Commit b2da3b0a authored by Christian Tischer's avatar Christian Tischer

EMBL Course

parent 23b63e17
......@@ -18,7 +18,7 @@
### Activity
* Open image: `xy_8bit__nuclei_noisy_different_intensity.tif`
* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
* Explore different ways to inspect pixel values and indices
* Add image calibration
* Check where the calibration is visible
......@@ -63,7 +63,7 @@ contrast = max - min
### Activity
* Open image: `xy_8bit__nuclei_noisy_different_intensity.tif`
* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
* Explore different LUTs and LUT settings
* Appreciate that LUT settings do not affect image content.
......@@ -72,10 +72,10 @@ contrast = max - min
Fill in the blanks, using those words: decrease, larger_than, increase, smaller_than
* Pixels with values _____ the `LUT_max` will appear saturated.
* Decreasing `LUT_max` while keeping `LUT_min` constant will _____ the contrast.
* Decreasing both `LUT_max` and `LUT_min` will _____ the overall brightness.
* Pixels with values _____ the `LUT_min` will appear black, when using a grayscale LUT.
* Pixels with values _____ `max` will appear saturated.
* Decreasing `max` while keeping `min` constant will _____ the contrast.
* Decreasing both `max` and `min` will _____ the overall brightness.
* Pixels with values _____ the `min` will appear black, when using a grayscale LUT.
 
......@@ -116,7 +116,7 @@ What are good reasons to change the pixel values in an image?
### Activity: Pixel based background subtraction
* Open image: `xy_8bit__nuclei_noisy_different_intensity.tif`
* 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:
......@@ -181,12 +181,12 @@ What are good reasons to change the pixel data type of an image?
### Activity: 16-bit to 8-bit conversion
* Open image: `xy_16bit__two_values.tif`
* Open image: xy_16bit__two_values.tif
* Convert to 8-bit
### Activity: 16-bit to float conversion
* Open image: `xy_16bit__two_values.tif`
* Open image: xy_16bit__two_values.tif
* Convert to float
### Formative Assessment
......@@ -226,7 +226,7 @@ In order to find objects in a image, the first step often is to determine whethe
### Activity: Threshold an image
* Open image: `xy_8bit__two_cells.tif`
* Open image: xy_8bit__two_cells.tif
* Convert the image to a binary image by means of thresholding.
### Formative assessment
......@@ -304,7 +304,7 @@ Fill in the blanks, using these words: less, more, 8, 255, 4, more.
### Activity: Measure object shape parameters
* Open image: `xy_8bit_labels__four_objects.tif`
* Open image: xy_8bit_labels__four_objects.tif
* Perform shape measurements and discuss their meanings.
* Color objects by their measurement values.
* Add a calibration to the image and check which shape measurements are affected.
......@@ -345,7 +345,7 @@ Which statements are true? Discuss with your neighbor!
### Activity: Segment objects and measure shapes
* Open image: `xy_8bit__two_cells.tif`
* Open image: xy_8bit__two_cells.tif
* Segment the cells and measure their shapes.
* Devise code to automate the workflow.
......@@ -370,7 +370,7 @@ Fill in below blanks, using these words: equal_to, larger_than, smaller_than, bi
### Activity: Measure intensities in image regions
* Open image: `xy_float__h2b_bg_corr.tif`
* Open image: xy_float__h2b_bg_corr.tif
* Measure for both nuclei:
* Maximum intensity
* Average intensity
......@@ -391,7 +391,7 @@ There are several good reasons not to subtract the background from each pixel in
#### Workflow
* Open image: `xy_calibrated_8bit__two_nuclei_high_background.tif`
* Open image: xy_calibrated_8bit__two_nuclei_high_background.tif
* Measure for both nuclei and a background region:
* Maximum intensity
* Average intensity
......@@ -434,7 +434,7 @@ Fill in the blanks, using these words: integrated, mean, number_of_pixels, decre
### Activity: Explore convolution filters
* Open image: `xy_8bit__nuclei_noisy_different_intensity.tif`
* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
* Try the result of different convolution filters, e.g.
* https://en.wikipedia.org/wiki/Kernel_(image_processing)
* Mean filter
......@@ -444,7 +444,7 @@ Fill in the blanks, using these words: integrated, mean, number_of_pixels, decre
### Activity: Use mean filter to facilitate image segmentation
* Open image: `xy_8bit__nuclei_noisy_different_intensity.tif`
* Open image: xy_8bit__nuclei_noisy_different_intensity.tif
* Appreciate that you cannot readily threshold the image
* Apply a mean filter
* Threshold the filtered image
......
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