of data elements as dicts
mu.read()
# creates image object
img = mu.image # before v0.1.0 this was mu.image()
# returns numpy array
self.pixel = img.numpy # before v0.1.0 this was mu.numpy()fileFolder
else:
print self.ts + " can not support Transfer Syntax"
return
return self.pixel
q[1] = max(q[1],1)
tf=[[0,0,0,0,0],[q[0],0,0,0,0],[q[1],1,1,1,0.5],[data.max(),1,1,1,1]]
actor_list = volumeRender(data, tf=tf, spacing=img.GetSpacing())
vtk_basic(actor_list)
下面一个不错的软件：
https://github.com/bastula/dicompyler
还有一个python的库mudicom，https://github.com/neurosnap/mudicom
[python] view plain copy
import mudicom
mu = mudicom.load("mudicom/tests/dicoms/ex1.dcm")
# returns array of data elements as dicts
mu.read()
# returns dict of errors and warnings for DICOM
mu.validate()
# basic anonymization
mu.anonymize()
# save anonymization
mu.save_as("dicom.dcm")
# creates image object
img = mu.image # before v0.1.0 this was mu.image()
# returns numpy array
# import cv2
import numpy as np
from matplotlib import pyplot as plt
# from PIL import Image
from skimage.color import rgb2gray
from skimage.filters import threshold_mean
from skimage import util
from skimage.filters import median
from skimage.morphology import disk, skeletonize, binary_dilation, binary_erosion, binary_closing
# from skimage.exposure import equalize_adapthist
# ds = dicom.read_file("2d_angiogram_2.dcm")
img_id = 1
mu = mudicom.load("2d_angiogram_" + str(img_id) + ".dcm")
mu_out = mu.image
pixel_array = mu_out.numpy
# with open("pixel_array", "w") as f:
# np.save(f, pixel_array)
# exit()
i = 1
# fig2, ax = plt.subplots(2, 2, figsize=(10, 8))
fig = plt.figure(frameon=False)
ax = plt.Axes(fig, [0., 0., 1., 1.])
fig.set_size_inches(5.12, 5.12)
ax.set_axis_off()
if event.key == 'j':
previous_slice(ax)
elif event.key == 'k':
next_slice(ax)
fig.canvas.draw()
def previous_slice(ax):
volume = ax.volume
ax.index = (ax.index - 1) % volume.shape[0] # wrap around using %
ax.images[0].set_array(volume[ax.index])
def next_slice(ax):
volume = ax.volume
ax.index = (ax.index + 1) % volume.shape[0]
ax.images[0].set_array(volume[ax.index])
fpath = "/home/j_69/Fiducial Localization - MRI Scans/pvc/Sequential Scan/DICOM/PA1/ST1/SE2" ## edit this accordingly
slices = 176 ## edit this accordingly
mu = []
arry = []
for i in range(1, slices):
mu.append(dicom.load(fpath + "/IM" + str(i)))
arry.append(mu[i - 1].image.numpy)
multi_slice_viewer(np.array(arry))
plt.show()
view_pointcloud(surfaceVoxels_ref, color='y')
plt.show()
##multi_slice_viewer(voxel_ndarray_ref)
##plt.show()
### Using Rawfloating image, as patient data missing for this view
directory_flo1 = "/home/j_69/Fiducial Localization - MRI Scans/glass/Glass Scan Coronal 0.9 mm/DICOM/PA1/ST1/SE2" ## edit this accordingly
slices = 256 ## edit this accordingly
mu = []
arry = []
for i in range(1, slices):
mu.append(mudicom.load(directory_flo1 + "/IM" + str(i)))
arry.append(mu[i - 1].image.numpy)
voxel_ndarray_flo1 = np.array(arry)
surfaceVoxels_flo1 = getSurfaceVoxels(voxel_ndarray_flo1)
print surfaceVoxels_flo1
view_pointcloud(surfaceVoxels_ref, color='b')
plt.show()
print("Applying ICP...")
ijkmat = icp(surfaceVoxels_ref, surfaceVoxels_flo1, max_iterations=40)
print(ijkmat)
"""
voxel_ndarray_flo1 = snd.rotate(voxel_ndarray_ref,15)
def test_animation_numpy_shape(self):
mu = mudicom.load(self.fnames[2])
image = mu.image
self.assertEqual(len(image.numpy.shape), 3)
self.assertEqual(image.numpy.shape[0], 76)
def test_animation_numpy_shape(self):
mu = mudicom.load(self.fnames[2])
image = mu.image
self.assertEqual(len(image.numpy.shape), 3)
self.assertEqual(image.numpy.shape[0], 76)
def _generate_data_elements(self, filename):
mu = mudicom.load(uploaded_dicoms.path(filename))
return [DicomDataElement(e) for e in mu.find()]
