Measure intensities: Add ROI activity

_includes/measure_intensities/measure_intensities_act1.md

@@ -1,21 +1,22 @@
-<h4 id="measure"><a href="#measure">Measure intensities (with background subtraction)</a></h4>
+<h4 id="measure"><a href="#measure">Measure object intensities with background subtraction</a></h4>
 
-##### Use the labels provided to measure objects intensities
+##### Measure object intensities
 
-- Open image [xy_16bit__h2b.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_16bit__h2b.tif)
-- H2B-mCherry staining acquired with a widefield microscope
-- Open label mask [xy_8bit_labels__h2b.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit_labels__h2b.tif)
-- Using the label mask, measure the mean and max intensities as well as the objects' pixel area.
-- Exports the results as a table (and open in a spreadsheet software)
-- Manually measure the mean intensity in the background.
-- Add the background measurement as a new column to the table
+- Measure the objects' **mean** and **max** intensities and pixel **area**.
+- Measure the mean intensity in the image background
+- Exports the results as a table and open in a spreadsheet software.
 - Create new columns for background corrected mean, max, and sum intensity.
 - Discuss the measurements' biophysical interpretation
 
-##### Now try using larger labels (optional)
+##### Explore influence of the object regions on measurement results
 
-- Open image [xy_16bit__h2b.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_16bit__h2b.tif) 
-- Open label mask [xy_8bit_labels__h2b_dilate_labels.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit_labels__h2b_dilate_labels.tif)
-- Appreciate that it is not always clear how large exactly the label regions have to be
-- Measure the intensities with the larger label mask
-- Discuss which values changed compared to label mask [xy_8bit_labels__h2b.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit_labels__h2b.tif) and by how much percent
+- Discuss that due to the diffraction limit is not obvious how to exactly deliniate objects in a fluorescence microscopy image
+- Measure the objects' intensities in significantly larger regions as above.
+- Explore and understand how the measurement values changed.
+
+#### Data
+
+- Intensity image: [xy_16bit__h2b.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_16bit__h2b.tif)
+    - H2B-mCherry staining acquired with a widefield microscope
+- Label image: [xy_8bit_labels__h2b.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit_labels__h2b.tif)
+- Larger label image: [xy_8bit_labels__h2b_dilate_labels.tif](https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit_labels__h2b_dilate_labels.tif)

_includes/measure_intensities/measure_intensities_act1_imagejgui_roi.md

@@ -0,0 +1,11 @@
+- Open the intensity image
+- Open the ROI manage to organise the object and background regions 
+    - `Analyze › Tools › ROI Manager...`
+- Use the Polygon selection tool to delineate both cells and a background region
+- `Add [t]` the respective ROIs to the ROI manager and `Rename...` them: `cell_1`, `cell_2`, `background`
+- Use `Analyze › Set Measurements...` to select `Area`, `Mean gray value`, `Min & max gray value`, `Integrated density`, `Display label`
+- Select all ROIs in the ROI Manager and click `Measure`
+- This will open a table
+- Use `File Save As..` to export the table as CSV and open it in a spreadsheet software (e.g. Google Sheet or Excel)
+- Add new columns for background corrected sum and mean intensity and do the math to correct all measurements for the background
+- Note that it is essential for the `Area` to be in pixel units when it using it to correct the sum intensity measurement

_modules/measure_intensities.md

@@ -14,23 +14,18 @@ motivation: >
 
 concept_map: >
   graph TD
-    li[Label image] --> im("Object intensity measurements")
-    ii[Intensity image] --> im
-    im --> table["Results table"]
-    ii --> bgm("Background measurement")
-    bgm --> table
+    re[Image regions (objects)] --> table[Measurement table]
+    ii[Intensity image] --> table
     table --> object_column["Columns are intensity features"]
-    object_column -.- |"e.g."| ex["Mean, Sum, Max, ..., Background"] 
-    table --> object_row["Rows are objects"]
-
-
+    object_column -.- |"e.g."| ex["Mean, Sum, Max, ..."] 
+    table --> object_row["Rows are regions (objects)"]
+
 figure: /figures/measure_intensities.png
-figure_legend: H2b-mCherry widefield image of two cells. Common object intensity measurements, using a label mask and a manual background measurement.
+figure_legend: H2b-mCherry widefield image of two cells. Common object intensity measurements, using a label mask image for the objects and a ROI for the background region.
 
 multiactivities:
-  - ["measure_intensities/measure_intensities_act1.md", [["ImageJ GUI", "measure_intensities/measure_intensities_act1_imagejgui.md", "markdown"], 
-  ["skimage napari", "measure_intensities/measure_intensities_act1_skimage_napari.py", "python"]]]
-  - ["measure_intensities/measure_intensities_act2.md", [["skimage napari", "measure_intensities/measure_intensities_act2_skimage_napari.py", "python"]]]
+  - ["measure_intensities/measure_intensities_act1.md", ["ImageJ GUI ROI", "measure_intensities/measure_intensities_act1_imagejgui_roi.md"], [["ImageJ GUI MorphoLibJ", "measure_intensities/measure_intensities_act1_imagejgui_mlj.md"], ["skimage napari", "measure_intensities/measure_intensities_act1_skimage_napari.py"]]]
+  - ["measure_intensities/measure_intensities_act2.md", [["skimage napari", "measure_intensities/measure_intensities_act2_skimage_napari.py"]]]
 
 exercises:
   - ["ImageJ GUI", "measure_intensities/exercises/measure_intensities_imagejgui.md"]