{ "cells": [ { "cell_type": "markdown", "id": "45bfac39", "metadata": {}, "source": [ "3D TV-Regularized Sparse-View CT Reconstruction (ADMM Solver)\n", "=============================================================\n", "\n", "This example demonstrates solution of a sparse-view, 3D CT\n", "reconstruction problem with isotropic total variation (TV)\n", "regularization\n", "\n", " $$\\mathrm{argmin}_{\\mathbf{x}} \\; (1/2) \\| \\mathbf{y} - C \\mathbf{x}\n", " \\|_2^2 + \\lambda \\| D \\mathbf{x} \\|_{2,1} \\;,$$\n", "\n", "where $C$ is the X-ray transform (the CT forward projection operator),\n", "$\\mathbf{y}$ is the sinogram, $D$ is a 3D finite difference operator,\n", "and $\\mathbf{x}$ is the reconstructed image.\n", "\n", "In this example the problem is solved via ADMM, while proximal\n", "ADMM is used in a [companion example](ct_astra_3d_tv_padmm.rst)." ] }, { "cell_type": "code", "execution_count": 1, "id": "4faf23c7", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2024-10-23T17:00:32.706293Z", "iopub.status.busy": "2024-10-23T17:00:32.705679Z", "iopub.status.idle": "2024-10-23T17:00:36.897493Z", "shell.execute_reply": "2024-10-23T17:00:36.896594Z" } }, "outputs": [], "source": [ "# This scico project Jupyter notebook has been automatically modified\n", "# to install the dependencies required for running it on Google Colab.\n", "# If you encounter any problems in running it, please open an issue at\n", "# https://github.com/lanl/scico-data/issues\n", "\n", "!pip install 'scico[examples] @ git+https://github.com/lanl/scico'\n", "\n", "import numpy as np\n", "\n", "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", "\n", "import scico.numpy as snp\n", "from scico import functional, linop, loss, metric, plot\n", "from scico.examples import create_tangle_phantom\n", "from scico.linop.xray.astra import XRayTransform3D\n", "from scico.optimize.admm import ADMM, LinearSubproblemSolver\n", "from scico.util import device_info\n", "plot.config_notebook_plotting()" ] }, { "cell_type": "markdown", "id": "5aeabd78", "metadata": {}, "source": [ "Create a ground truth image and projector." ] }, { "cell_type": "code", "execution_count": 2, "id": "efa7383b", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2024-10-23T17:00:36.903485Z", "iopub.status.busy": "2024-10-23T17:00:36.903048Z", "iopub.status.idle": "2024-10-23T17:00:37.151797Z", "shell.execute_reply": "2024-10-23T17:00:37.151161Z" } }, "outputs": [], "source": [ "Nx = 128\n", "Ny = 256\n", "Nz = 64\n", "\n", "tangle = snp.array(create_tangle_phantom(Nx, Ny, Nz))\n", "\n", "n_projection = 10 # number of projections\n", "angles = np.linspace(0, np.pi, n_projection, endpoint=False) # evenly spaced projection angles\n", "C = XRayTransform3D(\n", " tangle.shape, det_count=[Nz, max(Nx, Ny)], det_spacing=[1.0, 1.0], angles=angles\n", ") # CT projection operator\n", "y = C @ tangle # sinogram" ] }, { "cell_type": "markdown", "id": "b0f2c212", "metadata": {}, "source": [ "Set up problem and solver." ] }, { "cell_type": "code", "execution_count": 3, "id": "a8a8be4e", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2024-10-23T17:00:37.156774Z", "iopub.status.busy": "2024-10-23T17:00:37.156468Z", "iopub.status.idle": "2024-10-23T17:00:37.561125Z", "shell.execute_reply": "2024-10-23T17:00:37.560174Z" } }, "outputs": [], "source": [ "λ = 2e0 # ℓ2,1 norm regularization parameter\n", "ρ = 5e0 # ADMM penalty parameter\n", "maxiter = 25 # number of ADMM iterations\n", "cg_tol = 1e-4 # CG relative tolerance\n", "cg_maxiter = 25 # maximum CG iterations per ADMM iteration\n", "\n", "# The append=0 option makes the results of horizontal and vertical\n", "# finite differences the same shape, which is required for the L21Norm,\n", "# which is used so that g(Ax) corresponds to isotropic TV.\n", "D = linop.FiniteDifference(input_shape=tangle.shape, append=0)\n", "g = λ * functional.L21Norm()\n", "f = loss.SquaredL2Loss(y=y, A=C)\n", "\n", "solver = ADMM(\n", " f=f,\n", " g_list=[g],\n", " C_list=[D],\n", " rho_list=[ρ],\n", " x0=C.T(y),\n", " maxiter=maxiter,\n", " subproblem_solver=LinearSubproblemSolver(cg_kwargs={\"tol\": cg_tol, \"maxiter\": cg_maxiter}),\n", " itstat_options={\"display\": True, \"period\": 5},\n", ")" ] }, { "cell_type": "markdown", "id": "be32e9d5", "metadata": {}, "source": [ "Run the solver." ] }, { "cell_type": "code", "execution_count": 4, "id": "7dddeb2b", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2024-10-23T17:00:37.565090Z", "iopub.status.busy": "2024-10-23T17:00:37.564763Z", "iopub.status.idle": "2024-10-23T17:01:35.093098Z", "shell.execute_reply": "2024-10-23T17:01:35.092115Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Solving on GPU (NVIDIA GeForce RTX 2080 Ti)\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Iter Time Objective Prml Rsdl Dual Rsdl CG It CG Res \n", "-----------------------------------------------------------------\n", " 0 4.75e+00 1.338e+08 1.108e+03 4.148e+05 25 4.378e-03\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 1 8.36e+00 8.472e+05 5.867e+02 1.229e+04 25 5.837e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2 1.16e+01 2.890e+05 3.957e+02 2.195e+03 25 6.304e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 3 1.47e+01 2.136e+05 2.638e+02 1.096e+03 25 5.704e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 4 1.78e+01 1.884e+05 1.782e+02 7.120e+02 25 3.006e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 5 2.09e+01 1.777e+05 1.277e+02 5.287e+02 25 3.040e-04\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 6 2.40e+01 1.715e+05 9.657e+01 4.262e+02 25 2.097e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 7 2.72e+01 1.679e+05 8.323e+01 3.361e+02 25 1.937e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 8 3.05e+01 1.672e+05 7.962e+01 2.203e+02 25 1.461e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 9 3.29e+01 1.669e+05 5.758e+01 1.570e+02 19 8.946e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 10 3.58e+01 1.668e+05 4.715e+01 1.216e+02 23 9.359e-05\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 11 3.73e+01 1.663e+05 3.899e+01 1.025e+02 11 9.117e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 12 3.84e+01 1.659e+05 3.274e+01 8.080e+01 8 9.385e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 13 4.15e+01 1.652e+05 3.991e+01 6.994e+01 25 1.860e-04\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 14 4.33e+01 1.644e+05 3.067e+01 7.111e+01 14 9.665e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 15 4.43e+01 1.642e+05 2.617e+01 5.860e+01 7 7.569e-05\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 16 4.53e+01 1.641e+05 2.326e+01 3.329e+01 6 9.122e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 17 4.62e+01 1.641e+05 2.247e+01 2.862e+01 6 8.062e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 18 4.86e+01 1.643e+05 3.538e+01 6.108e+01 19 9.865e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 19 5.01e+01 1.641e+05 2.792e+01 6.106e+01 11 9.581e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 20 5.10e+01 1.639e+05 2.373e+01 3.051e+01 6 9.659e-05\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 21 5.32e+01 1.637e+05 2.953e+01 4.651e+01 17 9.602e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 22 5.48e+01 1.636e+05 2.363e+01 3.987e+01 10 8.185e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 23 5.55e+01 1.636e+05 1.902e+01 1.932e+01 4 9.290e-05\r" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 24 5.71e+01 1.641e+05 2.326e+01 3.868e+01 12 8.314e-05\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "TV Restruction\n", "SNR: 21.43 (dB), MAE: 0.014\n" ] } ], "source": [ "print(f\"Solving on {device_info()}\\n\")\n", "tangle_recon = solver.solve()\n", "\n", "print(\n", " \"TV Restruction\\nSNR: %.2f (dB), MAE: %.3f\"\n", " % (metric.snr(tangle, tangle_recon), metric.mae(tangle, tangle_recon))\n", ")" ] }, { "cell_type": "markdown", "id": "91f1a9f1", "metadata": {}, "source": [ "Show the recovered image." ] }, { "cell_type": "code", "execution_count": 5, "id": "cc6d6ce8", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2024-10-23T17:01:35.096336Z", "iopub.status.busy": "2024-10-23T17:01:35.095989Z", "iopub.status.idle": "2024-10-23T17:01:35.737501Z", "shell.execute_reply": "2024-10-23T17:01:35.736731Z" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plot.subplots(nrows=1, ncols=2, figsize=(7, 6))\n", "plot.imview(\n", " tangle[32],\n", " title=\"Ground truth (central slice)\",\n", " cmap=plot.cm.Blues,\n", " cbar=None,\n", " fig=fig,\n", " ax=ax[0],\n", ")\n", "plot.imview(\n", " tangle_recon[32],\n", " title=\"TV Reconstruction (central slice)\\nSNR: %.2f (dB), MAE: %.3f\"\n", " % (metric.snr(tangle, tangle_recon), metric.mae(tangle, tangle_recon)),\n", " cmap=plot.cm.Blues,\n", " fig=fig,\n", " ax=ax[1],\n", ")\n", "divider = make_axes_locatable(ax[1])\n", "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.2)\n", "fig.colorbar(ax[1].get_images()[0], cax=cax, label=\"arbitrary units\")\n", "fig.show()" ] } ], "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.2" } }, "nbformat": 4, "nbformat_minor": 5 }