adjusted title and included tutorial header.

Author: DanielaSchacherer

notebooks/collections_demos/bonemarrowwsi_pediatricleukemia.ipynb

@@ -13,7 +13,29 @@
         "id": "vBC86EhVsKql"
       },
       "source": [
-        "# TBD: better title - BoneMarrowWSI-PediatricLeukemia\n"
+        "# Where cells come from: exploring bone marrow with the `BoneMarrowWSI-PediatricLeukemia` collection\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "This tutorial is shared as part of the tutorials prepared by the Imaging Data Commons team and available at https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks.\n",
+        "\n",
+        "If you are new to IDC and DICOM for digital pathology applications, you may want to check out other introductory tutorials on this topic available here: https://github.com/ImagingDataCommons/IDC-Tutorials/tree/master/notebooks/pathomics.\n",
+        "\n",
+        "This tutorial is aimed for the users of Imaging Data Commons that are interested in **bone marrow smear analysis**. You will learn how to:\n",
+        "* select and access images and annotations of the comprehensive bone marrow collection `BoneMarrowWSI-PediatricLeukemia`\n",
+        "* parse and understand the available annotations stored in DICOM Bulk Simple Annotations (ANN) format\n",
+        "\n",
+        "To learn more about the IDC, please visit the [IDC user guide](https://learn.canceridc.dev).\n",
+        "\n",
+        "If you have any questions, bug reports, or feature requests please feel free to contact us at the [IDC discussion forum](https://discourse.canceridc.dev)!\n",
+        "\n",
+        "----------------------\n",
+        "\n",
+        "Initial version: Feb 2026  \n",
+        "Updated: Feb 2026"
       ]
     },
     {
@@ -33,7 +55,7 @@
         "    - For some slides: Unlabeled cell bounding boxes\n",
         "    - For some slides: Cell bounding boxes with cell type labels for each annotation session plus the finally obtained consensus.\n",
         "\n",
-        "Both images and annotations are made available in the DICOM format. For the annotations, more specifically, the **DICOM Microscopy Bulk Simple Annotation format (ANNs)** was used, which is one of multiple options to store pathology annotation data in DICOM. As a general introduction to this format, we recommend having a look at [this tutorial notebook](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/pathomics/microscopy_dicom_ann_intro.ipynb).\n",
+        "Both images and annotations are made available in the DICOM format. For the annotations, more specifically, the **DICOM Microscopy Bulk Simple Annotation format (ANN)** was used, which is one of multiple options to store pathology annotation data in DICOM. As a general introduction to this format, we recommend having a look at [this tutorial notebook](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/pathomics/microscopy_dicom_ann_intro.ipynb).\n",
         "This notebook demonstrates **how to access and explore** the `BoneMarrowWSI-PediatricLeukemia` collection with a focus on its extensive annotation data. \n",
         "\n",
         "\n",
@@ -11627,6 +11649,28 @@
         "\n",
         "If you are interested in tissue type annotations or want to learn about DICOM Structured Reporting, you can take a look at [this notebook](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/collections_demos/rms_mutation_prediction/RMS-Mutation-Prediction-Expert-Annotations_exploration.ipynb) navigating expert-generated region annotations for rhabdomyosarcoma tumor slides."
       ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Support\n",
+        "\n",
+        "If you have any questions about this notebook, please post your question on the [IDC User Forum](https://discourse.canceridc.dev) or [open an issue](https://github.com/ImagingDataCommons/IDC-Tutorials/issues/new) in the [IDC Tutorials repository](https://github.com/ImagingDataCommons/IDC-Tutorials)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Acknowledgments\n",
+        "\n",
+        "Imaging Data Commons has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003I.\n",
+        "\n",
+        "If you use IDC in your research, please cite the following publication:\n",
+        "\n",
+        "> Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. _National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence_. RadioGraphics (2023). [https://doi.org/10.1148/rg.230180](https://doi.org/10.1148/rg.230180)"
+      ]
     }
   ],
   "metadata": {