Commit b59ab5e0 by Christian Tischer

parent ccbd36e1
 --- title: Image calibration layout: page --- ## Image calibration ### 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.
 --- title: Connected components layout: page --- ## Connected components 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
 --- title: Pixel data types layout: page --- ## Pixel data types ## Pixel data type conversions ### 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.
 --- title: Image display layout: page --- # Image display ``` 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.
 # Image binarization
modules/math.md 0 → 100644
 --- title: Image math layout: page --- ## Image math ### 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/)