@@ -325,11 +325,27 @@ Try increasing the 'sigma' value to three and clicking run again:
325325of 3" width='40%'}
326326
327327You should see a new 'nuclei_gaussian_σ=3.0' layer that is much more heavily blurred.
328- If you used the ` + ` /` - ` buttons to set the sigma value, you may see many more
329- decimal places in the layer name e.g. 'nuclei_gaussian_σ=3.00000000000000'.
330- If so, double click on the layer name to re-name it to ` nuclei_gaussian_σ=3.0 ` .
331328
332- What's happening here? What exactly does a gaussian blur do? A gaussian blur is
329+ ::::::::::::::::::::::::::::::::::::: callout
330+
331+ ## Renaming Layer Names
332+
333+ The Gaussian filter plugin uses the special character ` σ ` in the layer names.
334+ This naming convention makes it difficult to type layer names in the Napari
335+ console (unless your keyboard has the ` σ ` character). To make life easier
336+ change the name of the added layer now. Double click on the layer name, delete ` σ `
337+ and change it to ` sigma `
338+
339+ ![ ] ( fig/layer-rename.png ) {alt="The mouse cursor hovers over a napari image layer named nuclei_gaussian_sigma=1.0." width='70%'}
340+
341+
342+ Similarly, if you used the ` + ` /` - ` buttons to set the sigma value, you may see excessive
343+ decimal places in the layer name e.g. ` nuclei_gaussian_σ=3.00000000000000 ` .
344+ If so, double click on the layer name to re-name it to ` nuclei_gaussian_sigma=3.0 ` .
345+
346+ :::::::::::::::::::::::::::::::::::::
347+
348+ What's happening here? What exactly does a gaussian blur do? A gaussian blur is
333349an example of a 'linear filter' which is used to manipulate pixel values in
334350images. When a filter is applied to an image, each pixel value is replaced by
335351some combination of the pixel values around it. For example, below is shown a
@@ -510,23 +526,25 @@ shrink in size. Increasing the 'Footprint size' of the filter enhances the effec
510526
511527## Thresholding the blurred image
512528
513- First, let's clean up our layer list. Make sure you only have the ' nuclei'
514- layer in the layer list - select any others and remove them by clicking the ![ ] (
529+ First, let's clean up our layer list. Make sure you only have the ` nuclei ` and
530+ ` nuclei_gaussian_sigma=3.0 ` layers in the layer list - select any others and remove them by clicking the ![ ] (
515531https://raw.githubusercontent.com/napari/napari/main/src/napari/resources/icons/delete.svg
516- ){alt="A screenshot of Napari's delete layer button" height='30px'} icon. Also,
517- close all filter settings panels on the right side of Napari (apart from the
532+ ){alt="A screenshot of Napari's delete layer button" height='30px'} icon.
533+ Close all filter settings panels on the right side of Napari (apart from the
518534gaussian settings) by clicking the tiny ` X ` icon at their top left corner.
519535
520- Now let's try thresholding our image again. Make sure you set your gaussian blur
521- sigma to three, then click 'Apply Gaussian Filter'.
536+ If you don't have the ` nuclei_gaussian_sigma=3.0 ` in your layer list then make it now
537+ using the Gaussian Filter with sigma set to three. You may need to rename the layer,
538+ replacing ` σ ` with ` sigma ` .
522539
523- Then, we'll apply the same threshold as before, now to the
524- 'nuclei_gaussian_σ=3.0' layer:
540+ Now let's try thresholding our image again.
541+ We'll apply the same threshold as before, now to the
542+ ` nuclei_gaussian_sigma=3.0 ` layer:
525543
526544``` python
527545
528546# Get the image data for the blurred nuclei
529- blurred = viewer.layers[" nuclei_gaussian_σ =3.0" ].data
547+ blurred = viewer.layers[" nuclei_gaussian_sigma =3.0" ].data
530548
531549# Create mask with a threshold of 8266
532550blurred_mask = blurred > 8266
@@ -578,7 +596,7 @@ Finally, open the `napari-matplotlib` histogram again with:
578596the nuclei image after a gaussian blur. The left contrast limit is set
579597to 0.134."}
580598
581- Make sure you have 'nuclei_gaussian_σ =3.0' selected in the layer list (should
599+ Make sure you have 'nuclei_gaussian_sigma =3.0' selected in the layer list (should
582600be highlighted in blue).
583601
584602You should see that this histogram now runs from 0 to 1, reflecting the new
@@ -588,7 +606,7 @@ threshold between the two peaks - around 0.134:
588606``` python
589607
590608# Get the image data for the blurred nuclei
591- blurred = viewer.layers[" nuclei_gaussian_σ =3.0" ].data
609+ blurred = viewer.layers[" nuclei_gaussian_sigma =3.0" ].data
592610
593611# Create mask with a threshold of 0.134
594612blurred_mask = blurred > 0.134
@@ -633,7 +651,7 @@ clear that some areas are still missed or incorrectly labelled.
633651## Automated thresholding
634652
635653First, let's clean up our layer list again. Make sure you only have the
636- 'nuclei', 'mask', 'blurred_mask' and 'nuclei_gaussian_σ =3.0' layers in the
654+ 'nuclei', 'mask', 'blurred_mask' and 'nuclei_gaussian_sigma =3.0' layers in the
637655layer list - select any others and remove them by clicking the ![ ] (
638656https://raw.githubusercontent.com/napari/napari/main/src/napari/resources/icons/delete.svg
639657){alt="A screenshot of Napari's delete layer button" height='30px'} icon. Then,
@@ -648,7 +666,7 @@ the most common methods is _Otsu thresholding_, which we will look at now.
648666
649667Let's go ahead and apply this to our blurred image:
650668
651- - Select 'nuclei_gaussian_σ =3.0' in the ` Image ` row
669+ - Select 'nuclei_gaussian_sigma =3.0' in the ` Image ` row
652670- Select 'otsu' as the method
653671- Click the 'Apply Thresholding' button
654672
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