کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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6029706 | 1580932 | 2013 | 10 صفحه PDF | دانلود رایگان |

A voxel-based algorithm to correct for partial volume effect in PET brain volumes is presented. This method (named LoReAn) is based on MRI based segmentation of anatomical regions and accurate measurements of the effective point spread function of the PET imaging process. The objective is to correct for the spill-out of activity from high-uptake anatomical structures (e.g. grey matter) into low-uptake anatomical structures (e.g. white matter) in order to quantify physiological uptake in the white matter. The new algorithm is presented and validated against the state of the art region-based geometric transfer matrix (GTM) method with synthetic and clinical data. Using synthetic data, both bias and coefficient of variation were improved in the white matter region using LoReAn compared to GTM. An increased number of anatomical regions doesn't affect the bias (<Â 5%) and misregistration affects equally LoReAn and GTM algorithms. The LoReAn algorithm appears to be a simple and promising voxel-based algorithm for studying metabolism in white matter regions.
364Highlights⺠Voxel-based intensity diffusion correction algorithm for PET volumes is presented. ⺠Algorithm relies on accurate measurement of the PSF. ⺠Estimates the true uptake by local regression analysis. ⺠Improves bias and CoV in WM structures compared to the GTM method. ⺠The use of the algorithm reduces intrinsic correlation between GM and WM uptake.
Journal: NeuroImage - Volume 72, 15 May 2013, Pages 183-192