Parametric ATT and CBF Mapping Using a Three-Dimensional Convolutional Neural Network

A CNN algorithm was proposed to estimate ATT and CBF simultaneously, using multi-TI ASL, acquiring ASL images at multiple PLDs. Hierarchical structure of CNN was used to reduce the estimation error of ATT and CBF. The proposed method successfully estimated ATT and CBF maps using reduced numbers of TIs or averages with a higher accuracy than a conventional non-linear model fitting. The successful estimation of ATT and CBF using our H-CNN may allow a total scan time reduction with a smaller number of TIs or averages and improvements of image quality when a part of acquisition is corrupted.