dMRI QC: implementation and automation

Title

dMRI QC: implementation and automation

Leaders

Dr. Thomas Close Dr. Mahdieh Dashtbani Moghari

Collaborators

Dr. Thomas Close

Brainhack Global 2022 Event

Brainhack Australasia

Project Description

• What are you doing, for whom, and why? I am a USYD NIF fellow from school of biomedical engineering. I work under Prof Fernando Calamante ’s supervision.
• What makes your project special and exciting? The proposed dMRI QC pipeline is called PreQual which is a pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images. The preprocessing and QC processes need to be done before performing any analysis on dMRI data.
• How to get started? Start with implementing PreQual pipeline (https://github.com/MASILab/PreQual), then think about how to eliminate the manual inspection of the generated images and graphs in order to fully automise the QC process.
• Where to find key resources? github page: https://github.com/MASILab/PreQual paper: “PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images”—-> https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.28678

Link to project repository/sources

https://github.com/MASILab/PreQual

Goals for Brainhack Global

• Implement the pipeline
• Try some ideas on how to fully automate the QC process

Good first issues

1. issue one: Read the paper: “PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images”—-> https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.28678
2. issue two: https://github.com/MASILab/PreQual

Communication channels

NA

Skills

• Python
• dMRI processing
• experience with machine learning

Onboarding documentation

Read the paper: “PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images”—-> https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.28678

What will participants learn?

• how to implement a dMRI QC pipeline
• how to interpret the results
• how to automate a QC process

Data to use

NA

Number of collaborators

more

Credit to collaborators

NA

Image

Type

pipeline_development

Development status

2_releases_existing

Topic

diffusion

Tools

other

Programming language

Python

Modalities

DWI

Git skills

0_no_git_skills, 4_not_applicable

Anything else?

NA

Things to do after the project is submitted and ready to review.

• Add a comment below the main post of your issue saying: Hi @brainhackorg/project-monitors my project is ready!
• Twitter-sized summary of your project pitch.