### EMBL Course

parent 34ddf270
 ... ... @@ -72,12 +72,12 @@ contrast = max - min ### Formative Assessment Fill in the blanks, using those words: decrease, larger_than, increase, smaller_than Fill in the blanks, using those words: decrease, larger than, increase, smaller than * 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. 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.   ... ... @@ -254,13 +254,12 @@ Repeat above activity but use a 3D image: Fill in the blanks, using these words: less, more, 8, 255, 4, more. * For a given input image there is only one correct connectivity. * In 3D, pixels have _____ neighbors than in 2D. * 8-connected connectivity results in _____ objects than 4-connected connectivity. * In 3D, pixels have ____ non-diagonal neighbors. * In 2D, pixels have ____ non-diagonal neighbors. * A 8-bit label image can maximally have _____ objects. * The maximum value in a label image is equal to or _____ than the number of objects. 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.   ... ... @@ -338,11 +337,11 @@ True or false? Discuss with your neighbour! Fill in below blanks, using these words: equal_to, larger_than, smaller_than, binary, connected_component_analysis, thresholding * A label image is the result of _____ . * The number of pixels in a binary image is typically _____ the number of connected components. * The number of distinct values in a label image is _____ the number of objects (minus one). * Converting an intensity image to a _____ image can be achieved by _____ . * The number of connected components can be _____ the maximal label. 1. A label image is the result of _____ . 2. The number of pixels in a binary image is typically _____ the number of connected components. 3. The number of distinct values in a label image is _____ the number of objects (minus one). 4. Converting an intensity image to a _____ image can be achieved by _____ . 5. The number of connected components can be _____ the maximal label.   ... ... @@ -392,10 +391,10 @@ There are several good reasons not to subtract the background from each pixel in Fill in the blanks, using these words: integrated, mean, number_of_pixels, decrease, increase, sum * Average intensity is just another word for _____ intensity. * The _____ intensity is equal to the mean intensity times the _____ in the measured region. * In an 8-bit image, increasing the size of the measurement region can only _____ the sum intensity. * In a float image, increasing the size of the measurement region can _____ the sum intensity. 1. Average intensity is just another word for _____ intensity. 2. The _____ intensity is equal to the mean intensity times the _____ in the measured region. 3. In an 8-bit image, increasing the size of the measurement region can only _____ the sum intensity. 4. In a float image, increasing the size of the measurement region can _____ the sum intensity.   ... ...
 ... ... @@ -58,11 +58,11 @@ Fill in the blanks, using those words: shrinks, increases, decreases, enlarges. '/> ``` opening( image ) = dilation( erosion( image ) ) opening( image, r ) = dilation( erosion( image, r ), r ) ``` ``` closing( image ) = erosion( dilation( image ) ) closing( image, r ) = erosion( dilation( image, r ), r ) ``` ... ... @@ -72,13 +72,16 @@ closing( image ) = erosion( dilation( image ) ) - Explore effects of morphological closing and opening: - closing can fill holes - closing can connect gaps - opening can remove thin structures - opening can remove thin structures ### Formative assessment TODO True of false? Discuss with your neighbour! 1. Morphological openings on binary images can decrease the number of foreground pixels. 2. Morphological closings on binary images never decreases the number of foreground pixels. 3. Performing a morphological closing a twice in a row does not make sense, because the second closing does not further change the image. ## Top hat filter for local background subtraction ... ... @@ -149,7 +152,11 @@ median_based_background_correction = image - median( image, r) ### Formative assessment TODO Answer below questions. Discuss with your neighbour! 1. What could one do to close small gaps in a binary image? 2. What could one do to remove small objects in a image? 3. What could you use for local background subtraction in a very noisy image? ## Learn more ... ...
 ... ... @@ -4,12 +4,13 @@ Take few sheets of empty (A4) paper. Work in pairs of two. * Draw a typical image analysis workflow: From intensity image to objects shape table. * Write down few (e.g., two) noteworthy facts about: * Write down a few (e.g., two) noteworthy facts about: * Pixel data types * Label images * Intensity measurements * Object shape measurements * Answer below questions: * Write down answers to below questions (there can be multiple answers for some questions): * How can you split touching objects? * What can you use a distance map for? * What can you do to segment spots in prescence of uneven background signal? * What can you do to remove small objects from a binary image?
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