Model-based joint reconstruction for multi b-value diffusion-weighted imaging

Zhongbiao Xu; Li Guo; Wenxing Fang; Chenguang Zhao; Yingjie Mei; Zhifeng Chen; Wufan Chen; Ed X. Wu; Feng Huang; Yanqiu Feng

Model-based joint reconstruction for multi b-value diffusion-weighted imaging

Zhongbiao Xu
, Li Guo
, Wenxing Fang
, Chenguang Zhao
, Yingjie Mei
, Zhifeng Chen
, Wufan Chen
, Ed X. Wu
, Feng Huang
, Yanqiu Feng

Research output: Contribution to conference › Abstract › peer-review

Abstract

In current multi b-value DWI, each b-value image is usually reconstructed independently by using parallel MRI techniques. In this work, wepropose a model-based joint reconstruction method for the reconstruction of under-sampled multi b-value DWI data. The proposed method candirectly estimate quantitative parameters form k-space data, and exploit inter-image constraint to improve the quality of reconstructed image.

Original language	English
Number of pages	2
Publication status	Published - 2017
Externally published	Yes
Event	Annual Meeting of ISMRM 2017 - Honolulu, United States of America Duration: 22 Apr 2017 → 27 Apr 2017 Conference number: 25th https://www.ismrm.org/2017-annual-meeting-exhibition/

Conference

Conference	Annual Meeting of ISMRM 2017
Country/Territory	United States of America
City	Honolulu
Period	22/04/17 → 27/04/17
Internet address	https://www.ismrm.org/2017-annual-meeting-exhibition/

Cite this

@conference{5767a3c03cf44cc4a5cee76f6de3d96d,

title = "Model-based joint reconstruction for multi b-value diffusion-weighted imaging",

abstract = "In current multi b-value DWI, each b-value image is usually reconstructed independently by using parallel MRI techniques. In this work, wepropose a model-based joint reconstruction method for the reconstruction of under-sampled multi b-value DWI data. The proposed method candirectly estimate quantitative parameters form k-space data, and exploit inter-image constraint to improve the quality of reconstructed image.",

author = "Zhongbiao Xu and Li Guo and Wenxing Fang and Chenguang Zhao and Yingjie Mei and Zhifeng Chen and Wufan Chen and Wu, \{Ed X.\} and Feng Huang and Yanqiu Feng",

year = "2017",

language = "English",

note = "Annual Meeting of ISMRM 2017 ; Conference date: 22-04-2017 Through 27-04-2017",

url = "https://www.ismrm.org/2017-annual-meeting-exhibition/",

}

TY - CONF

T1 - Model-based joint reconstruction for multi b-value diffusion-weighted imaging

AU - Xu, Zhongbiao

AU - Guo, Li

AU - Fang, Wenxing

AU - Zhao, Chenguang

AU - Mei, Yingjie

AU - Chen, Zhifeng

AU - Chen, Wufan

AU - Wu, Ed X.

AU - Huang, Feng

AU - Feng, Yanqiu

N1 - Conference code: 25th

PY - 2017

Y1 - 2017

N2 - In current multi b-value DWI, each b-value image is usually reconstructed independently by using parallel MRI techniques. In this work, wepropose a model-based joint reconstruction method for the reconstruction of under-sampled multi b-value DWI data. The proposed method candirectly estimate quantitative parameters form k-space data, and exploit inter-image constraint to improve the quality of reconstructed image.

AB - In current multi b-value DWI, each b-value image is usually reconstructed independently by using parallel MRI techniques. In this work, wepropose a model-based joint reconstruction method for the reconstruction of under-sampled multi b-value DWI data. The proposed method candirectly estimate quantitative parameters form k-space data, and exploit inter-image constraint to improve the quality of reconstructed image.

M3 - Abstract

T2 - Annual Meeting of ISMRM 2017

Y2 - 22 April 2017 through 27 April 2017

ER -