[1]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China. Electronic address: maxwell4444@hotmail.com.
[2]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China; Shanghai Medical Instrumentation College, University of Shanghai Science and Technology, Shanghai 200093, China. Electronic address: zhoumin_ecnu@163.com.
[3]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China. Electronic address: sullyying@126.com.
[4]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China. Electronic address: weiliu925@gmail.com.
[5]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China. Electronic address: gyang@phy.ecnu.edu.cn.
[6]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China. Electronic address: dmwu@phy.ecnu.edu.cn.
[7]Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China. Electronic address: yzhou12.yd@gmail.com.
[8]Center for Developmental Neuropsychiatry, Columbia University Department of Psychiatry & New York State Psychiatric Institute, Unit 74, 1051 Riverside Drive, New York, NY 10032, USA. Electronic address: PetersoB@nyspi.columbia.edu.
[9]Center for Developmental Neuropsychiatry, Columbia University Department of Psychiatry & New York State Psychiatric Institute, Unit 74, 1051 Riverside Drive, New York, NY 10032, USA; Epidemiology Division & MRI Unit, Columbia University Department of Psychiatry & New York State Psychiatric Institute, Unit 24, 1051 Riverside Drive, New York, NY 10032, USA. Electronic address: dx2103@columbia.edu.
Diffusion kurtosis imaging (DKI) is a new model in magnetic resonance imaging (MRI) characterizing restricted diffusion of water molecules in living tissues. We propose a method for fast estimation of the DKI parameters. These parameters - apparent diffusion coefficient (ADC) and apparent kurtosis coefficient (AKC) - are evaluated using an alternative iteration schema (AIS). This schema first roughly estimates a pair of ADC and AKC values from a subset of the DKI data acquired at 3 b-values. It then iteratively and alternately updates the ADC and AKC until they are converged. This approach employs the technique of linear least square fitting to minimize estimation error in each iteration. In addition to the common physical and biological constrains that set the upper and lower boundaries of the ADC and AKC values, we use a smoothing procedure to ensure that estimation is robust. Quantitative comparisons between our AIS methods and the conventional methods of unconstrained nonlinear least square (UNLS) using both synthetic and real data showed that our unconstrained AIS method can significantly accelerate the estimation procedure without compromising its accuracy, with the computational time for a DKI dataset successfully reduced to only 1 or 2min. Moreover, the incorporation of the smoothing procedure using one of our AIS methods can significantly enhance the contrast of AKC maps and greatly improve the visibility of details in fine structures. ;
(8.0+极速模式)