Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A practical and reliable method for correction of EPI distortions caused by susceptibility-induced field inhomogeneity is proposed. Our method integrates two existing algorithms, PLACE and SPHERE.  further improve the correction by embedding an upsampling scheme into the algorithms. The upsampling ratio is optimized using simulations. The number of field maps to be averaged in order to reduce noise is also investigated. The proposed method was applied to images from a phantom and from diffusion tensor imaging of the brain from four normal subjects. The normalized mutual information (NMI) beten reference anatomical T1-ighted images and T2-ighted images before and after correction was calculated and compared. The improved NMI was averaged slicewise across the four subjects to demonstrate the algorithm robustness. Color-coded fractional anisotropy maps and white matter fiber tracking results re also compared visually
['Udomchai Techavipoo', 'Song Lai', 'S. Dimitrov', 'John Lackey', 'Jianrong Shi', 'Xin Guan']
I am writing a research paper on a idea A ROBUST APPROACH FOR CORRECTION OF SUSCEPTIBILITY ARTIFACTS IN EPI
[{"from": "human", "value": "I am writing a research paper on a idea A ROBUST APPROACH FOR CORRECTION OF SUSCEPTIBILITY ARTIFACTS IN EPI"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A practical and reliable method for correction of EPI distortions caused by susceptibility-induced field inhomogeneity is proposed. Our method integrates two existing algorithms, PLACE and SPHERE.  further improve the correction by embedding an upsampling scheme into the algorithms. The upsampling ratio is optimized using simulations. The number of field maps to be averaged in order to reduce noise is also investigated. The proposed method was applied to images from a phantom and from diffusion tensor imaging of the brain from four normal subjects. The normalized mutual information (NMI) beten reference anatomical T1-ighted images and T2-ighted images before and after correction was calculated and compared. The improved NMI was averaged slicewise across the four subjects to demonstrate the algorithm robustness. Color-coded fractional anisotropy maps and white matter fiber tracking results re also compared visually"}]