Merge pull request #221 from Dana-Farber-AIOS/vignette-update

Vignette update

examples/manuscript_vignettes_stable/loading_images_vignette.ipynb

@@ -11,7 +11,9 @@
     "\n",
     "## Consistent API for loading images from diverse modalities and file formats\n",
     "\n",
-    "`PathML` provides support for loading a wide array of imaging modalities and file formats under a standardized syntax. In this vignette, we highlight code snippets for loading a range of image types ranging from brightfield H&E and IHC to highly multiplexed immunofluorescence and spatial expression and proteomics, from small images to gigapixel scale:\n",
+    "`PathML` provides support for loading a wide array of imaging modalities and file formats under a standardized syntax. \n",
+    "\n",
+    "In this vignette, we highlight code snippets for loading a range of image types ranging from brightfield H&E and IHC to highly multiplexed immunofluorescence and spatial expression and proteomics, from small images to gigapixel scale:\n",
     "\n",
     "| Imaging modality | File format | Source | Image dimensions (X, Y, Z, C, T)\n",
     "| :- | :- | :- | :- \n",
@@ -379,7 +381,7 @@
     "\n",
     "Full documentation of the `PathML` API is available at https://pathml.org.  \n",
     "\n",
-    "Full code for this vignette is available at https://github.com/Dana-Farber-AIOS/pathml/tree/master/examples/vignettes/"
+    "Full code for this vignette is available at https://github.com/Dana-Farber-AIOS/pathml/tree/master/examples/manuscript_vignettes_stable"
    ]
   }
  ],

examples/manuscript_vignettes_stable/workflow_HE_vignette.ipynb

@@ -9,7 +9,13 @@
     "\n",
     "## Example workflow for H&E images\n",
     "\n",
-    "Here we demonstrate a typical workflow for preprocessing of H&E images. The image used in this example is publicly avilalable for download: http://openslide.cs.cmu.edu/download/openslide-testdata/Aperio/\n",
+    "Here we demonstrate a typical workflow for preprocessing of H&E images, consisting of the following steps:\n",
+    "\n",
+    "1. Loading the raw image\n",
+    "2. Defining a simple preprocessing pipeline for tissue detection\n",
+    "3. Creating a PyTorch DataLoader for interfacing with any downstream machine learning model\n",
+    "\n",
+    "The image used in this example is publicly avilalable for download: http://openslide.cs.cmu.edu/download/openslide-testdata/Aperio/\n",
     "\n",
     "**a. Load the image**"
    ]
@@ -159,11 +165,11 @@
     "\n",
     "1. Loading the raw image\n",
     "2. Define a simple preprocessing pipeline for tissue detection\n",
-    "3. Create a PyTorch DataLoader for with any downstream machine learning model\n",
+    "3. Create a PyTorch DataLoader for interfacing with any downstream machine learning model\n",
     "\n",
     "Full documentation of the `PathML` API is available at https://pathml.org.  \n",
     "\n",
-    "Full code for this vignette is available at https://github.com/Dana-Farber-AIOS/pathml/tree/master/examples/vignettes/"
+    "Full code for this vignette is available at https://github.com/Dana-Farber-AIOS/pathml/tree/master/examples/manuscript_vignettes_stable"
    ]
   }
  ],

examples/manuscript_vignettes_stable/workflow_IF_vignette.ipynb

@@ -10,7 +10,17 @@
     "\n",
     "## Example workflow for immunofluorescence images\n",
     "\n",
-    "Here we demonstrate a typical workflow for preprocessing of immunofluorescence images. The image used in this example is a tissue microarray (TMA) generated on the CODEX spatial proteomics imaging platform, from Schurch et al., *Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front* (Cell, 2020). The image used in this example is publicly avilalable for download from the Cancer Imaging Archive: https://doi.org/10.7937/tcia.2020.fqn0-0326"
+    "Here we demonstrate a typical workflow for preprocessing of immunofluorescence images, comsisting of the following steps:\n",
+    "\n",
+    "1. Loading a raw image in TIFF format\n",
+    "2. Defining a preprocessing pipeline for cell segmentation and marker quantification for each cell\n",
+    "3. Integrating with other commonly used tools such as `Scanpy` for working with the quantified cell-level data:\n",
+    "    - dimensionality reduction\n",
+    "    - clustering\n",
+    "    - co-occurence analysis\n",
+    "    - visualization \n",
+    "\n",
+    "The image used in this example is a tissue microarray (TMA) generated on the CODEX spatial proteomics imaging platform, from Schurch et al., *Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front* (Cell, 2020). The image used in this example is publicly avilalable for download from the Cancer Imaging Archive: https://doi.org/10.7937/tcia.2020.fqn0-0326"
    ]
   },
   {
@@ -415,25 +425,24 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
     "### Summary\n",
     "\n",
     "Here we demonstrate a complete `PathML` workflow for analyzing immunofluorescence images:\n",
     "\n",
-    "1. Loading raw image in TIFF format\n",
-    "2. Define a preprocessing pipeline for cell segmentation and marker quantification for each cell\n",
-    "3. Integrate with other commonly used tools such as `Scanpy` for working with the quantified cell-level data:\n",
+    "1. Loading a raw image in TIFF format\n",
+    "2. Defining a preprocessing pipeline for cell segmentation and marker quantification for each cell\n",
+    "3. Integrating with other commonly used tools such as `Scanpy` for working with the quantified cell-level data:\n",
     "    - dimensionality reduction\n",
     "    - clustering\n",
     "    - co-occurence analysis\n",
     "    - visualization \n",
     "\n",
     "Full documentation of the `PathML` API is available at https://pathml.org.  \n",
     "\n",
-    "Full code for this vignette is available at https://github.com/Dana-Farber-AIOS/pathml/tree/master/examples/vignettes/"
+    "Full code for this vignette is available at https://github.com/Dana-Farber-AIOS/pathml/tree/master/examples/manuscript_vignettes_stable"
    ]
   }
  ],