Open-source, Flexible, and Reproducible Workflow for Data Acquisition, Reconstruction, and Post-processing Based on Pulseq and Open Recon

Motivation: Vendor-provided image reconstruction is seen by researchers as a black box and is oftentimes restrictive with regard to supporting novel acquisition strategies or including cutting edge third-party software libraries. Goal(s): To implement an open-source data acquisition, reconstruction, and post-processing pipeline. Approach: We combine vendor-neutral sequence programming in Pulseq with vendor's "Open Recon" environment. Results: We demonstrate the functionality of raw-data-to-complex-image and image-to-image Open Recon containers for four Pulseq sequences: GRE, GRE with GRAPPA, TSE and multi-echo spin echo. Impact: We demonstrate a successful integration of Pulseq with Open Recon, thereby establishing an open-source, flexible, and reproducible workflow for data acquisition, reconstruction, and post-processing, and validate this workflow with four example sequences.