{"title":"用人工智能超越传统的磁共振处理。","authors":"Amir Jahangiri, Vladislav Orekhov","doi":"10.1038/s42004-024-01325-w","DOIUrl":null,"url":null,"abstract":"Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed “impossible”: quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality. Our findings highlight the potential of AI techniques to revolutionize NMR processing and analysis. Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. Here, the authors use AI for quadrature detection using only (Anti-)Echo modulation, accessing uncertainties of signal intensities at each point in a spectrum processed by any given method, and to define a reference-free score of NMR spectrum quality.","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":"1-8"},"PeriodicalIF":5.9000,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42004-024-01325-w.pdf","citationCount":"0","resultStr":"{\"title\":\"Beyond traditional magnetic resonance processing with artificial intelligence\",\"authors\":\"Amir Jahangiri, Vladislav Orekhov\",\"doi\":\"10.1038/s42004-024-01325-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed “impossible”: quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality. Our findings highlight the potential of AI techniques to revolutionize NMR processing and analysis. Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. Here, the authors use AI for quadrature detection using only (Anti-)Echo modulation, accessing uncertainties of signal intensities at each point in a spectrum processed by any given method, and to define a reference-free score of NMR spectrum quality.\",\"PeriodicalId\":10529,\"journal\":{\"name\":\"Communications Chemistry\",\"volume\":\" \",\"pages\":\"1-8\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s42004-024-01325-w.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.nature.com/articles/s42004-024-01325-w\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications Chemistry","FirstCategoryId":"92","ListUrlMain":"https://www.nature.com/articles/s42004-024-01325-w","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Beyond traditional magnetic resonance processing with artificial intelligence
Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed “impossible”: quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality. Our findings highlight the potential of AI techniques to revolutionize NMR processing and analysis. Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. Here, the authors use AI for quadrature detection using only (Anti-)Echo modulation, accessing uncertainties of signal intensities at each point in a spectrum processed by any given method, and to define a reference-free score of NMR spectrum quality.
期刊介绍:
Communications Chemistry is an open access journal from Nature Research publishing high-quality research, reviews and commentary in all areas of the chemical sciences. Research papers published by the journal represent significant advances bringing new chemical insight to a specialized area of research. We also aim to provide a community forum for issues of importance to all chemists, regardless of sub-discipline.