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Susceptibility distortion correction in diffusion MRI dataset

Key Investigators

• Sedigheh Dargahi (École de technologie supérieure , Canada)
• Sylvain Bouix (École de technologie supérieure , Canada)

Presenter location: Online

Project Description

The aim of this project is to mitigate susceptibility distortions in dMRI dataset by offering a deep learning solution as an alternative of traditional state-of-the-arts methods, only using a single blip-up or blip-down image.

Objective

1. Objective A. Simplifying dMRI acquisition protocols by utilizing just one of the blip-up or blip-down image as input for the model. This approach can reduce scan time, potentially halving the duration of dMRI acquisitions.

2. Objective B. Facilitating more precise analysis and promoting advancements in our understanding of brain by equipping researchers with more efficient and accurate tools.

Approach and Plan

No response

Progress and Next Steps

I successfully debugged the initial error in the extension’s Python code. However, there remains an unresolved issue with an error, undefined function in my model. I am currently working on resolving this problem. Next Steps:

1. Address the undefined function issue.
2. Test the built extension.

Illustrations

No response

Background and References

No response