San-Chao HwangChing YaoChao-Hsien HsiehJYH-HORNG CHEN2018-09-102018-09-102006-0215525031http://scholars.lib.ntu.edu.tw/handle/123456789/325445https://www.scopus.com/inward/record.uri?eid=2-s2.0-33644932156&doi=10.1002%2fcmr.b.20058&partnerID=40&md5=7cb1fb6c4f6f63ace033bd3c47fd2b1aThis study describes the application of the method of feedback linearization neural networks, known from neural network computing, to the problem of gradient preemphasis. This approach of preemphasis adjustment does not require an iterative procedure between measurement and adjustment, therefore is essentially instantaneous in its execution. Based on our study, gradient compensation determined by our procedure effectively suppressed eddy current-induced geometric distortion and spatial shift of diffusion-weighted EPI images. © 2006 Wiley Periodicals, Inc.DW-EPI; Eddy current; Feedback linearization neural networks; Preemphasis adjustmentjournal article10.1002/cmr.b.200582-s2.0-33644932156WOS:000235523200001