A new hybrid non-clustering VOP compression algorithm

Motivation: Compression of SAR matrices can take very long for large data sets and large channel counts when using non-clustering algorithms that show the highest compression efficiency. Goal(s): The goal of this study was to develop an algorithm that performs the compression faster while maintaining the compression efficiency. Approach: We use a hybrid method that combines different algorithms to form a hybrid algorithm with greatly increased calculation speed. Results: The new compression algorithm outperforms the older non-clustering compression algorithms at all VOP counts while maintaining the compression efficiency. Impact: VOP compression is important for local SAR supervision and constraint pulse calculation in parallel transmission. We propose a new algorithm for non-clustered compression that greatly increases calculation speed, which is important especially at large channel counts.

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/10.58530/2024/3733
Primary Topic
Blind Source Separation Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A new hybrid non-clustering VOP compression algorithm

Stephan Orzada, Thomas M. Fiedler, Mark E. Ladd
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
Blind Source Separation Techniques
article

A new hybrid non-clustering VOP compression algorithm

Stephan Orzada, Thomas M. Fiedler, Mark E. Ladd
article en

Abstract

Motivation: Compression of SAR matrices can take very long for large data sets and large channel counts when using non-clustering algorithms that show the highest compression efficiency. Goal(s): The goal of this study was to develop an algorithm that performs the compression faster while maintaining the compression efficiency. Approach: We use a hybrid method that combines different algorithms to form a hybrid algorithm with greatly increased calculation speed. Results: The new compression algorithm outperforms the older non-clustering compression algorithms at all VOP counts while maintaining the compression efficiency. Impact: VOP compression is important for local SAR supervision and constraint pulse calculation in parallel transmission. We propose a new algorithm for non-clustered compression that greatly increases calculation speed, which is important especially at large channel counts.

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
Affordable and clean energy
Openalex Percentile: Top 76%
Blind Source Separation Techniques
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