Add several modules

modules/calibration.md

+---
+title:     Image calibration
+layout:    page
+---
+
+## Image calibration
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    pixel -> indices;
+    pixel -> coordinates;
+    indices -> calibration;
+    calibration -> coordinates;
+    calibration -> anisotropic [label="  can be"];
+    image -> calibration [label="  can have"];
+  }
+'/>
+
+
+### Activity: Explore image calibration
+
+* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
+* Add image calibration
+* Explore whether and how this affects image display and measurements (e.g. distance between two points)
+
+
+### Activity: Explore anisotropic 3D image data
+
+* Open image: xy_8bit_calibrated_anisotropic__mri_stack.tif
+        * Appreciate that the pixels are anisotropic
+
+
+### Formative assessment
+
+True or false?
+
+* Changing the image calibration changes the pixel values.
+* Pixel coordinates depend on image calibration.
+
+

modules/connected_components.md

+---
+title:     Connected components 
+layout:    page
+---
+
+## Connected components analysis
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    "intensity image" -> "connected component analysis" -> "label image";
+    connectivity -> "connected component analysis";
+  }
+'/>
+
+
+### Activity: 2D connected components analysis
+
+* Open image: xy_8bit_binary__nuclei.tif
+* Perform connected components analysis
+* Explore multi-color LUTs for object labelling
+* Explore removing and joining labels
+
+
+### Activity: 3D connected components analysis
+
+Repeat above activity but use a 3D image:
+
+* Open image: xyz_8bit_binary__spots.tif
+
+### Formative assessment
+
+Fill in the blanks, using these words: less, more, 8, 255, 4, more.
+
+1. In 3D, pixels have _____ neighbors than in 2D.
+2. 8-connected connectivity results in _____ objects than 4-connected connectivity.
+3. In 3D, pixels have ____ non-diagonal neighbors.
+4. In 2D, pixels have ____ non-diagonal neighbors.
+5. A 8-bit label image can maximally have _____ objects.
+6. The maximum value in a label image is equal to or _____ than the number of objects.
+
+## Learn next
+
+- shape_measurements.md

modules/datatypes.md

+---
+title:     Pixel data types
+layout:    page
+---
+
+## Pixel data types
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    "data type" -> "pixel values" [label="  restricts"];
+    "N-bit unsigned integer" -> "0, 1, ..., 2^N-1";
+    "data type" -> float -> "..., -1031.0, ..., 10.5, ...";
+    "data type" -> "...";
+    "data type" -> "N-bit unsigned integer";
+  }
+'/>
+
+## Pixel data type conversions
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    "data type conversion" -> "values" [label="  can change"];
+    "data type conversion" -> "value range" [label="  changes"];
+  }
+'/>
+
+### Activity: 16-bit to 8-bit conversion
+
+* Open image: xy_16bit__two_values.tif
+* Convert to 8-bit
+* Understand the mathematics underlying the conversion from 16-bit to 8-bit.
+
+### Activity: 16-bit to float conversion
+
+* Open image: xy_16bit__two_values.tif
+* Convert to float
+
+### Formative Assessment
+
+True or false? Discuss with your neighbor!
+
+1. Changing pixel data type never changes pixel values.
+2. Converting from 16-bit unsigned integer to float never changes the pixel values.
+3. Changing from float to 16-bit unsigned integer never changes the pixel values.
+4. There is only one correct way to convert from 16-bit to 8-bit.
+

modules/display.md

+---
+title:     Image display
+layout:    page
+---
+
+# Image display
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    LUT -> color;
+    LUT -> brightness;
+    min -> LUT;
+    max -> LUT;
+    value -> LUT;
+  }
+'/>
+
+```
+brightness = ( value - min ) / ( max - min )
+
+0 <= brightness <= 1
+
+contrast = max - min
+```
+
+## Activity
+
+* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
+* Explore different LUTs and LUT settings
+        * Appreciate that LUT settings do not affect image content.
+
+
+## Formative Assessment
+
+Fill in the blanks, using those words: decrease, larger than, increase, smaller than
+
+1. Pixels with values _____ `max` will appear saturated.
+2. Decreasing `max` while keeping `min` constant will _____ the contrast.
+3. Decreasing both `max` and `min` will _____ the overall brightness.
+4. Pixels with values _____ the `min` will appear black, when using a grayscale LUT.

modules/image-binariztion.md

-# Image binarization
- 
-<img src='https://g.gravizo.com/svg?
- digraph G {
-    shift [fontcolor=white,color=white];
-    intenstiy_image -> threshold;
-    threshold -> background [label="  <threshold"];
-    threshold -> foreground [label="  >=threshold"];
-    background -> binaryimage;
-	foreground -> binaryimage;
-	binaryimage -> 0 [label="  background"];
-	binaryimage -> 1 [label="  foreground"];   
-  }
-'/>

modules/math.md

+---
+title:     Image math
+layout:    page
+---
+
+## Image math 
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    "data type" -> "pixel values" [label="  restricts"];
+    "image math" -> "pixel values" [label="  changes"];
+    "N-bit unsigned integer" -> "0, 1, ..., 2^N-1";
+    "data type" -> float -> "..., -1031.0, ..., 10.5, ...";
+    "data type" -> "...";
+    "data type" -> "N-bit unsigned integer";
+  }
+'/>
+
+### Activity: Pixel based background subtraction
+
+* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
+* Appreciate the significant background intensity
+* Measure pixel values at `[ 28, 35 ]` and `[ 28, 39 ]`
+* Measure the image background intensity in this region:
+    * upper left corner at `[ 20, 35 ]`
+    * width = 10
+    * height = 10
+* Subtract the measured background intensity from each pixel.
+* Measure the pixel values again.
+* Observe that the resuls are incorrect.
+
+Repeat above activity, but:
+
+* After opening the image, convert its data type to floating point.
+
+### Activity: Explore the limitations of `float` data type
+
+* Create an empty image
+* Set all pixel values to 1000000000.0
+* Add 1.0 to all pixel values
+* Be shocked...
+
+...it turns out that from 16777216 on you cannot represent all integers anymore within a float.
+
+### Formative Assessment
+
+True or false?
+
+* Subtracting 100 from 50 in a 8-bit image will result in -50.
+* Adding 1 to 255 in a 8-bit image will result in 256.
+* Subtracting 10.1 from 10.0 in a float image will result in -0.1
+* Adding 1.0 to 255.0 in a float image will result in 256.0
+* Adding 1000.0 to 1000000000.0 in a float image will result in 1000001000.0
+
+### Learn more
+
+* [Limitations of float](https://randomascii.wordpress.com/2012/02/13/dont-store-that-in-a-float/)
+

modules/pixels.md

+---
+title:     Pixels 
+layout:    page
+---
+
+# Pixels
+
+## Concept map
+
+<img src='https://g.gravizo.com/svg?
+ digraph G {
+    shift [fontcolor=white,color=white];
+    image -> pixel [label="  has many"];
+    pixel -> value;
+    pixel -> indices;
+    pixel -> voxel [label="  3D"];
+  }
+'/>
+
+## Activity: Explore pixel values and indices
+
+* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
+* Explore different ways to inspect pixel values and indices
+* Check where the lowest pixel indices are in the displayed image:
+        * Most commonly: Upper left corner, which is different to conventional coordinate systems.
+
+## Formative assessment
+
+True or false?
+
+* The lowest pixel index of a 2D image always is `[1,1]`.
+* When looking at a 2D image, the lowest pixel indices are always in the lower left corner.