def test_vincentka_06_slice_thickness_interactive(self):
"""
Interactive test. SliceThickness is not voxel depth. If it is, this
test will fail.
"""
# dcmdir = os.path.join(path_to_script, './../sample_data/matlab/examples/sample_data/DICOM/digest_article/') #noqa
dcmdir = os.path.expanduser(
'~/data/medical/data_orig/vincentka/13021610/10200000/')
dcmdir = os.path.expanduser(
'~/data/medical/data_orig/vincentka/13021610/12460000/')
oseg = organ_segmentation.OrganSegmentation(dcmdir,
working_voxelsize_mm=4,
manualroi=False)
# manual seeds setting
print(
"with left mouse button select some pixels of the bottle content")
print("with right mouse button select some pixels of background")
oseg.interactivity()
volume = oseg.get_segmented_volume_size_mm3()
# print volume
self.assertGreater(volume, 550000)
self.assertLess(volume, 850000)
def test_organ_segmentation_with_boundary_penalties(self):
"""
Interactivity is stored to file
"""
dcmdir = io3d.datasets.join_path('jatra_5mm')
print("Interactive test: with left mouse button select liver, \
with right mouse button select other tissues")
# gcparams = {'pairwiseAlpha':10, 'use_boundary_penalties':True}
segparams = {
'pairwise_alpha_per': 3,
'use_boundary_penalties': True,
'boundary_penalties_sigma': 200
}
oseg = organ_segmentation.OrganSegmentation(dcmdir,
working_voxelsize_mm=4,
segparams=segparams)
oseg.add_seeds_mm([120], [120], [400], label=1, radius=30)
oseg.add_seeds_mm([170, 220, 250], [250, 280, 200], [400],
label=2,
radius=30)
"boundary penalties"
oseg.interactivity()
# oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# misc.obj_to_file(oseg.get_iparams(),'iparams.pkl', filetype='pickle')
self.assertGreater(volume, 1000000)
def test_create_iparams(self):
"""
Interactivity is stored to file
"""
if self.verbose:
print("test_create_iparams")
import misc
dcmdir = io3d.datasets.join_path('jatra_5mm')
# path_to_script, './../sample_data/jatra_5mm')
segparams = {'pairwiseAlpha': 20,
'use_boundary_penalties': False,
'boundary_penalties_sigma': 200}
# oseg = organ_segmentation.OrganSegmentation(dcmdir, working_voxelsize_mm = 4) # noqa
oseg = organ_segmentation.OrganSegmentation(
dcmdir, working_voxelsize_mm=4,
segparams=segparams, manualroi=False)
# oseg.add_seeds_mm([120, 160], [150, 120], [70], label=1, radius=20)
oseg.add_seeds_mm([120, 160], [150, 80], [85], label=1, radius=20)
oseg.add_seeds_mm([170, 220, 250, 100], [250, 300, 200, 350], [85],
label=2, radius=20)
oseg.add_seeds_mm([170], [240], [70], label=2, radius=20)
# print "test_ipars"
# oseg.interactivity()
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# print 'vol %.3g ' %(volume)
misc.obj_to_file(oseg.get_iparams(), 'iparams.pkl', filetype='pickle')
self.assertGreater(volume, 1000000)
def test_whole_organ_segmentation_interactive(self):
"""
Interactive test uses dicom data for segmentation
"""
dcmdir = os.path.join(
lisa.dataset.sample_data_path(),
'matlab/examples/sample_data/DICOM/digest_article/'
)
# path_to_script,
# './../sample_data/matlab/examples/sample_data/DICOM/digest_article/') # noqa
oseg = organ_segmentation.OrganSegmentation(
dcmdir, working_voxelsize_mm=4, manualroi=False)
# manual seeds setting
print ("with left mouse button select some pixels of the brain")
print ("with right mouse button select some pixels of other tissues\
and background")
oseg.interactivity()
volume = oseg.get_segmented_volume_size_mm3()
print volume
self.assertGreater(volume, 50000)
self.assertLess(volume, 1200000)
def test_split_by_two_vessels(self):
"""
Make virtual resection on synthetic data
"""
import lisa.virtual_resection as vr
data3d, segm, voxelsize_mm, slab = self.synthetic_data()
seeds = np.zeros([256, 256, 80], dtype=np.int16)
seeds[125, 160, 44] = 1
datap = {
'data3d': data3d,
'segmentation': segm,
'voxelsize_mm': voxelsize_mm,
'slab': slab
}
oseg = organ_segmentation.OrganSegmentation()
oseg.import_dataplus(datap)
oseg.split_organ_by_two_vessels(seed_label1="porta",
seed_label2="hepatic_veins",
organ_label="liver",
output_label1="liver",
output_label2="liver_remnant")
resected = np.sum(datap['segmentation'] == datap['slab']['liver'])
remaining = np.sum(
datap['segmentation'] == datap['slab']['liver_remnant'])
ratio = np.double(resected) / (resected + remaining)
# ed = sed3.sed3(datap["segmentation"])
# ed.show()
# print(ratio)
self.assertGreater(ratio, 0.6)
self.assertLess(ratio, 0.8)
def test_train_liver_model_and_liver_segmentation(self):
"""
combination of test_train_liver_model and test_organ_model_with_pretrained_classifier
:return:
"""
fn_mdl = "test_liver_intensity.Model.p"
organ_model.train_liver_model_from_sliver_data(
output_file=fn_mdl,
sliver_reference_dir="~/lisa_data/sample_data/",
orig_pattern="*orig*01.mhd",
ref_pattern="*seg*01.mhd",
)
path_to_data = lisa.dataset.sample_data_path()
dcmdir = os.path.join(path_to_data, './liver-orig001.mhd')
print "Interactive test: with left mouse button select liver, \
with right mouse button select other tissues"
# gcparams = {'pairwiseAlpha':10, 'use_boundary_penalties':True}
# fn_mdl = os.path.expanduser("~/lisa_data/liver_intensity.Model.p")
segparams = {}
segmodelparams = {
'mdl_stored_file': fn_mdl,
'fv_type': 'fv_extern',
'fv_extern': "intensity_localization_fv"
}
# 'pairwise_alpha_per': 3,
# 'use_boundary_penalties': True,
# 'boundary_penalties_sigma': 200}
oseg = organ_segmentation.OrganSegmentation(
dcmdir,
working_voxelsize_mm=4,
segparams=segparams,
segmodelparams=segmodelparams)
oseg.add_seeds_mm([200], [110, 150], [110, 100],
label=1,
radius=30,
width=5)
oseg.add_seeds_mm([200], [250, 230], [210, 260],
label=2,
radius=50,
width=5)
# from PyQt4.QtGui import QApplication
# app = QApplication(sys.argv)
# oseg.interactivity()
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# misc.obj_to_file(oseg.get_iparams(),'iparams.pkl', filetype='pickle')
self.assertGreater(volume, 1300000)
self.assertLess(volume, 2100000)
def synthetic_liver_template(self, params):
"""
Function uses organ_segmentation for synthetic box object
segmentation.
"""
# dcmdir = os.path.join(path_to_script,'./../sample_data/matlab/examples/sample_data/DICOM/digest_article/') # noqa
# data
data3d, segm, voxelsize_mm, slab = self.synthetic_liver()
# seeds
seeds = np.zeros(data3d.shape, np.int8)
seeds[40:55, 90:120, 70:110] = 1
seeds[30:45, 190:200, 40:90] = 2
# [mm] 10 x 10 x 10 # voxelsize_mm = [1, 4, 3]
metadata = {'voxelsize_mm': voxelsize_mm}
oseg = organ_segmentation.OrganSegmentation(
None,
data3d=data3d,
metadata=metadata,
seeds=seeds,
working_voxelsize_mm=5,
manualroi=False,
autocrop=False,
**params
)
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
oseg.portalVeinSegmentation(interactivity=False, threshold=180)
oseg.saveVesselTree('porta')
# print '> 0 '
# print np.sum(oseg.segmentation > 0)
# print np.sum(segm > 0)
# print np.sum(oseg.segmentation > 0) * np.prod(voxelsize_mm)
# print np.sum(segm > 0) * np.prod(voxelsize_mm)
# print 'computed ', volume
# print voxelsize_mm
# print oseg.voxelsize_mm
# import pdb; pdb.set_trace()
# import sed3
# ed = sed3.sed3(data3d, seeds=seeds,
# contour=(oseg.segmentation))
# ed.show()
# import ipdb; ipdb.set_trace() # noqa BREAKPOINT
# mel by to být litr. tedy milion mm3
# je to zvlastni. pro nekter verze knihoven je to 630, pro jine 580
self.assertGreater(volume, 570000)
self.assertLess(volume, 640000)
def main():
dcmdir = os.path.join(
path_to_script,
'./../sample_data/matlab/examples/sample_data/DICOM/digest_article/')
#data3d, metadata = dcmr.dcm_read_from_dir(dcmdir)
oseg = organ_segmentation.OrganSegmentation(dcmdir,
working_voxelsize_mm=4,
manualroi=False)
oseg.interactivity()
def test_resize_data_three_values(self):
datap = io3d.datasets.generate_abdominal()
target_voxelsize_mm = [7.14, 4.1, 3]
oseg = organ_segmentation.OrganSegmentation(working_voxelsize_mm=4,
manualroi=False)
oseg.import_dataplus(dataplus=datap)
orig_shape = oseg.data3d.shape
oseg.resize_to_mm(target_voxelsize_mm)
self.assertEqual(oseg.voxelsize_mm[0], target_voxelsize_mm[0])
self.assertEqual(oseg.voxelsize_mm[1], target_voxelsize_mm[1])
self.assertEqual(oseg.voxelsize_mm[2], target_voxelsize_mm[2])
self.assertNotEqual(orig_shape[0], oseg.data3d.shape[0])
self.assertNotEqual(orig_shape[1], oseg.data3d.shape[1])
self.assertNotEqual(orig_shape[2], oseg.data3d.shape[2])
def test_add_seeds_mm(self):
"""
Function uses organ_segmentation object for segmentation
"""
dcmdir = io3d.datasets.join_path(
'matlab/examples/sample_data/DICOM/digest_article/'
# path_to_script,
# './../sample_data/matlab/examples/sample_data/DICOM/digest_article/'
)
oseg = organ_segmentation.OrganSegmentation(dcmdir,
working_voxelsize_mm=4,
manualroi=False)
oseg.add_seeds_mm([80], [120], [120], 1, 25, width=2)
oseg.add_seeds_mm([80], [40], [130], 2, 25, width=2)
# just for testing resize
# oseg.seeds[:,:32,:32] = 2
# import ipdb; ipdb.set_trace()
# import sed3
# ed = sed3.sed3(oseg.data3d, seeds=oseg.seeds)
# ed.show()
# pro kontrolu lze odkomentovat
# from PyQt5.QtWidgets import QApplication
# app = QApplication(sys.argv)
# oseg.interactivity()
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# import pdb; pdb.set_trace()
# mel by to být litr. tedy milion mm3
self.assertGreater(volume, 800000)
self.assertLess(volume, 1200000)
# roi_mm = [[3, 3, 3], [150, 150, 50]]
# oseg.ni_set_roi()
# coordinates_mm = [[110, 50, 30], [10, 10, 10]]
# label = [1, 2]
# radius = [5, 5]
# oseg.ni_set_seeds(coordinates_mm, label, radius)
# oseg.make_segmentation()
# oseg.noninteractivity()
pass
def test_sync_paul(self):
"""
sync with paul account
"""
path_to_paul = lisa.lisa_data.path('sync','paul')
if os.path.exists(path_to_paul):
shutil.rmtree(path_to_paul)
oseg = organ_segmentation.OrganSegmentation(None)
oseg.sync_lisa_data('paul','P4ul')
file_path = lisa.lisa_data.path('sync','paul', 'from_server', 'test.txt')
logger.debug('file_path %s', file_path)
self.assertTrue(os.path.exists(file_path))
def test_organ_segmentation_with_pretrained_classifier(self):
"""
Interactivity is stored to file
:rtype: object
"""
path_to_data = lisa.dataset.sample_data_path()
dcmdir = os.path.join(path_to_data, './liver-orig001.mhd')
print("Interactive test: with left mouse button select liver, \
with right mouse button select other tissues")
# gcparams = {'pairwiseAlpha':10, 'use_boundary_penalties':True}
fn_mdl = os.path.expanduser("~/lisa_data/liver_intensity.Model.p")
segparams = {}
segmodelparams = {
'mdl_stored_file': fn_mdl,
'fv_type': 'fv_extern',
'fv_extern': "intensity_localization_fv"
}
# 'pairwise_alpha_per': 3,
# 'use_boundary_penalties': True,
# 'boundary_penalties_sigma': 200}
oseg = organ_segmentation.OrganSegmentation(
dcmdir,
working_voxelsize_mm=4,
segparams=segparams,
segmodelparams=segmodelparams)
oseg.add_seeds_mm([200], [110, 150], [110, 100],
label=1,
radius=30,
width=5)
oseg.add_seeds_mm([200], [250, 230], [210, 260],
label=2,
radius=50,
width=5)
from PyQt4.QtGui import QApplication
app = QApplication(sys.argv)
oseg.interactivity()
# oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# misc.obj_to_file(oseg.get_iparams(),'iparams.pkl', filetype='pickle')
self.assertGreater(volume, 1000000)
self.assertLess(volume, 2000000)
def synthetic_liver_template(self, params):
"""
Function uses organ_segmentation for synthetic box object
segmentation.
"""
# dcmdir = os.path.join(path_to_script,'./../sample_data/matlab/examples/sample_data/DICOM/digest_article/') # noqa
# data
data3d, segm, voxelsize_mm, slab, seeds_liver, seeds_porta = io3d.datasets.generate_synthetic_liver(
)
# seeds
# seeds = np.zeros(data3d.shape, np.int8)
# seeds[40:55, 90:120, 70:110] = 1
# seeds[30:45, 190:200, 40:90] = 2
# [mm] 10 x 10 x 10 # voxelsize_mm = [1, 4, 3]
metadata = {'voxelsize_mm': voxelsize_mm}
oseg = organ_segmentation.OrganSegmentation(None,
data3d=data3d,
metadata=metadata,
seeds=seeds_liver,
working_voxelsize_mm=5,
manualroi=False,
autocrop=False,
**params)
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3("liver")
self.assertGreater(volume, 570000,
"Liver volume should have proper size")
self.assertLess(volume, 640000, "Liver volume should have proper size")
oseg.portalVeinSegmentation(interactivity=False, threshold=180)
volume_porta = oseg.get_segmented_volume_size_mm3("porta")
self.assertGreater(volume_porta, 9000,
"Liver volume should have proper size")
self.assertLess(volume_porta, 11000,
"Liver volume should have proper size")
# import sed3
# ed = sed3.sed3(data3d,
# contour=(oseg.segmentation))
# ed.show()
oseg.saveVesselTree('porta')
def test_export_dicom(self):
"""
Interactivity is stored to file
"""
import io3d
import io3d.datareader
if self.verbose:
print("test_create_iparams")
data_path = os.path.join(lisa.dataset.sample_data_path(),
'liver-orig001.mhd')
seg_path = os.path.join(lisa.dataset.sample_data_path(),
'liver-seg001.mhd')
# load data
oseg = organ_segmentation.OrganSegmentation()
oseg.load_data(datapath=data_path)
oseg.import_segmentation_from_file(seg_path)
# export to dicom
output_datapath = "data3d.dcm"
output_segpath = "segmentation.dcm"
oseg.save_input_dcm(output_datapath)
oseg.save_outputs_dcm(output_segpath)
# check data
data3d_orig, metadata = io3d.datareader.read(data_path,
dataplus_format=False)
data3d_stored, metadata = io3d.datareader.read(output_datapath,
dataplus_format=False)
err_data = np.sum(np.abs(data3d_orig - data3d_stored))
self.assertLess(err_data, 500, "data error")
# check segmentation
seg_orig, metadata = io3d.datareader.read(data_path,
dataplus_format=False)
seg_stored, metadata = io3d.datareader.read(output_datapath,
dataplus_format=False)
err_data = np.sum(np.abs(seg_orig - seg_stored))
self.assertLess(err_data, 500, "segmentation error")
os.remove(output_datapath)
os.remove(output_segpath)
def box_segmentation_template(self, params, noise_sigma=3):
"""
Function uses organ_segmentation for synthetic box object
segmentation.
"""
# dcmdir = os.path.join(path_to_script,'./../sample_data/matlab/examples/sample_data/DICOM/digest_article/') # noqa
# data
img3d = np.random.rand(32, 64, 64) * noise_sigma
img3d[4:24, 12:32, 5:25] = img3d[4:24, 12:32, 5:25] + 30
# seeds
seeds = np.zeros([32, 64, 64], np.int8)
seeds[9:12, 13:29, 18:25] = 1
seeds[9:12, 4:9, 3:32] = 2
# [mm] 10 x 10 x 10 # voxelsize_mm = [1, 4, 3]
voxelsize_mm = [5, 5, 5]
metadata = {'voxelsize_mm': voxelsize_mm}
oseg = organ_segmentation.OrganSegmentation(
None,
data3d=img3d,
metadata=metadata,
seeds=seeds,
working_voxelsize_mm=10,
manualroi=False,
**params
)
# oseg.seeds = seeds
# oseg.make_gc()
# manual seeds setting
from PyQt5.QtWidgets import QApplication
app = QApplication(sys.argv)
# oseg.interactivity()
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# import pdb; pdb.set_trace()
# mel by to být litr. tedy milion mm3
self.assertGreater(volume, 800000)
self.assertLess(volume, 1100000)
def test_add_seeds_mm(self):
"""
Function uses organ_segmentation object for segmentation
"""
dcmdir = os.path.join(
lisa.dataset.sample_data_path(),
'matlab/examples/sample_data/DICOM/digest_article/'
# path_to_script,
# './../sample_data/matlab/examples/sample_data/DICOM/digest_article/'
)
oseg = organ_segmentation.OrganSegmentation(dcmdir,
working_voxelsize_mm=4,
manualroi=False)
oseg.add_seeds_mm([80], [120], [120], 1, 25)
oseg.add_seeds_mm([80], [40], [130], 2, 25)
# pro kontrolu lze odkomentovat
# from PyQt4.QtGui import QApplication
# app = QApplication(sys.argv)
# oseg.interactivity()
oseg.ninteractivity()
volume = oseg.get_segmented_volume_size_mm3()
# import pdb; pdb.set_trace()
# mel by to být litr. tedy milion mm3
self.assertGreater(volume, 800000)
self.assertLess(volume, 1200000)
# roi_mm = [[3, 3, 3], [150, 150, 50]]
# oseg.ni_set_roi()
# coordinates_mm = [[110, 50, 30], [10, 10, 10]]
# label = [1, 2]
# radius = [5, 5]
# oseg.ni_set_seeds(coordinates_mm, label, radius)
# oseg.make_segmentation()
# oseg.noninteractivity()
pass
def test_sync_paul(self):
"""
sync with paul account
"""
path_to_paul = lisa.lisa_data.path('sync', 'paul')
if os.path.exists(path_to_paul):
remove_read_only_flag_on_win32(path_to_paul)
# handleRemoveReadonly je asi zbytečné
shutil.rmtree(path_to_paul,
onerror=handleRemoveReadonly,
ignore_errors=False)
oseg = organ_segmentation.OrganSegmentation(None)
oseg.sync_lisa_data('paul', 'P4ul')
file_path = lisa.lisa_data.path('sync', 'paul', 'from_server',
'test.txt')
logger.debug('file_path %s', file_path)
self.assertTrue(os.path.exists(file_path))
def test_real_data_segmentation(self):
import lisa.dataset
app = QApplication(sys.argv)
dcmdir = os.path.join(lisa.dataset.sample_data_path(), 'jatra_5mm')
oseg = organ_segmentation.OrganSegmentation(dcmdir,
working_voxelsize_mm=4)
oseg.add_seeds_mm([81], [120], [120],
label=1, radius=30)
oseg.add_seeds_mm([81], [170, 220, 250], [250, 250, 200],
label=2, radius=30)
oseg.add_seeds_mm([100], [170], [140],
label=10, radius=5)
# oseg.interactivity(min_val=-200, max_val=200)
oseg.ninteractivity()
ed = sed3.sed3(oseg.data3d, contour=oseg.segmentation, seeds=oseg.seeds)
ed.show()
oseg.portalVeinSegmentation(seeds=(oseg.seeds==10))
def export_seg_to_file():
fnout = Path(__file__).parent / "test_export_segmentation.mhd"
if fnout.exists():
os.remove(fnout)
data3d, segm, voxelsize_mm, slab, seeds_liver, seeds_porta = io3d.datasets.generate_synthetic_liver()
metadata = {'voxelsize_mm': voxelsize_mm}
oseg = organ_segmentation.OrganSegmentation(
None,
data3d=data3d,
metadata=metadata,
seeds=seeds_liver,
working_voxelsize_mm=5,
manualroi=False,
autocrop=False,
)
oseg.export_segmentation_to_file(fnout)
assert fnout.exists()
def test_roi(self):
"""
Test setting of ROI. It is in pixels, not in mm
"""
img3d = (np.random.rand(30, 30, 30)*10).astype(np.int16)
seeds = (np.zeros(img3d.shape)).astype(np.int8)
segmentation = (np.zeros(img3d.shape)).astype(np.int8)
segmentation[10:25, 4:24, 2:16] = 1
img3d = img3d + segmentation*20
seeds[12:18, 9:16, 3:6] = 1
seeds[19:22, 21:27, 19:21] = 2
roi = [[7, 27], [2, 29], [0, 26]]
# seeds = seeds[7:27, 2:29, 0:26]
voxelsize_mm = [5, 5, 5]
metadata = {'voxelsize_mm': voxelsize_mm}
oseg = organ_segmentation.OrganSegmentation(
None,
data3d=img3d,
metadata=metadata,
seeds=seeds,
roi=roi,
working_voxelsize_mm=5,
manualroi=False)
# from PyQt4.QtGui import QApplication
# app = QApplication(sys.argv)
# oseg.interactivity(min_val=0, max_val=30)
oseg.ninteractivity()
datap = oseg.export()
volume = oseg.get_segmented_volume_size_mm3()
self.assertGreater(volume, 500000)
self.assertIn('data3d', datap.keys())
self.assertIn('voxelsize_mm', datap.keys())
