basics_and_cartesian_reconstructions.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basics and Cartesian Reconstructions\n",
    "Here we are going to have a look at a few basics of MRpro and reconstruct data acquired with a Cartesian sampling pattern."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview\n",
    "\n",
    "In this notebook we are going to explore the MRpro KData object and the included header parameters. We will then use a FFT-operator in order to reconstruct data acquired with a Cartesian sampling scheme. Finally we will try to reconstruct data acquired on a Cartesian grid but with partial echo and partial Fourier acceleration.\n",
    "\n",
    "Run this notebook in Google colab: \n",
    "\n",
    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/PTB-MR/mrpro_utrecht_workshop_2024/blob/main/basics_and_cartesian_reconstruction.ipynb\">\n",
    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
    "</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install MRpro and download data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "# Suppress all warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install MRpro\n",
    "!pip install git+https://github.com/PTB-MR/mrpro.git#egg=mrpro[notebook]\n",
    "import mrpro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the raw data from zenodo\n",
    "import tempfile\n",
    "from pathlib import Path\n",
    "import zenodo_get\n",
    "\n",
    "data_folder = Path(tempfile.mkdtemp())\n",
    "dataset = '14173489'\n",
    "zenodo_get.zenodo_get([dataset, '-r', 5, '-o', data_folder])  # r: retries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# List the downloaded files\n",
    "from os import listdir\n",
    "for f in listdir(data_folder):\n",
    "    print(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we have three different scans obtained from the same object with the same FOV and resolution:\n",
    "\n",
    "- cart_t1.mrd is a fully sampled Cartesian acquisition\n",
    "\n",
    "- cart_t1_partial_echo_partial_fourier.mrd is accelerated using partial echo and partial Fourier\n",
    "\n",
    "- cart_t1_msense_integraded.mrd is acclerated using regular undersampling and self-calibrated SENSE"
   ]
  }
 ],
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