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