{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Active perception for focused transmit steering\n", "\n", "In this tutorial we will implement a basic perception-action loop to drive intelligent and adaptive focused transmit steering. We will use [Diffusion Models](https://zea.readthedocs.io/en/latest/_autosummary/zea.models.diffusion.html#zea.models.diffusion.DiffusionModel) to implement perception-as-inference, with [greedy entropy minimization](https://zea.readthedocs.io/en/latest/_autosummary/zea.agent.selection.html#zea.agent.selection.GreedyEntropy) as our action selection policy.\n", "\n", "For more information we would like to refer you to the paper [Patient-Adaptive Focused Transmit Beamforming using Cognitive Ultrasound](https://tue-bmd.github.io/ulsa/)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tue-bmd/zea/blob/main/docs/source/notebooks/agent/agent_example.ipynb)\n", " \n", "[![View on GitHub](https://img.shields.io/badge/GitHub-View%20Source-blue?logo=github)](https://github.com/tue-bmd/zea/blob/main/docs/source/notebooks/agent/agent_example.ipynb)\n", " \n", "[![Hugging Face model](https://img.shields.io/badge/Hugging%20Face-Model-yellow?logo=huggingface)](https://huggingface.co/zeahub/diffusion-echonet-dynamic)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "‼️ **Important:** This notebook is optimized for **GPU/TPU**. Code execution on a **CPU** may be very slow.\n", "\n", "If you are running in Colab, please enable a hardware accelerator via:\n", "\n", "**Runtime → Change runtime type → Hardware accelerator → GPU/TPU** 🚀." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%%capture\n", "%pip install zea" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import os\n", "\n", "os.environ[\"KERAS_BACKEND\"] = \"jax\"\n", "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\"" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m\u001b[38;5;36mzea\u001b[0m\u001b[0m: Using backend 'jax'\n" ] } ], "source": [ "import keras\n", "import keras.ops as ops\n", "import matplotlib.pyplot as plt\n", "from matplotlib import animation\n", "from tqdm import tqdm\n", "\n", "from zea import init_device\n", "from zea.models.diffusion import DiffusionModel\n", "from zea.ops import Pipeline, ScanConvert\n", "from zea.func import translate\n", "from zea.data import Dataset\n", "from zea.visualize import plot_image_grid, set_mpl_style\n", "from zea.agent.selection import GreedyEntropy" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [ "parameters" ] }, "outputs": [], "source": [ "n_prior_samples = 4\n", "n_unconditional_steps = 90\n", "n_initial_conditonal_steps = 180\n", "n_conditional_steps = 200\n", "n_conditional_samples = 4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will work with the GPU if available, and initialize using `init_device` to pick the best available device. Also, (optionally), we will set the matplotlib style for plotting." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "init_device(verbose=False)\n", "set_mpl_style()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load dataset and model" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m\u001b[38;5;36mzea\u001b[0m\u001b[0m: Using pregenerated dataset info file: \u001b[33m/root/.cache/zea/huggingface/datasets/datasets--zeahub--camus-sample/snapshots/617cf91a1267b5ffbcfafe9bebf0813c7cee8493/val/dataset_info.yaml\u001b[0m ...\n", "\u001b[1m\u001b[38;5;36mzea\u001b[0m\u001b[0m: ...for reading file paths in \u001b[33m/root/.cache/zea/huggingface/datasets/datasets--zeahub--camus-sample/snapshots/617cf91a1267b5ffbcfafe9bebf0813c7cee8493/val\u001b[0m\n", "\u001b[1m\u001b[38;5;36mzea\u001b[0m\u001b[0m: Dataset was validated on \u001b[32mSeptember 24, 2025\u001b[0m\n", "\u001b[1m\u001b[38;5;36mzea\u001b[0m\u001b[0m: Remove \u001b[33m/root/.cache/zea/huggingface/datasets/datasets--zeahub--camus-sample/snapshots/617cf91a1267b5ffbcfafe9bebf0813c7cee8493/val/validated.flag\u001b[0m if you want to redo validation.\n" ] } ], "source": [ "# load generative model\n", "model = DiffusionModel.from_preset(\"diffusion-echonet-dynamic\")\n", "img_shape = model.input_shape[:2]\n", "\n", "\n", "# load camus dataset\n", "dataset = Dataset(\"hf://zeahub/camus-sample/val\", key=\"image\")\n", "data = dataset[0][\"data\"][\"image\"]\n", "data = keras.ops.expand_dims(data, axis=-1)\n", "data = keras.ops.image.resize(data, img_shape)\n", "dynamic_range = (-40, 0)\n", "data = keras.ops.clip(data, dynamic_range[0], dynamic_range[1])\n", "data = translate(data, dynamic_range, (-1, 1))\n", "data = data[..., 0] # remove channel dim" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualize target sequence\n", "Here we load a sequence of ultrasound frames from the CAMUS validation set. This will be our 'ground truth' target sequence, that the agent will need to reconstruct from a small budget of focused scan lines" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m\u001b[38;5;36mzea\u001b[0m\u001b[0m: \u001b[38;5;214mWARNING\u001b[0m GPU support for order > 1 is not available. Disabling jit for ScanConvert.\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scan_convert = Pipeline([ScanConvert(order=2, jit_compile=False)])\n", "parameters = {\n", " \"theta_range\": [-0.78, 0.78], # [-45, 45] in radians\n", " \"rho_range\": [0, 1],\n", "}\n", "parameters = scan_convert.prepare_parameters(**parameters)\n", "data_sc = scan_convert(data=data, **parameters)[\"data\"]\n", "\n", "n_frames_to_plot = 5\n", "fig, _ = plot_image_grid(\n", " data_sc[:n_frames_to_plot],\n", " titles=[f\"t={t}\" for t in range(n_frames_to_plot)],\n", " ncols=n_frames_to_plot,\n", " remove_axis=True,\n", " vmin=-1,\n", " vmax=1,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simulate Focused Line Acquisition\n", "We use a simple masking operator to simulate acquiring a set of focused lines from the tissue, where each line reveals a vertical column of pixels, in the polar domain, of the target." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "def simulate_acquisition(full_frame, mask):\n", " measurement = full_frame[None, ...] * mask\n", " return measurement, mask" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Perception-Action Loop" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Initially, we have not yet acquired any measurements, so we draw samples from the prior to drive our actions." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 48ms/step\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "prior_samples = model.sample(n_samples=n_prior_samples, n_steps=n_unconditional_steps, verbose=True)\n", "scan_converted_prior_samples = scan_convert(\n", " data=keras.ops.squeeze(prior_samples, axis=-1), **parameters\n", ")[\"data\"]\n", "posterior_variance = ops.nan_to_num(ops.var(scan_converted_prior_samples, axis=0))\n", "fig, _ = plot_image_grid(\n", " list(scan_converted_prior_samples) + [translate(posterior_variance, range_to=(-1, 1))],\n", " titles=[f\"Sample {i}\" for i in range(n_prior_samples)] + [\"Var[x]\"],\n", " vmin=-1,\n", " vmax=1,\n", " cmap=[\"gray\"] * n_prior_samples + [\"inferno\"],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we implement a perception-action loop, using a greedy entropy minimization strategy to select which lines to acquire next in the sequence. Each set of generated posterior samples at time $t$ are used as _initial samples_ for the reverse diffusion at time $t+1$ [1], ensuring that we generate a reconstructed sequence that is coherent over time.\n", "\n", "[1] https://ieeexplore.ieee.org/document/10889752" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "frame_height, frame_width, _ = model.input_shape\n", "action_selector = GreedyEntropy(\n", " n_actions=14, # acquire 25% of measurements\n", " n_possible_actions=frame_width,\n", " img_width=frame_width,\n", " img_height=frame_height,\n", ")\n", "\n", "# select the first actions based on the prior samples\n", "prior_samples_batched = prior_samples[None, ..., 0] # add batch, remove channel\n", "selected_lines, measurement_mask = action_selector.sample(prior_samples_batched)\n", "# initialise the previous samples as the prior samples\n", "previous_samples = prior_samples\n", "\n", "reconstructions = []\n", "measurements = []\n", "for target_frame in tqdm(data):\n", " # perception\n", " measurements_t, measurement_mask_t = simulate_acquisition(target_frame, measurement_mask)\n", " posterior_samples = model.posterior_sample(\n", " measurements=measurements_t[..., None], # add channel dim\n", " mask=measurement_mask_t[..., None], # add channel dim\n", " initial_samples=previous_samples,\n", " n_samples=n_conditional_samples,\n", " n_steps=n_conditional_steps,\n", " omega=10,\n", " initial_step=n_initial_conditonal_steps,\n", " )\n", "\n", " # action\n", " selected_lines, measurement_mask = action_selector.sample(posterior_samples[..., 0])\n", "\n", " # gather the selected measurements and reconstructions for visualization\n", " reconstructions.append(posterior_samples[0])\n", " measurements.append(measurements_t)\n", " # reset the previous_samples\n", " previous_samples = posterior_samples" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# postprocess outputs for plotting\n", "reconstructions = ops.convert_to_tensor(reconstructions)\n", "measurements = ops.convert_to_tensor(measurements)\n", "selected_reconstructions = reconstructions[\n", " :, 0, ...\n", "] # choose first sample for each frame to display\n", "reconstructions_sc = scan_convert(data=selected_reconstructions[..., 0], **parameters)[\"data\"]\n", "measurements_sc = scan_convert(data=measurements[:, 0, ...], **parameters)[\"data\"]\n", "variances_sc = scan_convert(\n", " data=ops.var(reconstructions, axis=1)[..., 0], **(parameters | {\"fill_value\": 0.0})\n", ")[\"data\"]\n", "variances_sc = translate(variances_sc, range_to=(-1, 1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualize the results\n", "Finally, we visualize our reconstructed sequence, along with the selected measurements and posterior variance at each step. The agent's goal of minizing posterior entropy is reflected in the low posterior variance throughout the sequence. You can see that the agent is quickly able to reduce the uncertainty after the first frame, when it was able to observe using acquisition of the first focused lines." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# plot image\n", "fig, ims = plot_image_grid(\n", " [data_sc[0], measurements_sc[0], reconstructions_sc[0], variances_sc[0]],\n", " titles=[\"Target\", \"Measurements\", \"Reconstruction\", \"Variance\"],\n", " ncols=4,\n", " vmin=-1,\n", " vmax=1,\n", " cmap=[\"gray\"] * 3 + [\"inferno\"],\n", " figsize=(11, 4),\n", ")\n", "fig.tight_layout(pad=0)\n", "\n", "\n", "def update(frame):\n", " ims[0].set_array(data_sc[frame])\n", " ims[1].set_array(measurements_sc[frame])\n", " ims[2].set_array(reconstructions_sc[frame])\n", " ims[3].set_array(variances_sc[frame])\n", " return ims\n", "\n", "\n", "ani = animation.FuncAnimation(fig, update, frames=len(data_sc), blit=True, interval=100)\n", "plt.close(fig)\n", "ani.save(\"agent_example_reconstruction.gif\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![Agent example reconstruction](agent_example_reconstruction.gif)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.11" } }, "nbformat": 4, "nbformat_minor": 2 }