4Dflow-unwrap: A collection of python-based phase unwrapping algorithms

Motivation: Low-Venc PC-MRI acquisitions present the advantage of higher velocity-to-noise ratio (VNR). To the best of the author’s knowledge, no Python-based public repository exists with 4D flow MRI unwrapping algorithms and realistic examples. Goal(s): To share a collection of simple unwrapping tools for 4D Flow MRI and test their performance. Approach: To use three established unwrapping techniques to create a Python package to unwrap 4D flow MRI data. Results: We demonstrate the performance of these algorithms on aortic data including multiple Venc values and undersampling factors. Impact: The Python repository with a collection of simple unwrapping tools facilitates access to unwrapping techniques. These scripts can readily be used to unwrap any PC-MRI dataset.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/4679
Primary Topic
Optical measurement and interference techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

4Dflow-unwrap: A collection of python-based phase unwrapping algorithms

Pietro Dirix, Sebastian Kozerke, Luuk Jacobs
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Optical measurement and interference techniques
article

4Dflow-unwrap: A collection of python-based phase unwrapping algorithms

Pietro Dirix, Sebastian Kozerke, Luuk Jacobs
article en

Abstract

Motivation: Low-Venc PC-MRI acquisitions present the advantage of higher velocity-to-noise ratio (VNR). To the best of the author’s knowledge, no Python-based public repository exists with 4D flow MRI unwrapping algorithms and realistic examples. Goal(s): To share a collection of simple unwrapping tools for 4D Flow MRI and test their performance. Approach: To use three established unwrapping techniques to create a Python package to unwrap 4D flow MRI data. Results: We demonstrate the performance of these algorithms on aortic data including multiple Venc values and undersampling factors. Impact: The Python repository with a collection of simple unwrapping tools facilitates access to unwrapping techniques. These scripts can readily be used to unwrap any PC-MRI dataset.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 79%
Optical measurement and interference techniques
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