![]() Assignors: MA, JINGFEI Application granted granted Critical Publication of US6466014B1 publication Critical patent/US6466014B1/en Anticipated expiration legal-status Critical Status Expired - Lifetime legal-status Critical Current Links Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.) Filing date Publication date Application filed by GE Medical Systems Global Technology Co LLC filed Critical GE Medical Systems Global Technology Co LLC Priority to US09/650,251 priority Critical patent/US6466014B1/en Assigned to GE MEDICAL SYSTEMS GLOBAL TECHNOLOGY COMPANY, LLC reassignment GE MEDICAL SYSTEMS GLOBAL TECHNOLOGY COMPANY, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Original Assignee GE Medical Systems Global Technology Co LLC Priority date (The priority date is an assumption and is not a legal conclusion. GE Medical Systems Global Technology Co LLC Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.) Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.) Expired - Lifetime Application number US09/650,251 Inventor Jingfei Ma Current Assignee (The listed assignees may be inaccurate. Google Patents Suppression of fat signals in MR water images produced in Dixon imagingĭownload PDF Info Publication number US6466014B1 US6466014B1 US09/650,251 US65025100A US6466014B1 US 6466014 B1 US6466014 B1 US 6466014B1 US 65025100 A US65025100 A US 65025100A US 6466014 B1 US6466014 B1 US 6466014B1 Authority US United States Prior art keywords image fat recited water image data Prior art date Legal status (The legal status is an assumption and is not a legal conclusion. Google Patents US6466014B1 - Suppression of fat signals in MR water images produced in Dixon imaging Journal of Biomolecular NMR Springer Journals US6466014B1 - Suppression of fat signals in MR water images produced in Dixon imaging With a set of 10 commonly used NMR spectra, on average 82.5% of all backbone and side-chain 1H, 13C and 15N resonances could be assigned with an average error rate of 3.5%. The DYNASSIGN algorithm was implemented in the program CYANA and tested with data sets obtained from the experimental NMR data of nine small proteins. Peak-particle dynamics-based simulated annealing was combined with the Hungarian algorithm for local optimization, and a residue-based score was introduced to distinguish between reliable assignments and “unassigned” resonances for which no reliable assignment can be established. Molecular dynamics simulation techniques are used to calculate a trajectory of the system of peak-particles subjected to the potential function in order to find energetically optimal configurations that correspond to correct assignments. Schmucki, Roland Yokoyama, Shigeyuki Güntert, PeterĪ new algorithm, DYNASSIGN, for the automated assignment of NMR chemical shift resonances was developed in which expected cross peaks in multidimensional NMR spectra are represented by peak-particles and assignment restraints are translated into a potential energy function. Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the.
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