New extension is added for lung CT segmentation and analysis for COVID-19 assessment. It is developed by Prof. Rudolf Bumm ( @rbumm ), a clinician in KSGR (Chur, Switzerland; with some help from Slicer core developers to polish things up), which is a nice demonstration of how Python scripting in Slice…

And you are using the “Show/hide final segments in 3D” button to create 3D VIEW ? [image]

Thank you for replying. Before reaching this step, when I click on show/hide preview in 3D under the Thresholds section, the entire 3D segment is black. I can change the opacity but the 3D model remains mono-colored. When I select the show/hide final segments in 3D under the Statistics section, the…

[3D slicer LUNG CT COVID output segments shown] This is what I obtain when I do not click on show preview in 3D and only display show segments in 3D.

I can not yet reproduce your black preview in 3D, mine (in Slicer 4.13 and LCTA 2.47) is colored. Anyway, if you enabled the 3D preview, you should “Hide preview in 3D” afterwards to obtain only the final output segmentation in the 3D view. [image]

Hi Rudolf, I would like to test the package on rodents’ lung tissue analysis. When I move to step 2, that is the step I would need to place a few seeds. However, the image is kind of resample to very large voxels makes the images blurred. Dose this package only good for human CT images? Thank y…

Hi, The package has been developed for human CT and the Lung CT Segmenter module does not yet work reliably with Micro CT. However, you could go to “Segment Editor”, and create a “lung segmentation” with “right lung” and “left lung” by using the “Grow From Seeds” effect. As soon as you have good lu…

I think the only value hardcoded for human clinical CT is the preview image resolution of 2mm. This is probably too large for microCT. You can easily modify this value by editing this line in LungCTSegmenter.py file: rbumm/SlicerLungCTAnalyzer/blob/0ebbfee16245c44c5f2b3e848f93eb3e045ee6dc/…

@lassoan never thought you could set volume spacing from the Volumes extension directly. So now I can confirm that setting a rodent microCT´s spacing from 0.133mm 10 x larger enables the use of Lung CT Segmenter [image] with the following lung thresholds: [image] The other option does not work…

[image] lassoan: parameters = {"outputPixelSpacing": "2.0,2.0,2.0", "InputVolume": self.inputVolume, "interpolationType": "linear", "OutputVolume": self.resampledVolume} To my understanding setting 914. parameters = {"outputPixelSpacing": "0.,0.,0.", "InputVolume": self.inputVolume, "interpo…

0 spacing is invalid, do not set that value. If you don’t resample then computation time will be too long for interactive use. If you do not want to expose spacing as a parameter to the users (because it is too technical) then we could add a “lung size” (diameter of the lungs along a chosen anatomic…

LungCTAnalyzer extension for lung CT segmentation and analysis for COVID-19 assessment

Support

Topic		Replies	Views
LungCTAnalyzer error: Input lung CT is invalid Support lungctanalyzer	26	1337	June 29, 2022
LungCTAnalyzer extension used for research paper Success stories lungctanalyzer	1	357	November 20, 2022
Exporting CSV with parenchyma analysis module Support cip	58	2325	April 13, 2022
Lung CT Analyzer now supports lung lobes and emphysema statistics Support	5	520	July 30, 2024
Same problem：AI segmentation with lung CT analyzer error Support lungctanalyzer	0	55	March 4, 2025

LungCTAnalyzer extension for lung CT segmentation and analysis for COVID-19 assessment

Related topics