Difference between revisions of "Documentation/Nightly/Modules/FastGrowCut"

From Slicer Wiki
Jump to: navigation, search
 
(14 intermediate revisions by 2 users not shown)
Line 4: Line 4:
 
<!-- ---------------------------- -->
 
<!-- ---------------------------- -->
  
 
+
[[Documentation/4.8/Modules/FastGrowCut|FastGrowCut]] extension has been completely reworked, hugely improved in performance, robustness, and usability, and moved to a built-in effect of Segment editor module named as [https://slicer.readthedocs.io/en/latest/user_guide/module_segmenteditor.html#grow-from-seeds-grow-from-seeds Grow from seeds] effect.
 
 
 
 
 
 
 
 
<!-- ---------------------------- -->
 
{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
 
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
 
{{documentation/{{documentation/version}}/module-introduction-row}}
 
 
 
This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the [http://www.na-mic.org/ NA-MIC website].<br>
 
 
 
Author: Liangjia Zhu, Stony Brook University<br>
 
Author: Ivan Kolesov, Stony Brook University<br>
 
Author: Yi Gao, University of Alabama Birmingham<br>
 
Author: Peter Karasev, Georgia Institute of Technology<br>
 
Author: Allen Tannenbaum, Stony Brook University<br>
 
<!--Contributor2: FIRSTNAME LASTNAME, AFFILIATION<br> -->
 
<!--Contact: FIRSTNAME LASTNAME, <email>john@doe.org</email><br> -->
 
 
 
{{documentation/{{documentation/version}}/module-introduction-row}}
 
 
 
<!--{{documentation/{{documentation/version}}/module-introduction-logo-gallery
 
|[[File:GeorgiaTech_Logo.svg]]
 
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}  <-Replace this logo with yours
 
}} -->
 
 
 
 
 
{{documentation/{{documentation/version}}/module-introduction-end}}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
<!-- ---------------------------- -->
 
{{documentation/{{documentation/version}}/module-section|Module Description}}
 
 
 
This is a fast implementation of the GrowCut method. It supports multi-label segmentation and user online interactions. Please see the references below for more details.
 
 
 
<!--Here comes a description what the module is good for. Explain briefly how it works and point to the [[documentation/{{documentation/version}}/Modules/{{documentation/modulename}}#References|references]] giving more details on the algorithm.
 
If you are documenting a CLI, the description should be extracted from the corresponding XML description. This could be done automatically using the following wiki template:<pre>{{documentation/{{documentation/version}}/module-description}}
 
{{documentation/{{documentation/version}}/module-description}} -->
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
<!-- ---------------------------- -->
 
<!-- {{documentation/{{documentation/version}}/module-section|Use Cases}}
 
N/A -->
 
 
 
 
 
 
 
 
 
 
 
 
 
<!-- ---------------------------- -->
 
{{documentation/{{documentation/version}}/module-section|Tutorials}}
 
 
 
 
 
Step 1.) Add data volume to segment
 
 
 
[[File:LoadMeningioma.png|500px]]
 
 
 
 
 
Step 2.) Go to the “Editor” module, select the volume loaded in Step 1 as the “Master Volume” in the “Create and Select Label Maps” drop-down menu
 
 
 
[[File:StartEditorMeningioma.png|500px]]
 
 
 
 
 
Step 3.) Select the “CarreraSlice” effect in the “Edit Selected Label Map” drop-down menu
 
 
 
[[File:CarreraSliceEffect.png|50px]]
 
 
 
 
 
Step 4.) Set the “Radius” parameter, the "Number of Iterations" and press the “Start Interactive Segmentor” button ( CarreraSlice is now running in the background until the “Stop Interactive Segmentor” button is pressed)
 
 
 
[[File:StartBotMeningioma.png|500px]]
 
 
 
 
 
Step 5.) Turn “On” all three slice views in the 3D Plane
 
 
 
[[File:TurnOnSlices3DMeningioma.png|500px]]
 
 
 
Step 6.) Initialize the segmentation using fast GrowCut
 
* (a) go to PaintEffect to draw seed regions (label 1 for foreground and 2 for background), then press 'G' to run fast GrowCut.
 
[[File:FGCSeed.png|500px]] [[File:FGCSeg1.png|500px]]
 
 
 
* (b) If not satified, press 'S' to toggle between seed image and segmentation result. Edit on the seed image to reduce over/under segmentaions.
 
[[File:FGCSeed2.png|500px]]
 
 
 
* (c) Once finished editing on the seed image, press 'G' to run fast GrowCut again.
 
[[File:FGCSeg2.png|500px]]
 
 
 
The steps 6 (b) and (c) may be repeated a couple of times until satisfied.
 
 
 
Step 7.) Once satisfied with the initialization, press 'M' to start KSlice interactive segmentation. The energy functionals available are:
 
* (a) press 'F' for local-global Chan-Vese segmentation
 
* (b) press 'U' for mean curvature smoothing
 
* (c) press 'E' for Chan-Vese segmentation
 

Latest revision as of 17:00, 5 November 2018

Home < Documentation < Nightly < Modules < FastGrowCut


For the latest Slicer documentation, visit the read-the-docs.


FastGrowCut extension has been completely reworked, hugely improved in performance, robustness, and usability, and moved to a built-in effect of Segment editor module named as Grow from seeds effect.