def ShowSlice(self, index = 0):
bitmap = self.bitmap_list[index]
# UPDATE GUI
## Text related to size
value = STR_SIZE %(bitmap[3], bitmap[4])
self.text_image_size.SetValue(value)
value1 = ''
value2 = ''
value = "%s\n%s" %(value1, value2)
self.text_image_location.SetValue(value)
#self.text_patient.SetValue(value)
self.text_patient.SetValue('')
#self.text_acquisition.SetValue(value)
self.text_acquisition.SetValue('')
n_array = bitmap_reader.ReadBitmap(bitmap[0])
image = converters.to_vtk(n_array, spacing=(1,1,1),\
slice_number=1, orientation="AXIAL")
# ADJUST CONTRAST
window_level = n_array.max()/2
window_width = n_array.max()
colorer = vtk.vtkImageMapToWindowLevelColors()
colorer.SetInputData(image)
colorer.SetWindow(float(window_width))
colorer.SetLevel(float(window_level))
colorer.Update()
if self.actor is None:
self.actor = vtk.vtkImageActor()
self.renderer.AddActor(self.actor)
# PLOT IMAGE INTO VIEWER
self.actor.SetInputData(colorer.GetOutput())
self.renderer.ResetCamera()
self.interactor.Render()
# Setting slider position
self.slider.SetValue(index)
def bitmap2memmap(files, slice_size, orientation, spacing,
resolution_percentage):
"""
From a list of dicom files it creates memmap file in the temp folder and
returns it and its related filename.
"""
message = _("Generating multiplanar visualization...")
update_progress = vtk_utils.ShowProgress(len(files) - 1,
dialog_type="ProgressDialog")
temp_file = tempfile.mktemp()
if orientation == 'SAGITTAL':
if resolution_percentage == 1.0:
shape = slice_size[1], slice_size[0], len(files)
else:
shape = math.ceil(slice_size[1]*resolution_percentage),\
math.ceil(slice_size[0]*resolution_percentage), len(files)
elif orientation == 'CORONAL':
if resolution_percentage == 1.0:
shape = slice_size[1], len(files), slice_size[0]
else:
shape = math.ceil(slice_size[1]*resolution_percentage), len(files),\
math.ceil(slice_size[0]*resolution_percentage)
else:
if resolution_percentage == 1.0:
shape = len(files), slice_size[1], slice_size[0]
else:
shape = len(files), math.ceil(slice_size[1]*resolution_percentage),\
math.ceil(slice_size[0]*resolution_percentage)
if resolution_percentage == 1.0:
matrix = numpy.memmap(temp_file, mode='w+', dtype='int16', shape=shape)
cont = 0
max_scalar = None
min_scalar = None
xy_shape = None
first_resample_entry = False
for n, f in enumerate(files):
image_as_array = bitmap_reader.ReadBitmap(f)
image = converters.to_vtk(image_as_array, spacing=spacing,\
slice_number=1, orientation=orientation.upper())
if resolution_percentage != 1.0:
image_resized = ResampleImage2D(image, px=None, py=None,\
resolution_percentage = resolution_percentage, update_progress = None)
yx_shape = image_resized.GetDimensions(
)[1], image_resized.GetDimensions()[0]
if not (first_resample_entry):
shape = shape[0], yx_shape[0], yx_shape[1]
matrix = numpy.memmap(temp_file,
mode='w+',
dtype='int16',
shape=shape)
first_resample_entry = True
image = image_resized
min_aux, max_aux = image.GetScalarRange()
if min_scalar is None or min_aux < min_scalar:
min_scalar = min_aux
if max_scalar is None or max_aux > max_scalar:
max_scalar = max_aux
array = numpy_support.vtk_to_numpy(image.GetPointData().GetScalars())
if array.dtype == 'uint16':
array = array - 32768 / 2
array = array.astype("int16")
if orientation == 'CORONAL':
array.shape = matrix.shape[0], matrix.shape[2]
matrix[:, n, :] = array[:, ::-1]
elif orientation == 'SAGITTAL':
array.shape = matrix.shape[0], matrix.shape[1]
# TODO: Verify if it's necessary to add the slices swapped only in
# sagittal rmi or only in # Rasiane's case or is necessary in all
# sagittal cases.
matrix[:, :, n] = array[:, ::-1]
else:
array.shape = matrix.shape[1], matrix.shape[2]
matrix[n] = array
update_progress(cont, message)
cont += 1
matrix.flush()
scalar_range = min_scalar, max_scalar
return matrix, scalar_range, temp_file
