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| 1 | +# Copyright 2022 MONAI Consortium |
| 2 | +# Licensed under the Apache License, Version 2.0 (the "License"); |
| 3 | +# you may not use this file except in compliance with the License. |
| 4 | +# You may obtain a copy of the License at |
| 5 | +# http://www.apache.org/licenses/LICENSE-2.0 |
| 6 | +# Unless required by applicable law or agreed to in writing, software |
| 7 | +# distributed under the License is distributed on an "AS IS" BASIS, |
| 8 | +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 9 | +# See the License for the specific language governing permissions and |
| 10 | +# limitations under the License. |
| 11 | + |
| 12 | +import numpy as np |
| 13 | + |
| 14 | +import monai.deploy.core as md |
| 15 | +from monai.deploy.core import ExecutionContext, Image, InputContext, IOType, Operator, OutputContext |
| 16 | +from monai.deploy.utils.importutil import optional_import |
| 17 | + |
| 18 | +DataDefinition, _ = optional_import("clara.viz.core", name="DataDefinition") |
| 19 | +Widget, _ = optional_import("clara.viz.widgets", name="Widget") |
| 20 | +display, _ = optional_import("IPython.display", name="display") |
| 21 | +interact, _ = optional_import("ipywidgets", name="interact") |
| 22 | +Dropdown, _ = optional_import("ipywidgets", name="Dropdown") |
| 23 | + |
| 24 | + |
| 25 | +@md.input("image", Image, IOType.IN_MEMORY) |
| 26 | +@md.input("seg_image", Image, IOType.IN_MEMORY) |
| 27 | +@md.env(pip_packages=["clara.viz.core", "clara.viz.widgets", "IPython"]) |
| 28 | +class ClaraVizOperator(Operator): |
| 29 | + """ |
| 30 | + This operator uses Clara Viz to provide interactive view of a 3D volume including segmentation mask. |
| 31 | + """ |
| 32 | + |
| 33 | + def __init__(self): |
| 34 | + """Constructor of the operator.""" |
| 35 | + super().__init__() |
| 36 | + |
| 37 | + @staticmethod |
| 38 | + def _build_array(image, order): |
| 39 | + if order == "MXYZ": |
| 40 | + # @todo mask is transposed, see issue #171 |
| 41 | + numpy_array = np.transpose(image.asnumpy(), (2, 1, 0)) |
| 42 | + else: |
| 43 | + numpy_array = image.asnumpy() |
| 44 | + |
| 45 | + array = DataDefinition.Array(array=numpy_array, order=order) |
| 46 | + array.element_size = [1.0] |
| 47 | + array.element_size.append(image.metadata().get("col_pixel_spacing", 1.0)) |
| 48 | + array.element_size.append(image.metadata().get("row_pixel_spacing", 1.0)) |
| 49 | + array.element_size.append(image.metadata().get("depth_pixel_spacing", 1.0)) |
| 50 | + |
| 51 | + # the renderer is expecting data in RIP order (Right Inferior Posterior) which results in |
| 52 | + # this matrix |
| 53 | + target_affine_transform = [ |
| 54 | + [0.0, 1.0, 0.0, 0.0], |
| 55 | + [1.0, 0.0, 0.0, 0.0], |
| 56 | + [0.0, 0.0, -1.0, 0.0], |
| 57 | + [0.0, 0.0, 0.0, 1.0], |
| 58 | + ] |
| 59 | + |
| 60 | + dicom_affine_transform = image.metadata().get("dicom_affine_transform", np.identity(4)) |
| 61 | + |
| 62 | + affine_transform = np.matmul(target_affine_transform, dicom_affine_transform) |
| 63 | + |
| 64 | + array.permute_axes = [ |
| 65 | + 0, |
| 66 | + max(range(3), key=lambda k: abs(affine_transform[0][k])) + 1, |
| 67 | + max(range(3), key=lambda k: abs(affine_transform[1][k])) + 1, |
| 68 | + max(range(3), key=lambda k: abs(affine_transform[2][k])) + 1, |
| 69 | + ] |
| 70 | + |
| 71 | + array.flip_axes = [ |
| 72 | + False, |
| 73 | + affine_transform[0][array.permute_axes[1] - 1] < 0.0, |
| 74 | + affine_transform[1][array.permute_axes[2] - 1] < 0.0, |
| 75 | + affine_transform[2][array.permute_axes[3] - 1] < 0.0, |
| 76 | + ] |
| 77 | + |
| 78 | + return array |
| 79 | + |
| 80 | + def compute(self, op_input: InputContext, op_output: OutputContext, context: ExecutionContext): |
| 81 | + """Displays the input image and segmentation mask |
| 82 | +
|
| 83 | + Args: |
| 84 | + op_input (InputContext): An input context for the operator. |
| 85 | + op_output (OutputContext): An output context for the operator. |
| 86 | + context (ExecutionContext): An execution context for the operator. |
| 87 | + """ |
| 88 | + input_image = op_input.get("image") |
| 89 | + if not input_image: |
| 90 | + raise ValueError("Input image is not found.") |
| 91 | + input_seg_image = op_input.get("seg_image") |
| 92 | + if not input_seg_image: |
| 93 | + raise ValueError("Input segmentation image is not found.") |
| 94 | + |
| 95 | + # build the data definition |
| 96 | + data_definition = DataDefinition() |
| 97 | + |
| 98 | + data_definition.arrays.append(self._build_array(input_image, "DXYZ")) |
| 99 | + |
| 100 | + data_definition.arrays.append(self._build_array(input_seg_image, "MXYZ")) |
| 101 | + |
| 102 | + widget = Widget() |
| 103 | + widget.select_data_definition(data_definition) |
| 104 | + # default view mode is 'CINEMATIC' switch to 'SLICE_SEGMENTATION' since we have no transfer functions defined |
| 105 | + widget.settings["Views"][0]["mode"] = "SLICE_SEGMENTATION" |
| 106 | + widget.settings["Views"][0]["cameraName"] = "Top" |
| 107 | + widget.set_settings() |
| 108 | + display(widget) |
| 109 | + |
| 110 | + # add controls |
| 111 | + def set_view_mode(view_mode): |
| 112 | + widget.settings["Views"][0]["mode"] = view_mode |
| 113 | + if view_mode == "CINEMATIC": |
| 114 | + widget.settings["Views"][0]["cameraName"] = "Perspective" |
| 115 | + elif widget.settings["Views"][0]["cameraName"] == "Perspective": |
| 116 | + widget.settings["Views"][0]["cameraName"] = "Top" |
| 117 | + widget.set_settings() |
| 118 | + |
| 119 | + interact( |
| 120 | + set_view_mode, |
| 121 | + view_mode=Dropdown( |
| 122 | + options=[("Cinematic", "CINEMATIC"), ("Slice", "SLICE"), ("Slice Segmentation", "SLICE_SEGMENTATION")], |
| 123 | + value="SLICE_SEGMENTATION", |
| 124 | + description="View mode", |
| 125 | + ), |
| 126 | + ) |
| 127 | + |
| 128 | + def set_camera(camera): |
| 129 | + if widget.settings["Views"][0]["mode"] != "CINEMATIC": |
| 130 | + widget.settings["Views"][0]["cameraName"] = camera |
| 131 | + widget.set_settings() |
| 132 | + |
| 133 | + interact(set_camera, camera=Dropdown(options=["Top", "Right", "Front"], value="Top", description="Camera")) |
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