Warning:  The EBRAINS Lab will be down today from 21:00 CEST (my timezone)  for ~10 minutes for an update


Last modified by annedevismes on 2021/06/08 11:56
From version 20.1
edited by puchades
on 2020/09/24 12:17
Change comment: There is no comment for this version
To version 12.1
edited by evanhancock
on 2020/07/21 09:38
Change comment: There is no comment for this version

Summary

Details

Page properties
Author
... ... @@ -1,1 +1,1 @@
1 -XWiki.puchades
1 +XWiki.evanhancock
Content
... ... @@ -1,13 +1,13 @@
1 1  == [[image:ilastik_logo.PNG||style="float:right"]] ==
2 2  
3 -== [[image:Pixel_classification workflow.png||style="float:left"]](% style="color:#c0392b" %)Analysis approach for series of rodent brain section image(%%) ==
3 +== (% style="color:#c0392b" %)Analysis approach for series of rodent brain section image(%%) ==
4 4  
5 5  Ilastik is a versatile image analysis tool specifically designed for the classification, segmentation and analysis of biological images based on supervised machine learning algorithms.
6 6  
7 -**There are two main approaches for the analysis of rodent brain section image**
7 +There are two main approaches for the analysis of rodent brain section images.
8 8  
9 9  1. Pixel classification only (with two or more classes)
10 -1. Pixel classification with two classes (//immunoreactivity// and //background//), followed by Object classification with two classes (//objects of interest// and //artefact//).
10 +1. Pixel classification with two classes (//immunoreactivity// and //background//), followed by object classification with two classes (//objects of interest// and //artefact//).
11 11  
12 12  **Which approach is best for my dataset?**
13 13  
Pixel_classification workflow.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.puchades
Size
... ... @@ -1,1 +1,0 @@
1 -1.0 MB
Content