{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/robust-retrospective-frequency-and-phase","title":"Robust Retrospective Frequency and Phase Correction for Single-voxel MR Spectroscopy","arxiv_id":"1807.08915","date":"2018-09-14","proceeding":null,"authors":[],"abstract":"Purpose: subject motion and static field (B$_0$) drift are known to reduce\nthe quality of single voxel MR spectroscopy data due to incoherent averaging.\nRetrospective correction has previously been shown to improve data quality by\nadjusting the phase and frequency offset of each average to match a reference\nspectrum. In this work, a new method (RATS) is developed to be tolerant to\nlarge frequency shifts (greater than 7Hz) and baseline instability resulting\nfrom inconsistent water suppression. Methods: in contrast to previous\napproaches, the variable-projection method and baseline fitting is incorporated\ninto the correction procedure to improve robustness to fluctuating baseline\nsignals and optimization instability. RATS is compared to an alternative\nmethod, based on time-domain spectral registration (TDSR), using simulated data\nto model frequency, phase and baseline instability. In addition, a J-difference\nedited glutathione in-vivo dataset is processed using both approaches and\ncompared. Results: RATS offers improved accuracy and stability for large\nfrequency shifts and unstable baselines. Reduced subtraction artifacts are\ndemonstrated for glutathione edited MRS when using RATS, compared with\nuncorrected or TDSR corrected spectra. Conclusion: the RATS algorithm has been\nshown to provide accurate retrospective correction of SVS MRS data in the\npresence of large frequency shifts and baseline instability. The method is\nrapid, generic and therefore readily incorporated into MRS processing pipelines\nto improve lineshape, SNR and aid quality assessment.","url_abs":"http://arxiv.org/abs/1807.08915v3","url_pdf":"http://arxiv.org/pdf/1807.08915v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"robust-retrospective-frequency-and-phase","repo_url":"https://github.com/martin3141/rats","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}