Add an automatic rendering function

README.md

@@ -197,7 +197,7 @@ If the 2D/3D registration capabilities are helpful, please cite our followup, [`
       year={2024}
     }
 
-If you use the 3D CBCT reconstruction capabilities, please cite our followup, [`DiffVox`](https://arxiv.org/abs/2312.06358):
+If you use the 3D CBCT reconstruction capabilities, please cite our followup, [`DiffVox`](https://arxiv.org/abs/2411.19224):
 
     @article{momeni2024voxel,
       title={Voxel-based Differentiable X-ray Rendering Improves Self-Supervised 3D CBCT Reconstruction},

diffdrr/_modidx.py

@@ -175,6 +175,7 @@
                                'diffdrr.utils.resample': ('api/utils.html#resample', 'diffdrr/utils.py')},
             'diffdrr.visualization': { 'diffdrr.visualization._make_camera_frustum_mesh': ( 'api/visualization.html#_make_camera_frustum_mesh',
                                                                                             'diffdrr/visualization.py'),
+                                       'diffdrr.visualization.add_image': ('api/visualization.html#add_image', 'diffdrr/visualization.py'),
                                        'diffdrr.visualization.animate': ('api/visualization.html#animate', 'diffdrr/visualization.py'),
                                        'diffdrr.visualization.drr_to_mesh': ( 'api/visualization.html#drr_to_mesh',
                                                                               'diffdrr/visualization.py'),
@@ -183,5 +184,6 @@
                                        'diffdrr.visualization.labelmap_to_mesh': ( 'api/visualization.html#labelmap_to_mesh',
                                                                                    'diffdrr/visualization.py'),
                                        'diffdrr.visualization.plot_drr': ('api/visualization.html#plot_drr', 'diffdrr/visualization.py'),
-                                       'diffdrr.visualization.plot_mask': ( 'api/visualization.html#plot_mask',
-                                                                            'diffdrr/visualization.py')}}}
+                                       'diffdrr.visualization.plot_mask': ('api/visualization.html#plot_mask', 'diffdrr/visualization.py'),
+                                       'diffdrr.visualization.visualize_scene': ( 'api/visualization.html#visualize_scene',
+                                                                                  'diffdrr/visualization.py')}}}

diffdrr/data.py

@@ -161,6 +161,8 @@ def read(
                 dim=0,
             )
 
+        subject.volume.data = subject.volume.data * mask
+        subject.mask.data = subject.mask.data * mask
         subject.density.data = subject.density.data * mask
 
     return subject

diffdrr/visualization.py

@@ -12,7 +12,7 @@
 from tqdm import tqdm
 
 # %% auto 0
-__all__ = ['plot_drr', 'plot_mask', 'animate', 'drr_to_mesh', 'labelmap_to_mesh', 'img_to_mesh']
+__all__ = ['plot_drr', 'plot_mask', 'animate', 'drr_to_mesh', 'labelmap_to_mesh', 'img_to_mesh', 'visualize_scene', 'add_image']
 
 # %% ../notebooks/api/04_visualization.ipynb 5
 import torch
@@ -352,3 +352,39 @@ def _make_camera_frustum_mesh(source, target, size=0.125):
         ]
     )
     return pyvista.PolyData(vertices, faces)
+
+# %% ../notebooks/api/04_visualization.ipynb 15
+def visualize_scene(
+    drr: DRR,
+    pose: RigidTransform,
+    labelmap: bool = False,
+    grid: bool = True,
+    verbose: bool = False,
+    **kwargs
+):
+    """
+    Given a DRR and a RigidTransform, render the 3D scene in PyVista.
+    **kwargs are passed to drr_to_mesh.
+    """
+    # Extract a mesh from the subject
+    if labelmap:
+        mesh = labelmap_to_mesh(drr.subject, verbose=verbose)
+    else:
+        mesh = drr_to_mesh(drr.subject, "surface_nets", verbose=verbose, **kwargs)
+
+    # Plot on a grid
+    pl = pyvista.Plotter()
+    pl.add_mesh(mesh)
+    pl = add_image(drr, pose, pl)
+    if grid:
+        pl.show_grid()
+    return pl
+
+
+def add_image(drr: DRR, pose: RigidTransform, pl: pyvista.Plotter):
+    """Add a camera to an existing scene."""
+    camera, detector, texture, principal_ray = img_to_mesh(drr, pose)
+    pl.add_mesh(camera, show_edges=True)
+    pl.add_mesh(detector, texture=texture)
+    pl.add_mesh(principal_ray, color="lime", line_width=3)
+    return pl

notebooks/api/03_data.ipynb

@@ -232,6 +232,8 @@
     "                dim=0,\n",
     "            )\n",
     "\n",
+    "        subject.volume.data = subject.volume.data * mask\n",
+    "        subject.mask.data = subject.mask.data * mask\n",
     "        subject.density.data = subject.density.data * mask\n",
     "\n",
     "    return subject"

notebooks/api/04_visualization.ipynb

@@ -483,6 +483,50 @@
     "    return pyvista.PolyData(vertices, faces)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ebb5fe6b-886c-415a-8881-5387269f7950",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| export\n",
+    "def visualize_scene(\n",
+    "    drr: DRR,\n",
+    "    pose: RigidTransform,\n",
+    "    labelmap: bool = False,\n",
+    "    grid: bool = True,\n",
+    "    verbose: bool = False,\n",
+    "    **kwargs\n",
+    "):\n",
+    "    \"\"\"\n",
+    "    Given a DRR and a RigidTransform, render the 3D scene in PyVista.\n",
+    "    **kwargs are passed to drr_to_mesh.\n",
+    "    \"\"\"\n",
+    "    # Extract a mesh from the subject\n",
+    "    if labelmap:\n",
+    "        mesh = labelmap_to_mesh(drr.subject, verbose=verbose)\n",
+    "    else:\n",
+    "        mesh = drr_to_mesh(drr.subject, \"surface_nets\", verbose=verbose, **kwargs)\n",
+    "\n",
+    "    # Plot on a grid\n",
+    "    pl = pyvista.Plotter()\n",
+    "    pl.add_mesh(mesh)\n",
+    "    pl = add_image(drr, pose, pl)\n",
+    "    if grid:\n",
+    "        pl.show_grid()\n",
+    "    return pl\n",
+    "\n",
+    "\n",
+    "def add_image(drr: DRR, pose: RigidTransform, pl: pyvista.Plotter):\n",
+    "    \"\"\"Add a camera to an existing scene.\"\"\"\n",
+    "    camera, detector, texture, principal_ray = img_to_mesh(drr, pose)\n",
+    "    pl.add_mesh(camera, show_edges=True)\n",
+    "    pl.add_mesh(detector, texture=texture)\n",
+    "    pl.add_mesh(principal_ray, color=\"lime\", line_width=3)\n",
+    "    return pl"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

notebooks/index.ipynb

@@ -48,9 +48,17 @@
    "source": [
     "## Install\n",
     "\n",
+    "To install the latest stable release (**recommended**):\n",
+    "\n",
     "```zsh\n",
     "pip install diffdrr\n",
-    "```"
+    "```\n",
+    "\n",
+    "To install the development version:\n",
+    "\n",
+    "```zsh\n",
+    "git clone https://github.com/eigenvivek/DiffDRR.git --depth 1\n",
+    "pip install -e 'DiffDRR/[dev]'"
    ]
   },
   {
@@ -253,19 +261,36 @@
    "source": [
     "## Citing `DiffDRR`\n",
     "\n",
-    "If you find `DiffDRR` useful in your work, please cite our [paper](https://doi.org/10.1007/978-3-031-23179-7_1) (or the [freely accessible arXiv version](https://arxiv.org/abs/2208.12737)):\n",
-    "\n",
-    "```\n",
-    "@inproceedings{gopalakrishnanDiffDRR2022,\n",
-    "    author    = {Gopalakrishnan, Vivek and Golland, Polina},\n",
-    "    title     = {Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging},\n",
-    "    year      = {2022},\n",
-    "    booktitle = {Clinical Image-based Procedures: 11th International Workshop, CLIP 2022, Held in Conjunction with MICCAI 2022, Singapore, Proceedings},\n",
-    "    series    = {Lecture Notes in Computer Science},\n",
-    "    publisher = {Springer},\n",
-    "    doi       = {https://doi.org/10.1007/978-3-031-23179-7_1},\n",
-    "}\n",
-    "```"
+    "If you find `DiffDRR` useful in your work, please cite our\n",
+    "[paper](https://arxiv.org/abs/2208.12737):\n",
+    "\n",
+    "    @inproceedings{gopalakrishnan2022fast,\n",
+    "      title={Fast auto-differentiable digitally reconstructed radiographs for solving inverse problems in intraoperative imaging},\n",
+    "      author={Gopalakrishnan, Vivek and Golland, Polina},\n",
+    "      booktitle={Workshop on Clinical Image-Based Procedures},\n",
+    "      pages={1--11},\n",
+    "      year={2022},\n",
+    "      organization={Springer}\n",
+    "    }\n",
+    "\n",
+    "If the 2D/3D registration capabilities are helpful, please cite our followup, [`DiffPose`](https://arxiv.org/abs/2312.06358):\n",
+    "\n",
+    "    @article{gopalakrishnan2023intraoperative,\n",
+    "      title={Intraoperative {2D/3D} image registration via differentiable {X}-ray rendering},\n",
+    "      author={Gopalakrishnan, Vivek and Dey, Neel and Golland, Polina},\n",
+    "      booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},\n",
+    "      pages={11662--11672},\n",
+    "      year={2024}\n",
+    "    }\n",
+    "\n",
+    "If you use the 3D CBCT reconstruction capabilities, please cite our followup, [`DiffVox`](https://arxiv.org/abs/2411.19224):\n",
+    "\n",
+    "    @article{momeni2024voxel,\n",
+    "      title={Voxel-based Differentiable X-ray Rendering Improves Self-Supervised 3D CBCT Reconstruction},\n",
+    "      author={Momeni, Mohammadhossein and Gopalakrishnan, Vivek and Dey, Neel and Golland, Polina and Frisken, Sarah},\n",
+    "      booktitle={Machine Learning and the Physical Sciences, NeurIPS 2024},\n",
+    "      year={2024}\n",
+    "    }"
    ]
   },
   {