HIGHLIGHTS
- who: Neda Zaker from the (UNIVERSITY) have published the Article: Direct inference of Patlak parametric images in whole-body PET/CT imaging using convolutional neural networks, in the Journal: (JOURNAL)
- what: Purpose This study proposed and investigated the feasibility of estimating Patlak-derived influx rate constant (Ki) from standardized uptake value (SUV) and/or dynamic PET image series. To address the abovementioned challenges of dynamic PET imaging, the authors propose a direct and fast method for generating Patlak maps from dynamic passes and/or SUV images with the aid of deep learning techniques. The study . . .
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