def filtering( self, inputs, outputs, length, cortex_only ):
'''
Filter the mapped fibers.
'''
# check if we have all required input data
# we need at least:
# - outputs['fibers_mapped'] == Track file in T1 space with mapped scalars
if not os.path.exists( outputs['fibers_mapped'] ):
c.error( Colors.RED + 'Could not find ' + Colors.YELLOW + outputs['fibers_mapped'] + Colors.RED + ' but we really need it to start with stage 4!!' + Colors._CLEAR )
sys.exit( 2 )
# find the order of the mapped scalars
header = io.loadTrkHeaderOnly( outputs['fibers_mapped'] )
scalars = list( header['scalar_name'] )
# split the length range
length = length.split( ' ' )
min_length = int( length[0] )
max_length = int( length[1] )
# length filtering
c.info( Colors.YELLOW + ' Filtering ' + Colors.PURPLE + 'fiber length' + Colors.YELLOW + ' to be ' + Colors.PURPLE + '>' + str( min_length ) + ' and <' + str( max_length ) + Colors.YELLOW + ' for ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped'] )[1] + Colors.YELLOW + ' and store as ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped_length_filtered'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
fyborg.fyborg( outputs['fibers_mapped'], outputs['fibers_mapped_length_filtered'], [fyborg.FyFilterLengthAction( scalars.index( 'length' ), min_length, max_length )] )
header = io.loadTrkHeaderOnly( outputs['fibers_mapped_length_filtered'] )
new_count = header['n_count']
c.info( Colors.YELLOW + ' Number of tracks after ' + Colors.PURPLE + 'length filtering' + Colors.YELLOW + ': ' + str( new_count ) + Colors.YELLOW + Colors._CLEAR )
if cortex_only:
# special cortex filtering
c.info( Colors.YELLOW + ' Filtering for ' + Colors.PURPLE + 'valid cortex structures' + Colors.YELLOW + ' in ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped_length_filtered'] )[1] + Colors.YELLOW + ' and store as ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped_length_filtered_cortex_only'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
c.info( Colors.PURPLE + ' Conditions for valid fibers:' + Colors._CLEAR )
c.info( Colors.PURPLE + ' 1.' + Colors.YELLOW + ' The fiber track has to pass through the cerebral white matter. (Label values: ' + Colors.PURPLE + '[2, 41]' + Colors.YELLOW + ')' + Colors._CLEAR )
c.info( Colors.PURPLE + ' 2.' + Colors.YELLOW + ' The fiber track shall only touch sub-cortical structures not more than ' + Colors.PURPLE + '5 times' + Colors.YELLOW + '. (Label values: ' + Colors.PURPLE + '[10, 49, 16, 28, 60, 4, 43]' + Colors.YELLOW + ')' + Colors._CLEAR )
c.info( Colors.PURPLE + ' 3.' + Colors.YELLOW + ' The track shall not pass through the corpus callosum (Labels: ' + Colors.PURPLE + '[251, 255]' + Colors.YELLOW + ') and end in the same hemisphere (Labels: ' + Colors.PURPLE + '[1000-1035]' + Colors.YELLOW + ' for left, ' + Colors.PURPLE + '[2000-2035]' + Colors.YELLOW + ' for right).' + Colors._CLEAR )
fyborg.fyborg( outputs['fibers_mapped_length_filtered'], outputs['fibers_mapped_length_filtered_cortex_only'], [fyborg.FyFilterCortexAction( scalars.index( 'segmentation' ) )] )
header = io.loadTrkHeaderOnly( outputs['fibers_mapped_length_filtered_cortex_only'] )
new_count = header['n_count']
c.info( Colors.YELLOW + ' Number of tracks after ' + Colors.PURPLE + 'cortex filtering' + Colors.YELLOW + ': ' + str( new_count ) + Colors.YELLOW + Colors._CLEAR )
c.info( Colors.YELLOW + ' Copied filtered tracks from ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped_length_filtered_cortex_only'] )[1] + Colors.YELLOW + ' to ' + Colors.PURPLE + os.path.split( outputs['fibers_final'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
shutil.copyfile( outputs['fibers_mapped_length_filtered_cortex_only'], outputs['fibers_final'] )
else:
c.info( Colors.YELLOW + ' Info: ' + Colors.PURPLE + 'Cortical _and_ sub-cortical structures ' + Colors.YELLOW + 'will be included..' + Colors._CLEAR )
c.info( Colors.YELLOW + ' Copied filtered tracks from ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped_length_filtered'] )[1] + Colors.YELLOW + ' to ' + Colors.PURPLE + os.path.split( outputs['fibers_final'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
shutil.copyfile( outputs['fibers_mapped_length_filtered'], outputs['fibers_final'] )
def mapping( self, inputs, outputs, radius ):
'''
Map all detected scalar volumes to each fiber.
'''
# check if we have all required input data
# we need at least:
# - outputs['fibers'] == Track file in T1 space
# - outputs['segmentation'] == Label Map
if not os.path.exists( outputs['fibers'] ):
c.error( Colors.RED + 'Could not find ' + Colors.YELLOW + outputs['fibers'] + Colors.RED + ' but we really need it to start with stage 3!!' + Colors._CLEAR )
sys.exit( 2 )
if not os.path.exists( outputs['segmentation'] ):
c.error( Colors.RED + 'Could not find ' + Colors.YELLOW + outputs['segmentation'] + Colors.RED + ' but we really need it to start with stage 3!!' + Colors._CLEAR )
sys.exit( 2 )
actions = []
for i in inputs:
if i == 'fibers' or i == 'segmentation' or i == 'T1' or i == 'b0':
# we do not map these
continue
if not os.path.exists( outputs[i + '_T1_space'] ):
# we can't map this since we didn't find the file
continue
# for normal scalars: append it to the actions
actions.append( fyborg.FyMapAction( i, outputs[i + '_T1_space'] ) )
c.info( Colors.YELLOW + ' Configuring mapping of ' + Colors.PURPLE + os.path.split( outputs[i + '_T1_space'] )[1] + Colors.YELLOW + ' to ' + Colors.PURPLE + os.path.split( outputs['fibers'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
# now the segmentation with the lookaround radius
actions.append( fyborg.FyRadiusMapAction( 'segmentation', outputs['segmentation'], radius ) )
c.info( Colors.YELLOW + ' Configuring mapping of ' + Colors.PURPLE + os.path.split( outputs['segmentation'] )[1] + Colors.YELLOW + ' to ' + Colors.PURPLE + os.path.split( outputs['fibers'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
# and also the fiber length
actions.append( fyborg.FyLengthAction() )
c.info( Colors.YELLOW + ' Configuring mapping of ' + Colors.PURPLE + 'fiber length' + Colors.YELLOW + ' to ' + Colors.PURPLE + os.path.split( outputs['fibers'] )[1] + Colors.YELLOW + '!' + Colors._CLEAR )
# run, forest, run!!
c.info( Colors.YELLOW + ' Performing configured mapping for ' + Colors.PURPLE + os.path.split( outputs['fibers'] )[1] + Colors.YELLOW + ' and storing as ' + Colors.PURPLE + os.path.split( outputs['fibers_mapped'] )[1] + Colors.YELLOW + ' (~ 30 minutes)!' + Colors._CLEAR )
if self.__debug:
fyborg.fyborg( outputs['fibers'], outputs['fibers_mapped'], actions, 'debug' )
else:
fyborg.fyborg( outputs['fibers'], outputs['fibers_mapped'], actions )
def filtering(self, inputs, outputs, length, cortex_only):
'''
Filter the mapped fibers.
'''
# check if we have all required input data
# we need at least:
# - outputs['fibers_mapped'] == Track file in T1 space with mapped scalars
if not os.path.exists(outputs['fibers_mapped']):
c.error(Colors.RED + 'Could not find ' + Colors.YELLOW +
outputs['fibers_mapped'] + Colors.RED +
' but we really need it to start with stage 4!!' +
Colors._CLEAR)
sys.exit(2)
# find the order of the mapped scalars
header = io.loadTrkHeaderOnly(outputs['fibers_mapped'])
scalars = list(header['scalar_name'])
# split the length range
length = length.split(' ')
min_length = int(length[0])
max_length = int(length[1])
# length filtering
c.info(Colors.YELLOW + ' Filtering ' + Colors.PURPLE +
'fiber length' + Colors.YELLOW + ' to be ' + Colors.PURPLE +
'>' + str(min_length) + ' and <' + str(max_length) +
Colors.YELLOW + ' for ' + Colors.PURPLE +
os.path.split(outputs['fibers_mapped'])[1] + Colors.YELLOW +
' and store as ' + Colors.PURPLE +
os.path.split(outputs['fibers_mapped_length_filtered'])[1] +
Colors.YELLOW + '!' + Colors._CLEAR)
fyborg.fyborg(outputs['fibers_mapped'],
outputs['fibers_mapped_length_filtered'], [
fyborg.FyFilterLengthAction(scalars.index('length'),
min_length, max_length)
])
header = io.loadTrkHeaderOnly(outputs['fibers_mapped_length_filtered'])
new_count = header['n_count']
c.info(Colors.YELLOW + ' Number of tracks after ' + Colors.PURPLE +
'length filtering' + Colors.YELLOW + ': ' + str(new_count) +
Colors.YELLOW + Colors._CLEAR)
if cortex_only:
# special cortex filtering
c.info(
Colors.YELLOW + ' Filtering for ' + Colors.PURPLE +
'valid cortex structures' + Colors.YELLOW + ' in ' +
Colors.PURPLE +
os.path.split(outputs['fibers_mapped_length_filtered'])[1] +
Colors.YELLOW + ' and store as ' + Colors.PURPLE +
os.path.split(
outputs['fibers_mapped_length_filtered_cortex_only'])[1] +
Colors.YELLOW + '!' + Colors._CLEAR)
c.info(Colors.PURPLE + ' Conditions for valid fibers:' +
Colors._CLEAR)
c.info(
Colors.PURPLE + ' 1.' + Colors.YELLOW +
' The fiber track has to pass through the cerebral white matter. (Label values: '
+ Colors.PURPLE + '[2, 41]' + Colors.YELLOW + ')' +
Colors._CLEAR)
c.info(
Colors.PURPLE + ' 2.' + Colors.YELLOW +
' The fiber track shall only touch sub-cortical structures not more than '
+ Colors.PURPLE + '5 times' + Colors.YELLOW +
'. (Label values: ' + Colors.PURPLE +
'[10, 49, 16, 28, 60, 4, 43]' + Colors.YELLOW + ')' +
Colors._CLEAR)
c.info(
Colors.PURPLE + ' 3.' + Colors.YELLOW +
' The track shall not pass through the corpus callosum (Labels: '
+ Colors.PURPLE + '[251, 255]' + Colors.YELLOW +
') and end in the same hemisphere (Labels: ' + Colors.PURPLE +
'[1000-1035]' + Colors.YELLOW + ' for left, ' + Colors.PURPLE +
'[2000-2035]' + Colors.YELLOW + ' for right).' + Colors._CLEAR)
fyborg.fyborg(
outputs['fibers_mapped_length_filtered'],
outputs['fibers_mapped_length_filtered_cortex_only'],
[fyborg.FyFilterCortexAction(scalars.index('segmentation'))])
header = io.loadTrkHeaderOnly(
outputs['fibers_mapped_length_filtered_cortex_only'])
new_count = header['n_count']
c.info(Colors.YELLOW + ' Number of tracks after ' +
Colors.PURPLE + 'cortex filtering' + Colors.YELLOW + ': ' +
str(new_count) + Colors.YELLOW + Colors._CLEAR)
c.info(
Colors.YELLOW + ' Copied filtered tracks from ' +
Colors.PURPLE + os.path.split(
outputs['fibers_mapped_length_filtered_cortex_only'])[1] +
Colors.YELLOW + ' to ' + Colors.PURPLE +
os.path.split(outputs['fibers_final'])[1] + Colors.YELLOW +
'!' + Colors._CLEAR)
shutil.copyfile(
outputs['fibers_mapped_length_filtered_cortex_only'],
outputs['fibers_final'])
else:
c.info(Colors.YELLOW + ' Info: ' + Colors.PURPLE +
'Cortical _and_ sub-cortical structures ' + Colors.YELLOW +
'will be included..' + Colors._CLEAR)
c.info(Colors.YELLOW + ' Copied filtered tracks from ' +
Colors.PURPLE +
os.path.split(outputs['fibers_mapped_length_filtered'])[1] +
Colors.YELLOW + ' to ' + Colors.PURPLE +
os.path.split(outputs['fibers_final'])[1] + Colors.YELLOW +
'!' + Colors._CLEAR)
shutil.copyfile(outputs['fibers_mapped_length_filtered'],
outputs['fibers_final'])
def mapping(self, inputs, outputs, radius):
'''
Map all detected scalar volumes to each fiber.
'''
# check if we have all required input data
# we need at least:
# - outputs['fibers'] == Track file in T1 space
# - outputs['segmentation'] == Label Map
if not os.path.exists(outputs['fibers']):
c.error(Colors.RED + 'Could not find ' + Colors.YELLOW +
outputs['fibers'] + Colors.RED +
' but we really need it to start with stage 3!!' +
Colors._CLEAR)
sys.exit(2)
if not os.path.exists(outputs['segmentation']):
c.error(Colors.RED + 'Could not find ' + Colors.YELLOW +
outputs['segmentation'] + Colors.RED +
' but we really need it to start with stage 3!!' +
Colors._CLEAR)
sys.exit(2)
actions = []
for i in inputs:
if i == 'fibers' or i == 'segmentation' or i == 'T1' or i == 'b0' or i == 'T1toB0matrix' or i == 'b0_resampled':
# we do not map these
continue
if not os.path.exists(outputs[i]):
# we can't map this since we didn't find the file
continue
# for normal scalars: append it to the actions
actions.append(fyborg.FyMapAction(i, outputs[i]))
c.info(Colors.YELLOW + ' Configuring mapping of ' +
Colors.PURPLE + os.path.split(outputs[i])[1] +
Colors.YELLOW + ' to ' + Colors.PURPLE +
os.path.split(outputs['fibers'])[1] + Colors.YELLOW + '!' +
Colors._CLEAR)
# now the segmentation with the lookaround radius
actions.append(
fyborg.FyRadiusMapAction('segmentation', outputs['segmentation'],
radius))
c.info(Colors.YELLOW + ' Configuring mapping of ' + Colors.PURPLE +
os.path.split(outputs['segmentation'])[1] + Colors.YELLOW +
' to ' + Colors.PURPLE + os.path.split(outputs['fibers'])[1] +
Colors.YELLOW + '!' + Colors._CLEAR)
# and also the fiber length
actions.append(fyborg.FyLengthAction())
c.info(Colors.YELLOW + ' Configuring mapping of ' + Colors.PURPLE +
'fiber length' + Colors.YELLOW + ' to ' + Colors.PURPLE +
os.path.split(outputs['fibers'])[1] + Colors.YELLOW + '!' +
Colors._CLEAR)
# run, forest, run!!
c.info(Colors.YELLOW + ' Performing configured mapping for ' +
Colors.PURPLE + os.path.split(outputs['fibers'])[1] +
Colors.YELLOW + ' and storing as ' + Colors.PURPLE +
os.path.split(outputs['fibers_mapped'])[1] + Colors.YELLOW +
' (~ 30 minutes)!' + Colors._CLEAR)
if self.__debug:
fyborg.fyborg(outputs['fibers'], outputs['fibers_mapped'], actions,
'debug')
else:
fyborg.fyborg(outputs['fibers'], outputs['fibers_mapped'], actions)
save_image(img, volFile)
# trk file
fibers = []
# 2,5,6
# 3,5,7
# 2,6,7
# 8,7,3
# 9,5,4
points = np.array([[2, 5, 6], [3, 5, 7], [2, 6, 7], [8, 7, 3], [9, 5, 4]],
dtype=np.float32)
fibers.append((points, None, None))
io.saveTrk(trkFile, fibers, None, None, True)
# with fyborg
fyborg.fyborg(trkFile, mappedTrkFile, [fyborg.FyMapAction('test', volFile)])
# now validate
s = io.loadTrk(mappedTrkFile)
tracks = s[0]
origHeader = s[1]
scalars = tracks[0][1]
print scalars[0], '==', testArr[2][5][6]
print scalars[1], '==', testArr[3][5][7]
print scalars[2], '==', testArr[2][6][7]
print scalars[3], '==', testArr[8][7][3]
print scalars[4], '==', testArr[9][5][4]
# trk file fibers = [] # 2,5,6 # 3,5,7 # 2,6,7 # 8,7,3 # 9,5,4 points = np.array( [[2, 5, 6], [3, 5, 7], [2, 6, 7], [8, 7, 3], [9, 5, 4]], dtype=np.float32 ) fibers.append( ( points, None, None ) ) io.saveTrk( trkFile, fibers, None, None, True ) # with fyborg fyborg.fyborg( trkFile, mappedTrkFile, [fyborg.FyMapAction( 'test', volFile )] ) # now validate s = io.loadTrk( mappedTrkFile ) tracks = s[0] origHeader = s[1] scalars = tracks[0][1] print scalars[0], '==', testArr[2][5][6] print scalars[1], '==', testArr[3][5][7] print scalars[2], '==', testArr[2][6][7] print scalars[3], '==', testArr[8][7][3] print scalars[4], '==', testArr[9][5][4]
