Pré-Publication, Document De Travail Année : 2025

gGRAPPA: A Flexible, GPU-Accelerated Python Package for Fast and Efficient generalized GRAPPA Reconstruction

Résumé

Motivation: Existing open-source MR reconstruction tools often fail to efficiently utilize GPU resources and lack support for generalized GRAPPA implementations. Many tools are limited to 2D or 3D reconstruction, and few incorporate advanced techniques such as 2D-CAIPIRINHA, which enhances imaging capabilities. Goal(s): gGRAPPA aims to provide a fast, flexible, and open-source tool for generalized GRAPPA/CAIPI reconstruction. Approach: By utilizing PyTorch, gGRAPPA runs multiple convolutional windows in batch mode to optimize GPU memory usage and accelerate reconstruction times. Results: gGRAPPA achieves up to a 65x speedup over CPU implementations and a 6x speedup compared to non-batched GPU methods, enabling efficient and fast reconstruction MRI scans.

Purpose: Generalized autocalibrating partially parallel acquisitions (GRAPPA) is widely used in MRI reconstruction, but conventional implementations, such as those in MATLAB on CPUs, are computationally intensive, especially for high-dimensional data, and those in Python on GPU not implementing a "generalized GRAPPA". We developed gGRAPPA to address these limitations by (1) utilizing GPU acceleration for high-speed processing and (2) supporting flexible GRAPPA configurations (2D and 3D). Furthermore, gGRAPPA allows users to have full control on the reconstruction by tuning key parameters like kernel size and regularization strength. This tool aims to provide a generalized and flexible GRAPPA reconstruction framework allowing fast and efficient processing on GPU.

Impact: gGRAPPA provides a fast, flexible, and open-source solution for GRAPPA MRI reconstruction on GPU, significantly accelerating reconstruction times and enabling ultra high-resolution imaging reconstruction, thereby supporting advanced research applications across diverse MRI protocols.

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hal-04906124 , version 1 (22-01-2025)

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  • HAL Id : hal-04906124 , version 1

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Maxime Bertrait, Chaithya Giliyar Radhakrishna, Philippe Ciuciu. gGRAPPA: A Flexible, GPU-Accelerated Python Package for Fast and Efficient generalized GRAPPA Reconstruction. 2025. ⟨hal-04906124⟩
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