Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -8,7 +8,7 @@
8	8
9	9	For //ilastik// (Borg et al.2019) images are downscaled in order to enable efficient processing. The pixel classification algorithm relies on input from manual user annotations of the training images, and the features ‒ intensity, edge and/or texture ‒ of the image pixels. The resizing factor is determined by trial and error, with a test run performed with //ilastik// on images of different sizes to determine the optimal resolution for segmentation. As an example, in Yates et al., 2019, the images were downscaled by a factor of 0.1 and 0.05 for cellular features and Alzheimer's plaques respectively (factor applies to the image width here).
10	10
11		-== (% style="color:#c0392b" %)Naming convention(%%) ==
	11	+=== (% style="color:#c0392b" %)Naming convention(%%) ===
12	12
13	13	For QUINT analysis, Nutil Quantifier quantifies objects extracted from segmentations and registers them to regions defined by customised atlas maps. To match segmentations and corresponding atlas maps together, Nutil Quantifier relies on a unique ID in the file name of both files.The ID should be unique to the particular brain section and in the format: sXXX.., with XXX.. representing the section number. The section number should reflect the serial order and spacing of the sections (e.g. s002, s006, s010 for every 4^^th^^ section starting with section 2).
14	14
...	...	@@ -17,7 +17,7 @@
17	17	(It is fine to include a string of letters and numbers followed by the unique ID).
18	18
19	19
20		-== (% style="color:#c0392b" %)Running the transformation(%%) ==
	20	+=== (% style="color:#c0392b" %)Running the transformation(%%) ===
21	21
22	22	Consult the Nutil user manual for detailed procedure (lincluded in the Nutil package available for download at Nitrc.org)
23	23