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+{
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "# BraTS \n",
+                "In this Notebook we demonstrate how to utilize the BraTS package to use top performing algorithms from recent BraTS challenges.\n",
+                "\n",
+                "---\n",
+                "## Getting Started\n",
+                "\n",
+                "#### This tutorial requires:\n",
+                "\n",
+                "   - Python 3.8+\n",
+                "   - Docker: Installation instructions on the official [website](https://docs.docker.com/get-docker/)\n",
+                "\n",
+                "\n",
+                "#### Optional but recommended:\n",
+                "   <!--CUDA 11.4+ (https://developer.nvidia.com/cuda-toolkit)-->\n",
+                "   - GPU with CUDA support (*otherwise CPU can be used for a some algorithms*) \n",
+                "   - NVIDIA Container Toolkit: Refer to the [NVIDIA install guide](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) and the official [GitHub page](https://github.com/NVIDIA/nvidia-container-toolkit) \n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 1,
+            "metadata": {
+                "scrolled": true
+            },
+            "outputs": [],
+            "source": [
+                "# Installations\n",
+                "!pip install brats matplotlib ipywidgets > /dev/null\n",
+                "\n",
+                "%load_ext autoreload\n",
+                "%autoreload 2"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "If you installed the packages and requirements on your own machine, you can skip this section and start from the import section.\n",
+                "\n",
+                "### Setup Colab environment (optional) \n",
+                "Otherwise you can follow and execute the tutorial on your browser.\n",
+                "In order to start working on the notebook, click on the following button, this will open this page in the Colab environment and you will be able to execute the code on your own (*Google account required*).\n",
+                "\n",
+                "<a target=\"_blank\" href=\"https://colab.research.google.com/github/BrainLesion/tutorials/blob/main/BraTS/tutorial.ipynb\">\n",
+                "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
+                "</a>\n",
+                "\n",
+                "Now that you are visualizing the notebook in Colab, run the next cell to install the packages we will use. There are few things you should follow in order to properly set the notebook up:\n",
+                "1. Warning: This notebook was not authored by Google. Click on 'Run anyway'.\n",
+                "1. When the installation commands are done, there might be \"Restart runtime\" button at the end of the output. Please, click it."
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "If you run the next cell in a Google Colab environment, it will **clone the 'tutorials' repository** in your google drive. This will create a **new folder** called \"tutorials\" in **your Google Drive**.\n",
+                "All generated file will be created/uploaded to your Google Drive respectively.\n",
+                "\n",
+                "After the first execution of the next cell, you might receive some warnings and notifications, please follow these instructions:\n",
+                "   - 'Permit this notebook to access your Google Drive files?' Click on 'Yes', and select your account.\n",
+                "   - Google Drive for desktop wants to access your Google Account. Click on 'Allow'.\n",
+                "\n",
+                "Afterwards the \"tutorials\" folder has been created. You can navigate it through the lefthand panel in Colab. You might also have received an email that informs you about the access on your Google Drive."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 2,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import sys\n",
+                "\n",
+                "# Check if we are in google colab currently\n",
+                "try:\n",
+                "    import google.colab\n",
+                "\n",
+                "    colabFlag = True\n",
+                "except ImportError as r:\n",
+                "    colabFlag = False\n",
+                "\n",
+                "# Execute certain steps only if we are in a colab environment\n",
+                "if colabFlag:\n",
+                "    # Create a folder in your Google Drive\n",
+                "    from google.colab import drive\n",
+                "\n",
+                "    drive.mount(\"/content/drive\")\n",
+                "    # clone repository and set path\n",
+                "    !git clone https://github.com/BrainLesion/tutorials.git /content/drive/MyDrive/tutorials\n",
+                "    BASE_PATH = \"/content/drive/MyDrive/tutorials/BraTS/\"\n",
+                "    sys.path.insert(0, BASE_PATH)\n",
+                "\n",
+                "else:  # normal jupyter notebook environment\n",
+                "    BASE_PATH = \"./\"  # current working directory would be BraTs-Toolkit anyways if you are not in colab"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Imports"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 3,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from pathlib import Path\n",
+                "from brats import AdultGliomaSegmenter\n",
+                "from brats.constants import AdultGliomaAlgorithms\n",
+                "import utils  # local file"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "---"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Data\n",
+                "\n",
+                "AURORA expects *preprocessed* input data as NIfTI file or NumPy Array (*preprocessed* meaning the files should be co-registerend, skullstripped and in SRI-24 space).\n",
+                "\n",
+                "In this example we provide sample data from the [ASNR-MICCAI BraTS Brain Metastasis Challenge](https://www.synapse.org/#!Synapse:syn51156910/wiki/622553), which is already preprocessed in the `AURORA/data` folder in the form of 4 modalities of the same brain (T1, T1C, T2, FLAIR). To get an intuition of the data, one example slice of the 3D scans is visualized below.\n",
+                "\n",
+                "For your own data:\n",
+                "If the data is *not* preprocessed yet, consider using our [BrainLes preprocessing](https://github.com/BrainLesion/preprocessing) package (or its predecessor [BraTS-Toolkit](https://github.com/neuronflow/BraTS-Toolkit)).\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 4,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 1200x1000 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {},
+                    "output_type": "display_data"
+                }
+            ],
+            "source": [
+                "subject = \"BraTS-GLI-00001-000\"\n",
+                "data_path = Path(BASE_PATH) / \"data\"\n",
+                "subject_path = data_path / subject\n",
+                "utils.visualize_data(data_path, subject_id=subject)"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Using BraTS"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "### Minimal example using default settings"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 5,
+            "metadata": {},
+            "outputs": [
+                {
+                    "name": "stderr",
+                    "output_type": "stream",
+                    "text": [
+                        "\u001b[32m2024-07-23 17:31:59.144\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m47\u001b[0m - \u001b[1mInstantiated AdultGliomaSegmenter with algorithm: BraTS23_1 by André Ferreira, et al.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:31:59.145\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_single\u001b[0m:\u001b[36m90\u001b[0m - \u001b[1mPerforming single inference \u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:31:59.158\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m53\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Adult Glioma Segmentation (1st place)\u001b[0m\u001b[1m\u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:31:59.159\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1m\u001b[34m(Docker image)\u001b[0m\u001b[1m: brainles/brats23_faking_it:latest\u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:31:59.160\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m59\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: https://arxiv.org/abs/2402.17317v1 by André Ferreira, et al.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:31:59.301\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m243\u001b[0m - \u001b[1mStarting inference\u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:35:29.255\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m268\u001b[0m - \u001b[1mFinished inference\u001b[0m\n",
+                        "\u001b[32m2024-07-23 17:35:29.257\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_single\u001b[0m:\u001b[36m119\u001b[0m - \u001b[1mSaved segmentation to: /home/ivan_marcel/tutorials/BraTS/segmentation.nii.gz\u001b[0m\n"
+                    ]
+                }
+            ],
+            "source": [
+                "segmenter = AdultGliomaSegmenter(cuda_devices=\"1\")\n",
+                "segmenter.infer_single(\n",
+                "    t1c=subject_path / f\"{subject}-t1c.nii.gz\",\n",
+                "    t1n=subject_path / f\"{subject}-t1n.nii.gz\",\n",
+                "    t2f=subject_path / f\"{subject}-t2f.nii.gz\",\n",
+                "    t2w=subject_path / f\"{subject}-t2w.nii.gz\",\n",
+                "    output_file=\"segmentation.nii.gz\",\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "### Visualize results\n",
+                "\n",
+                "The segementation comprise of the\n",
+                "TODO\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 5,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 800x400 with 2 Axes>"
+                        ]
+                    },
+                    "metadata": {},
+                    "output_type": "display_data"
+                }
+            ],
+            "source": [
+                "utils.visualize_segmentation(\n",
+                "    modality_file=subject_path / f\"{subject}-t1c.nii.gz\",\n",
+                "    segmentation_file=\"segmentation.nii.gz\",\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Batch processing\n",
+                "\n",
+                "BraTS allows to run an algorithm for a single set of input images (t1n, t1c, t2f, t2w of the same patient) or for multiple subjects.\n",
+                "Each of the available classes provides methods for both: \n",
+                "- `.infer_single(...)` that takes in the paths to the required input modalities and a path to store the result\n",
+                "- `.infer_batch(...)` that takes in a path to a data folder containing multiple sets of subjects and a path to an output folder to store the results"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "The sets of subject inputs need to be stored in a specific structure to be recognized by the package:\n",
+                "```\n",
+                "data_folder\n",
+                "┣ A\n",
+                "┃ ┣ A-t1c.nii.gz\n",
+                "┃ ┣ A-t1n.nii.gz\n",
+                "┃ ┣ A-t2f.nii.gz\n",
+                "┃ ┗ A-t2w.nii.gz\n",
+                "┣ B\n",
+                "┃ ┣ B-t1c.nii.gz\n",
+                "┃ ┣ ...\n",
+                "```"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 5,
+            "metadata": {
+                "scrolled": true
+            },
+            "outputs": [
+                {
+                    "name": "stderr",
+                    "output_type": "stream",
+                    "text": [
+                        "\u001b[32m2024-07-23 19:59:18.168\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m47\u001b[0m - \u001b[1mInstantiated AdultGliomaSegmenter with algorithm: BraTS23_1 by André Ferreira, et al.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 19:59:18.171\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m53\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Adult Glioma Segmentation (1st place)\u001b[0m\u001b[1m\u001b[0m\n",
+                        "\u001b[32m2024-07-23 19:59:18.172\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1m\u001b[34m(Docker image)\u001b[0m\u001b[1m: brainles/brats23_faking_it:latest\u001b[0m\n",
+                        "\u001b[32m2024-07-23 19:59:18.173\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m59\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: https://arxiv.org/abs/2402.17317v1 by André Ferreira, et al.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 19:59:18.175\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m165\u001b[0m - \u001b[1mFound 2 subjects: BraTS-GLI-00001-001, BraTS-GLI-00001-000 \u001b[0m\n",
+                        "\u001b[32m2024-07-23 19:59:18.208\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m174\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n"
+                    ]
+                },
+                {
+                    "name": "stderr",
+                    "output_type": "stream",
+                    "text": [
+                        "\u001b[32m2024-07-23 19:59:18.385\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m243\u001b[0m - \u001b[1mStarting inference\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:03:42.416\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m268\u001b[0m - \u001b[1mFinished inference\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:03:42.418\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m191\u001b[0m - \u001b[1mSaved results to: /home/ivan_marcel/tutorials/BraTS/batch_out\u001b[0m\n"
+                    ]
+                },
+                {
+                    "name": "stdout",
+                    "output_type": "stream",
+                    "text": [
+                        "['BraTS-GLI-00001-000.nii.gz', 'BraTS-GLI-00001-001.nii.gz']\n"
+                    ]
+                }
+            ],
+            "source": [
+                "output_path = Path(\"batch_out\")\n",
+                "\n",
+                "segmenter = AdultGliomaSegmenter(cuda_devices=\"1\")\n",
+                "segmenter.infer_batch(\n",
+                "    data_folder=data_path,\n",
+                "    output_folder=output_path,\n",
+                ")\n",
+                "\n",
+                "print([path.name for path in output_path.iterdir()])"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Advanced Usage"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "By default the algorithm that won the most recent challenge will be run on the first available GPU. This behavior and other options can be adapted, e.g.:\n",
+                "- Select a different algorithm from the available constants (Enum classes for each challenge) with the `algorithm` parameter\n",
+                "- Select a specific GPU if multiple are available with the `cuda_decives` parameter\n",
+                "- Force CPU execution with the `force_cpu`flag (will cause an exception for many algorithms since many do not support CPU execution)\n",
+                "- Save the generated logs in a log file with the `log_file` parameter"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 6,
+            "metadata": {},
+            "outputs": [
+                {
+                    "name": "stderr",
+                    "output_type": "stream",
+                    "text": [
+                        "\u001b[32m2024-07-23 20:15:40.003\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m47\u001b[0m - \u001b[1mInstantiated AdultGliomaSegmenter with algorithm: BraTS23_3 by Fadillah Adamsyah Maani, et al.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.007\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_single\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mLogging to: /home/ivan_marcel/tutorials/BraTS/segmentation.log\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.008\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_single\u001b[0m:\u001b[36m90\u001b[0m - \u001b[1mPerforming single inference \u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.017\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m53\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Adult Glioma Segmentation (3rd place)\u001b[0m\u001b[1m\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.018\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1m\u001b[34m(Docker image)\u001b[0m\u001b[1m: brainles/brats23_biomedmbz:latest\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.018\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m59\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: N/A by Fadillah Adamsyah Maani, et al.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.600\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.weights\u001b[0m:\u001b[36mcheck_model_weights\u001b[0m:\u001b[36m54\u001b[0m - \u001b[1mFound downloaded local weights: 11573315_v1.0.1\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.601\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.weights\u001b[0m:\u001b[36mcheck_model_weights\u001b[0m:\u001b[36m64\u001b[0m - \u001b[1mLatest model weights (11573315_v1.0.1) are already present.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:15:40.602\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m243\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
+                    ]
+                }
+            ],
+            "source": [
+                "segmenter = AdultGliomaSegmenter(\n",
+                "    algorithm=AdultGliomaAlgorithms.BraTS23_3,  # Use the 3rd placed algorithm of the Adult Glioma BraTS 2023 challenge\n",
+                "    cuda_devices=\"4\",  # Select GPU device with ID 4\n",
+                "    force_cpu=False,  # default, could be set to True to force CPU\n",
+                ")\n",
+                "\n",
+                "segmenter.infer_single(\n",
+                "    t1c=subject_path / f\"{subject}-t1c.nii.gz\",\n",
+                "    t1n=subject_path / f\"{subject}-t1n.nii.gz\",\n",
+                "    t2f=subject_path / f\"{subject}-t2f.nii.gz\",\n",
+                "    t2w=subject_path / f\"{subject}-t2w.nii.gz\",\n",
+                "    output_file=\"segmentation.nii.gz\",\n",
+                "    log_file=\"segmentation.log\",  # Save the logs in a new filed called `segmentation.log`\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Algorithms from other Challenges\n",
+                "\n",
+                "BraTS provides the algorithms from all available recent BraTS Challenges, i.e.:\n",
+                "- Adult Glioma Segmentation\n",
+                "- BraTS-Africa Segmentation\n",
+                "- Meningioma Segmentation\n",
+                "- Brain Metastases Segmentation\n",
+                "- Pediatric Tumors Segmentation\n",
+                "- Inpainting\n",
+                "\n",
+                "The package provides a separate class and algorithm constants for each of the challenges.<br>\n",
+                "The examples above were demonstrated using the class and constants of the Adult Glioma Segmentation challenge.\n",
+                "\n",
+                "In an identical way you can use:\n",
+                "- `MeningiomaSegmenter` class with `MeningiomaAlgorithms`\n",
+                "- `PediatricSegmenter` class with `PediatricAlgorithms`\n",
+                "- etc."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 6,
+            "metadata": {},
+            "outputs": [
+                {
+                    "name": "stderr",
+                    "output_type": "stream",
+                    "text": [
+                        "\u001b[32m2024-07-23 20:55:41.467\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m47\u001b[0m - \u001b[1mInstantiated MeningiomaSegmenter with algorithm: BraTS23_2 by Ziyan Huang\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.471\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m160\u001b[0m - \u001b[1mLogging to: /home/ivan_marcel/tutorials/BraTS/test.log\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.472\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m53\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Meningioma Segmentation (2nd place)\u001b[0m\u001b[1m\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.473\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1m\u001b[34m(Docker image)\u001b[0m\u001b[1m: brainles/brats23_meningioma_blackbean:latest\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.474\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m59\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: N/A by Ziyan Huang\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.475\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m165\u001b[0m - \u001b[1mFound 2 subjects: BraTS-GLI-00001-001, BraTS-GLI-00001-000 \u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.506\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m174\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:55:41.641\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36m_ensure_image\u001b[0m:\u001b[36m57\u001b[0m - \u001b[1mPulling docker image brainles/brats23_meningioma_blackbean:latest\u001b[0m\n",
+                        "\u001b[32m2024-07-23 20:59:21.168\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m243\u001b[0m - \u001b[1mStarting inference\u001b[0m\n",
+                        "\u001b[32m2024-07-23 21:00:03.730\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.docker\u001b[0m:\u001b[36mrun_docker\u001b[0m:\u001b[36m268\u001b[0m - \u001b[1mFinished inference\u001b[0m\n",
+                        "\u001b[32m2024-07-23 21:00:03.731\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.algorithms\u001b[0m:\u001b[36minfer_batch\u001b[0m:\u001b[36m191\u001b[0m - \u001b[1mSaved results to: /home/ivan_marcel/tutorials/BraTS/men_output\u001b[0m\n"
+                    ]
+                }
+            ],
+            "source": [
+                "# e.g. for the Meningioma Algorithms\n",
+                "from brats import MeningiomaSegmenter\n",
+                "from brats.constants import MeningiomaAlgorithms\n",
+                "\n",
+                "segmenter = MeningiomaSegmenter(\n",
+                "    algorithm=MeningiomaAlgorithms.BraTS23_2, cuda_devices=\"1\"\n",
+                ")\n",
+                "segmenter.infer_batch(\n",
+                "    data_folder=data_path, output_folder=\"men_output\", log_file=\"test.log\"\n",
+                ")"
+            ]
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "Python 3 (ipykernel)",
+            "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": "3.8.10"
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 2
+}
\ No newline at end of file
diff --git a/BraTS/utils.py b/BraTS/utils.py
new file mode 100644
index 0000000..4c0c93f
--- /dev/null
+++ b/BraTS/utils.py
@@ -0,0 +1,48 @@
+from pathlib import Path
+import matplotlib.pyplot as plt
+import nibabel as nib
+
+DATA_FOLDER = "data"
+
+
+def visualize_data(
+    data_folder: str = DATA_FOLDER,
+    subject_id: str = "BraTS-GLI-00001-000",
+    slice_index: int = 75,
+):
+    """Visualize the MRI modalities for a given slice index
+
+    Args:
+        data_folder (str, optional): Path to the folder containing the t1, t1c, t2 & flair file. Defaults to DATA_FOLDER.
+        slice_index (int, optional): Slice to be visualized (first index in data of shape (155, 240, 240)). Defaults to 75.
+    """
+    _, axes = plt.subplots(1, 4, figsize=(12, 10))
+
+    subject_path = Path(data_folder) / subject_id
+    modalities = ["t1n", "t1c", "t2f", "t2w"]
+    for i, mod in enumerate(modalities):
+        modality_file = subject_path / f"{subject_id}-{mod}.nii.gz"
+        modality_np = nib.load(modality_file).get_fdata().transpose(2, 1, 0)
+        axes[i].set_title(mod)
+        axes[i].imshow(modality_np[slice_index, :, :], cmap="gray")
+        axes[i].axis("off")
+
+
+def visualize_segmentation(modality_file: str, segmentation_file: str):
+    """Visualize the MRI modality and the segmentation
+
+    Args:
+        modality_file (str): Path to the desired modality file
+        segmentation_file (str): Path to the segmentation file
+    """
+    modality_np = nib.load(modality_file).get_fdata().transpose(2, 1, 0)
+    seg_np = nib.load(segmentation_file).get_fdata().transpose(2, 1, 0)
+    _, ax = plt.subplots(1, 2, figsize=(8, 4))
+
+    slice_index = modality_np.shape[0] // 2  # You can choose any slice here
+    ax[0].imshow(modality_np[slice_index, :, :], cmap="gray")
+    ax[1].imshow(modality_np[slice_index, :, :], cmap="gray")
+    ax[1].imshow(seg_np[slice_index, :, :], cmap="plasma", alpha=0.3)
+    for ax in ax:
+        ax.axis("off")
+    plt.tight_layout()