Effect of Scan Quality on Pipeline Result Discrepancy
Short description and the goals for the OHBM BrainHack
As we all know, neuroimaging experiment results are subject to reproducibility issues. Computing the same measure (on the same data) across multiple pipelines can yield different results.
We will run FSL, FreeSurfer, and ASHS on a subset of Prevent-AD data to obtain volumetric measures across the three pipelines. We will then find the discrepancies in these measures between the pipelines, and see if we can explain the discrepancies given the properties of the input scans. We will do this by running MRIQC on the scans, and correlating the outputted image quality metrics with the pipelines discrepancies.
As we all know, neuroimaging experiment results are subject to reproducibility issues. Computing the same measure (on the same data) across multiple pipelines can yield different results.
We will run FSL, FreeSurfer, and ASHS on a subset of Prevent-AD data to obtain volumetric measures across the three pipelines. We will then find the discrepancies in these measures between the pipelines, and see if we can explain the discrepancies given the properties of the input scans. We will do this by running MRIQC on the scans, and correlating the outputted image quality metrics with the pipelines discrepancies.
Short name for the Discord chat channel (~15 chars)
discrepancies
Please read and follow the OHBM Code of Conduct
[X] I agree to follow the OHBM Code of Conduct during the hackathon
Title
Effect of Scan Quality on Pipeline Result Discrepancy
Short description and the goals for the OHBM BrainHack
As we all know, neuroimaging experiment results are subject to reproducibility issues. Computing the same measure (on the same data) across multiple pipelines can yield different results. We will run FSL, FreeSurfer, and ASHS on a subset of Prevent-AD data to obtain volumetric measures across the three pipelines. We will then find the discrepancies in these measures between the pipelines, and see if we can explain the discrepancies given the properties of the input scans. We will do this by running MRIQC on the scans, and correlating the outputted image quality metrics with the pipelines discrepancies.
Link to the Project
https://github.com/jacobsanz97/Pipeline-Discrepancy-Exploration
Image for the OHBM brainhack website
No response
Project lead
jacobsanz97 (Jacob's GitHub) mtorabi59 (Mohammad's GitHub) tylerwishard (Tyler's GitHub)
lgbty_libros (Tyler's discord)
Main Hub
Glasgow
Other Hub covered by the leaders
Skills
Python, FreeSurfer, FSL, ASHS
Recommended tutorials for new contributors
Good first issues
Run more segmentation pipelines on our data!
Twitter summary
As we all know, neuroimaging experiment results are subject to reproducibility issues. Computing the same measure (on the same data) across multiple pipelines can yield different results. We will run FSL, FreeSurfer, and ASHS on a subset of Prevent-AD data to obtain volumetric measures across the three pipelines. We will then find the discrepancies in these measures between the pipelines, and see if we can explain the discrepancies given the properties of the input scans. We will do this by running MRIQC on the scans, and correlating the outputted image quality metrics with the pipelines discrepancies.
Short name for the Discord chat channel (~15 chars)
discrepancies
Please read and follow the OHBM Code of Conduct