Last modified by annedevismes on 2021/06/08 11:56
From version 1.1
edited by sharoncy
on 2020/03/09 13:49
Change comment: There is no comment for this version
To version 1.5
edited by puchades
on 2020/03/25 14:46
Change comment: There is no comment for this version

Summary

Details

Page properties
Title
... ... @@ -1,1 +1,1 @@
1 -3. Image segmentation with ilastik
1 +4. Image segmentation with ilastik
Author
... ... @@ -1,1 +1,1 @@
1 -XWiki.sharoncy
1 +XWiki.puchades
Content
... ... @@ -1,12 +1,15 @@
1 -== H2 Headings Will Appear in Table of Content ==
1 +== Analysis approach for series of rodent brain section image ==
2 2  
3 +There are two main approaches for the analysis of rodent brain section images.
3 3  
4 -Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
5 +1. Pixel classification only (with two or more classes)
6 +1. Pixel classification with two classes (//immunoreactivity// and //background//), followed by object classification with two classes (//objects-of-interest// and //artefact//).
5 5  
6 ->This is a quote. You can add a quote by selecting some text and clicking the quote button in the editor.
8 +**Which approach is best for my dataset?**
7 7  
8 -Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
10 +As a general rule, pixel classification is suitable for images in which there are clear differences in the colour, intensity and/ or texture of the feature-of-interest versus the background and other structures.  If there is non-specific labelling in the image that is very similar in appearance to the labelling-of-interest, object classification may allow the non-specific labelling to be filtered out based on object level features such as size and shape. The best approach is determined by trial and error.
9 9  
12 +
10 10  === H3 Headings Will Appear In The Table of Content ===
11 11  
12 12  ==== You can also add images ====