def show(data3d_a_path, sliver_seg_path, ourSegmentation):
reader = datareader.DataReader()
#data3d_a_path = os.path.join(path_to_script, data3d_a_path)
datap_a = reader.Get3DData(data3d_a_path,
dataplus_format=True)
if 'orig_shape' in datap_a.keys():
# pklz
data3d_a = qmisc.uncrop(datap_a['data3d'], datap_a['crinfo'],
datap_a['orig_shape'])
else:
#dicom
data3d_a = datap_a['data3d']
if sliver_seg_path is not None:
sliver_seg_path = os.path.join(path_to_script, sliver_seg_path)
sliver_datap = reader.Get3DData(sliver_seg_path,
dataplus_format=True)
if 'segmentation' in sliver_datap.keys():
sliver_seg = sliver_datap['segmentation']
sliver_seg = qmisc.uncrop(sliver_datap['segmentation'],
sliver_datap['crinfo'],
data3d_a.shape)
else:
sliver_seg = sliver_datap['data3d']
pyed = sed3.sed3(data3d_a, contour=sliver_seg)
print "Sliver07 segmentation"
pyed.show()
if ourSegmentation != None:
ourSegmentation = os.path.join(path_to_script, ourSegmentation)
datap_our = reader.Get3DData(ourSegmentation, dataplus_format=True)
#data_our = misc.obj_from_file(ourSegmentation, 'pickle')
#data3d_our = data_our['segmentation']
our_seg = qmisc.uncrop(datap_our['segmentation'], datap_our['crinfo'],
data3d_a.shape)
if ourSegmentation != None:
pyed = sed3.sed3(data3d_a, contour=our_seg)
print "Our segmentation"
pyed.show()
if (ourSegmentation is not None) and (sliver_seg_path is not None):
diff = (our_seg.astype(np.int8) - sliver_seg)
diff[diff==-1] = 2
#import ipdb; ipdb.set_trace() # BREAKPOINT
pyed = sed3.sed3(data3d_a, contour=our_seg,
seeds=diff)
print "Sliver07 and our segmentation differences"
pyed.show()
def main():
parser = argparse.ArgumentParser(
description=__doc__) # 'Simple VTK Viewer')
parser.add_argument('-i', '--inputfile', default=None, help='File as .pkl')
parser.add_argument('-o',
'--outputfile',
default=None,
help='Output file. Filetype is given by extension.')
parser.add_argument('-k',
'--key',
default='data3d',
help='Which key should be writen to output file. \
Default is "data3d". You can use "segmentation"')
args = parser.parse_args()
data = misc.obj_from_file(args.inputfile, filetype='pickle')
data3d_uncrop = qmisc.uncrop(data[args.key], data['crinfo'],
data['orig_shape'])
#import ipdb; ipdb.set_trace() # BREAKPOINT
import SimpleITK as sitk
sitk_img = sitk.GetImageFromArray(data3d_uncrop.astype(np.uint16),
isVector=True)
sitk.WriteImage(sitk_img, args.outputfile)
print(
"Warning: .mhd and .raw format has corupted metadta. You can edit it manually."
)
def show(data3d_a_path, sliver_seg_path, ourSegmentation):
reader = datareader.DataReader()
#data3d_a_path = os.path.join(path_to_script, data3d_a_path)
datap_a = reader.Get3DData(data3d_a_path, dataplus_format=True)
if 'orig_shape' in datap_a.keys():
# pklz
data3d_a = qmisc.uncrop(datap_a['data3d'], datap_a['crinfo'],
datap_a['orig_shape'])
else:
#dicom
data3d_a = datap_a['data3d']
if sliver_seg_path is not None:
sliver_seg_path = os.path.join(path_to_script, sliver_seg_path)
sliver_datap = reader.Get3DData(sliver_seg_path, dataplus_format=True)
if 'segmentation' in sliver_datap.keys():
sliver_seg = sliver_datap['segmentation']
sliver_seg = qmisc.uncrop(sliver_datap['segmentation'],
sliver_datap['crinfo'], data3d_a.shape)
else:
sliver_seg = sliver_datap['data3d']
pyed = sed3.sed3(data3d_a, contour=sliver_seg)
print("Sliver07 segmentation")
pyed.show()
if ourSegmentation != None:
ourSegmentation = os.path.join(path_to_script, ourSegmentation)
datap_our = reader.Get3DData(ourSegmentation, dataplus_format=True)
#data_our = misc.obj_from_file(ourSegmentation, 'pickle')
#data3d_our = data_our['segmentation']
our_seg = qmisc.uncrop(datap_our['segmentation'], datap_our['crinfo'],
data3d_a.shape)
if ourSegmentation != None:
pyed = sed3.sed3(data3d_a, contour=our_seg)
print("Our segmentation")
pyed.show()
if (ourSegmentation is not None) and (sliver_seg_path is not None):
diff = (our_seg.astype(np.int8) - sliver_seg)
diff[diff == -1] = 2
#import ipdb; ipdb.set_trace() # BREAKPOINT
pyed = sed3.sed3(data3d_a, contour=our_seg, seeds=diff)
print("Sliver07 and our segmentation differences")
pyed.show()
def test_crop_and_uncrop(self):
shape = [10, 10, 5]
img_in = np.random.random(shape)
crinfo = [[2, 8], [3, 9], [2, 5]]
img_cropped = qmisc.crop(img_in, crinfo)
img_uncropped = qmisc.uncrop(img_cropped, crinfo, shape)
self.assertTrue(img_uncropped[4, 4, 3] == img_in[4, 4, 3])
def sliver_compare_with_other_volume(self, segmentation_datap):
"""
Compares actual Lisa data with other which are given by
segmentation_datap. That means
segmentation_datap = {
'segmentation': 3d np.array,
'crinfo': information about crop (optional)
}
"""
# if there is no segmentation, data can be stored in data3d. It is the
# way how are data stored in sliver.
if 'segmentation' in segmentation_datap.keys():
segm_key = 'segmentation'
else:
segm_key = 'data3d'
if 'crinfo' in segmentation_datap.keys():
data3d_segmentation = qmisc.uncrop(
segmentation_datap[segm_key],
segmentation_datap['crinfo'],
self.orig_shape)
else:
data3d_segmentation = segmentation_datap[segm_key]
pass
# now we can uncrop actual Lisa data
data3d_segmentation_actual = qmisc.uncrop(
self.segmentation,
self.crinfo,
self.orig_shape)
evaluation = volumetry_evaluation.compare_volumes(
data3d_segmentation_actual,
data3d_segmentation,
self.voxelsize_mm
)
score = volumetry_evaluation.sliver_score_one_couple(evaluation)
segdiff = qmisc.crop(
((data3d_segmentation) - data3d_segmentation_actual),
self.crinfo)
return evaluation, score, segdiff
def saveOverlayToDicomCopy(input_dcmfilelist, output_dicom_dir, overlays,
crinfo, orig_shape):
""" Save overlay to dicom. """
import datawriter as dwriter
if not os.path.exists(output_dicom_dir):
os.mkdir(output_dicom_dir)
# uncrop all overlays
for key in overlays:
overlays[key] = qmisc.uncrop(overlays[key], crinfo, orig_shape)
dw = dwriter.DataWriter()
dw.DataCopyWithOverlay(input_dcmfilelist, output_dicom_dir, overlays)
def get_model(self, crinfo, image_shape):
"""
:param image_shape: Size of output image
:param crinfo: Array with min and max index of object for each axis.
[[minx, maxx], [miny, maxy], [minz, maxz]]
"""
# Průměrování
mdl = self.model / self.data_number
print(mdl.shape)
print(crinfo)
# mdl_res = io3d.misc.resize_to_shape(mdl, crinfo[0][]
uncr = qmisc.uncrop(mdl, crinfo, image_shape, resize=True)
return uncr
def saveOverlayToDicomCopy(input_dcmfilelist, output_dicom_dir, overlays,
crinfo, orig_shape):
""" Save overlay to dicom. """
import datawriter as dwriter
if not os.path.exists(output_dicom_dir):
os.mkdir(output_dicom_dir)
# uncrop all overlays
for key in overlays:
overlays[key] = qmisc.uncrop(overlays[key], crinfo, orig_shape)
dw = dwriter.DataWriter()
dw.DataCopyWithOverlay(input_dcmfilelist, output_dicom_dir, overlays)
def get_model(self, crinfo, image_shape):
"""
:param image_shape: Size of output image
:param crinfo: Array with min and max index of object for each axis.
[[minx, maxx], [miny, maxy], [minz, maxz]]
"""
# Průměrování
mdl = self.model / self.data_number
print mdl.shape
print crinfo
# mdl_res = qmisc.resize_to_shape(mdl, crinfo[0][]
uncr = qmisc.uncrop(mdl, crinfo, image_shape, resize=True)
return uncr
def test_multiple_crop_and_uncrop(self):
"""
test combination of multiple crop
"""
shape = [10, 10, 5]
img_in = np.random.random(shape)
crinfo1 = [[2, 8], [3, 9], [2, 5]]
crinfo2 = [[2, 5], [1, 4], [1, 2]]
img_cropped = qmisc.crop(img_in, crinfo1)
img_cropped = qmisc.crop(img_cropped, crinfo2)
crinfo_combined = qmisc.combinecrinfo(crinfo1, crinfo2)
img_uncropped = qmisc.uncrop(img_cropped, crinfo_combined, shape)
self.assertTrue(img_uncropped[4, 4, 3] == img_in[4, 4, 3])
def main():
parser = argparse.ArgumentParser(description=__doc__) # 'Simple VTK Viewer')
parser.add_argument('-i','--inputfile', default=None,
help='File as .pkl')
parser.add_argument('-o','--outputfile', default=None,
help='Output file. Filetype is given by extension.')
parser.add_argument('-k','--key', default='data3d',
help='Which key should be writen to output file. \
Default is "data3d". You can use "segmentation"')
args = parser.parse_args()
data = misc.obj_from_file(args.inputfile, filetype = 'pickle')
data3d_uncrop = qmisc.uncrop(data[args.key], data['crinfo'], data['orig_shape'])
#import ipdb; ipdb.set_trace() # BREAKPOINT
import SimpleITK as sitk
sitk_img = sitk.GetImageFromArray(data3d_uncrop.astype(np.uint16), isVector=True)
sitk.WriteImage(sitk_img, args.outputfile)
print "Warning: .mhd and .raw format has corupted metadta. You can edit it manually."
def eval_all_from_dataset_metadata(inputdata, visualization=False):
"""
set metadata
"""
evaluation_all = {
'file1': [],
'file2': [],
'volume1_mm3': [],
'volume2_mm3': [],
'err1_mm3': [],
'err2_mm3': [],
'err1_percent': [],
'err2_percent': [],
'voe': [],
'vd': [],
'avgd': [],
'rmsd': [],
'processing_time': [],
'organ_interactivity_counter': [],
'maxd': []
}
for i in range(0, len(inputdata['data'])):
reader = datareader.DataReader()
data3d_a_path = os.path.join(inputdata['basedir'],
inputdata['data'][i]['sliverseg'])
data3d_a, metadata_a = reader.Get3DData(data3d_a_path)
print "inputdata ", inputdata['data'][i].keys()
try:
# if there is defined overlay
data3d_a = reader.GetOverlay()[inputdata['data'][i][
'overlay_number']]
logger.info('overlay loaded')
print 'overlay loaded'
except:
logger.debug("overlay not loaded")
pass
logger.debug('data A shape ' + str(data3d_a.shape))
data3d_b_path = os.path.join(inputdata['basedir'],
inputdata['data'][i]['ourseg'])
obj_b = misc.obj_from_file(data3d_b_path, filetype='pickle')
#data_b, metadata_b = reader.Get3DData(data3d_b_path)
data3d_b = qmisc.uncrop(obj_b['segmentation'],
obj_b['crinfo'], data3d_a.shape)
#import pdb; pdb.set_trace()
#data3d_a = (data3d_a > 1024).astype(np.int8)
data3d_a = (data3d_a > 0).astype(np.int8)
data3d_b = (data3d_b > 0).astype(np.int8)
if visualization:
pyed = py3DSeedEditor.py3DSeedEditor(data3d_a, # + (4 * data3d_b)
contour=data3d_b)
pyed.show()
evaluation_one = compare_volumes(data3d_a, data3d_b,
metadata_a['voxelsize_mm'])
evaluation_all['file1'].append(data3d_a_path)
evaluation_all['file2'].append(data3d_b_path)
evaluation_all['volume1_mm3'].append(evaluation_one['volume1_mm3'])
evaluation_all['volume2_mm3'].append(evaluation_one['volume2_mm3'])
evaluation_all['err1_mm3'].append(evaluation_one['err1_mm3'])
evaluation_all['err2_mm3'].append(evaluation_one['err2_mm3'])
evaluation_all['err1_percent'].append(evaluation_one['err1_percent'])
evaluation_all['err2_percent'].append(evaluation_one['err2_percent'])
evaluation_all['voe'].append(evaluation_one['voe'])
evaluation_all['vd'].append(evaluation_one['vd'])
evaluation_all['avgd'].append(evaluation_one['avgd'])
evaluation_all['rmsd'].append(evaluation_one['rmsd'])
evaluation_all['maxd'].append(evaluation_one['maxd'])
if 'processing_time' in obj_b.keys():
#this is only for compatibility with march2014 data
processing_time = obj_b['processing_time']
organ_interactivity_counter = obj_b['organ_interactivity_counter']
else:
processing_time = obj_b['processing_information']['organ_segmentation']['processing_time'] # noqa
organ_interactivity_counter = obj_b['processing_information']['organ_segmentation']['organ_interactivity_counter'] # noqa
evaluation_all['processing_time'].append(processing_time)
evaluation_all['organ_interactivity_counter'].append(
organ_interactivity_counter)
return evaluation_all
def eval_all_from_dataset_metadata(inputdata, visualization=False,
special_evaluation_function=None):
"""
set metadata
"""
evaluation_all = {
'file1': [],
'file2': [],
'volume1_mm3': [],
'volume2_mm3': [],
'err1_mm3': [],
'err2_mm3': [],
'err1_percent': [],
'err2_percent': [],
'voe': [],
'vd': [],
'avgd': [],
'rmsd': [],
'processing_time': [],
'organ_interactivity_counter': [],
'maxd': []
}
for i in range(0, len(inputdata['data'])):
reader = datareader.DataReader()
data3d_a_path = os.path.join(inputdata['basedir'],
inputdata['data'][i]['sliverseg'])
data3d_a, metadata_a = reader.Get3DData(data3d_a_path)
print "inputdata ", inputdata['data'][i].values()
try:
# if there is defined overlay
data3d_a = reader.GetOverlay()[inputdata['data'][i][
'overlay_number']]
logger.info('overlay loaded')
print 'overlay loaded'
except:
logger.debug("overlay not loaded")
pass
logger.debug('data A shape ' + str(data3d_a.shape))
data3d_b_path = os.path.join(inputdata['basedir'],
inputdata['data'][i]['ourseg'])
obj_b = misc.obj_from_file(data3d_b_path, filetype='pickle')
# data_b, metadata_b = reader.Get3DData(data3d_b_path)
if 'crinfo' in obj_b.keys():
data3d_b = qmisc.uncrop(obj_b['segmentation'],
obj_b['crinfo'], data3d_a.shape)
else:
data3d_b = obj_b['segmentation']
# import pdb; pdb.set_trace()
# data3d_a = (data3d_a > 1024).astype(np.int8)
data3d_a = (data3d_a > 0).astype(np.int8)
data3d_b = (data3d_b > 0).astype(np.int8)
if visualization:
pyed = sed3.sed3(data3d_a, # + (4 * data3d_b)
contour=data3d_b)
pyed.show()
evaluation_one = compare_volumes(data3d_a, data3d_b,
metadata_a['voxelsize_mm'])
if special_evaluation_function is not None:
evaluation_one.update(
special_evaluation_function(
data3d_a, data3d_b, metadata_a['voxelsize_mm']
))
evaluation_all['file1'].append(data3d_a_path)
evaluation_all['file2'].append(data3d_b_path)
for key in evaluation_one.keys():
if key not in evaluation_all.keys():
evaluation_all[key] = []
evaluation_all[key].append(evaluation_one[key])
# evaluation_all['volume1_mm3'].append(evaluation_one['volume1_mm3'])
# evaluation_all['volume2_mm3'].append(evaluation_one['volume2_mm3'])
# evaluation_all['err1_mm3'].append(evaluation_one['err1_mm3'])
# evaluation_all['err2_mm3'].append(evaluation_one['err2_mm3'])
# evaluation_all['err1_percent'].append(evaluation_one['err1_percent'])
# evaluation_all['err2_percent'].append(evaluation_one['err2_percent'])
# evaluation_all['voe'].append(evaluation_one['voe'])
# evaluation_all['vd'].append(evaluation_one['vd'])
# evaluation_all['avgd'].append(evaluation_one['avgd'])
# evaluation_all['rmsd'].append(evaluation_one['rmsd'])
# evaluation_all['maxd'].append(evaluation_one['maxd'])
if 'processing_time' in obj_b.keys():
# this is only for compatibility with march2014 data
processing_time = obj_b['processing_time']
organ_interactivity_counter = obj_b['organ_interactivity_counter']
else:
try:
processing_time = obj_b['processing_information']['organ_segmentation']['processing_time'] # noqa
organ_interactivity_counter = obj_b['processing_information']['organ_segmentation'][
'organ_interactivity_counter'] # noqa
except:
processing_time = 0
organ_interactivity_counter = 0
evaluation_all['processing_time'].append(processing_time)
evaluation_all['organ_interactivity_counter'].append(
organ_interactivity_counter)
return evaluation_all
def resection_portal_vein_new(data,
interactivity=False,
seeds=None,
label=10,
vein=6,
**kwargs):
"""
New function for portal vein segmentation
:param data:
:param interactivity:
:param seeds:
:param kwargs:
:return:
"""
# ed = sed3.sed3(a)
# ed.show()
# from PyQt4 import QtGui
# from PyQt4.QtGui import QApplication, QMainWindow, QVBoxLayout, QHBoxLayout, QLabel, QPushButton, QFrame, \
# QFont, QPixmap, QFileDialog
#
# window = QtGui.QWidget()
# mainLayout = QVBoxLayout()
# window.setLayout(mainLayout)
# mainLayout.addWidget(sed3.sed3qtWidget(data['data3d'], contour=data['segmentation']))
# zachovani puvodnich dat
segmentation = data["segmentation"]
data3d = data["data3d"]
# data pouze se segmentacemi
segm = ((data["segmentation"] == label) * label +
(data["segmentation"] == vein) * vein)
# ufiknutí segmentace
crinfo = qmisc.crinfo_from_specific_data(segm, [0])
data["segmentation"] = qmisc.crop(segm, crinfo)
data["data3d"] = qmisc.crop(data3d, crinfo)
# @TODO zde nahradit střeve čímkoliv smysluplnějším
if interactivity:
print("Select cut")
# seeds = cut_editor_old(data)
seeds = cut_editor_old(data)
elif seeds is None:
logger.error('seeds is None and interactivity is False')
return None
lab, cut = split_vessel(data, seeds)
segm, dist1, dist2 = split_organ_by_two_vessels(data, lab)
# jatra rozdeleny na 3 kusy
a = morphology.label(segm, background=0)
### podmínka nefunguje
if 3 in a: # zda se v segmentaci objevuje 3. cast
print "slape :) :) :P"
a_index = velikosti(segm)
print a_index
i = nejnizsi(a_index[0], a_index[1], a_index[2])
segm = ((a == i) * (segm == 1).astype('int8') + (a != i) *
(segm == 2).astype('int8') + (segm != 0).astype('int8'))
# TODO split this function from visualization
data = virtual_resection_visualization(data,
segm,
dist1,
dist2,
cut,
interactivity=interactivity)
# vrácení původních dat a spojení s upravenými daty
data["data3d"] = data3d
data["segmentation"] = qmisc.uncrop(
data["segmentation"], crinfo,
(len(segmentation), len(segmentation[0]), len(segmentation[0])))
#segmentation = segmentation == vein
data["segmentation"] = (
data["segmentation"] +
(segmentation != label) * segmentation) - (segmentation == vein) * vein
return data
