1

Workshop on MR Image Reconstruction

March 1-3, Shenzhen, China

2013.3.1 3.3

SIAT

SIAT

GE Healthcare (USA)

The Ohio State University

State University of New York - Buffalo

University of British Columbia

University of Illinois Urbana-Champaign

1. (Introduction)

(MRI) 20

MRI

2

,

EPI

C

3

2. Instructors

1989 Case Western Reserve University

University of Illinois Urbana-ChampaignUIUC

Franklin W. Woeltge Professor of Electrical and Computer Engineering

Beckman Beckman Integrative

Imaging Theme 2006 2012 IEEE-EMBS

IEEEAIMBE ISMRMFellow member NSF

IEEE

Principles of Magnetic Resonance Imaging: A Signal Processing Perspective

4

University of British Columbia1982

CUSPEA1988

UC-Irvine Dr. F. Reines

1992

UBC

EPI

SSFP

Sylvia Fedoruk

Kevin F. King, Global Applied Science

Laboratory 30

CT CT

Handbook of MRI Pulse Sequences

5

2003

NSFNIH

GE Healthcare

5

ISMRMMagnetic Resonance in Medicine

(Deputy Editor)

CAREER Award, NSF

2011 IEEESenior member

(2001 )

2000 7-92011 7-8

1998

4863 1

863 973 1

1 500 30

, EI SCI 1

6

5

2004 2000

MRI Devices Corp. Invivo Corp.

23

30 120

10

2006

7

20062006 7

2007 82007 11 2011 3

University of Wisconsin-Milwaukee

2011 3

Fast MR

Imaging

60

10 2

10

20112012 IEEE- EMBSStudent

Paper Competition

1999Case Western Reserve University

Siemens Medical Solutions

USA2010

8

100

3. (Syllabus)

Day 0 (March 1, Friday Evening)

Lecture 0a (optional): Essential mathematics for image reconstruction

Lecture 0b (optional): Basic principles of MRI

Day 1 (March 2, Saturday)

Lecture 1: Image reconstruction an overview and introduction

Lecture 2: Common image reconstruction techniques

Lecture 3: Use of phase information in image reconstruction

Lecture 4: Susceptibility weighted imaging

Lecture 5: Gridding and projection reconstruction

Lecture 6: Image reconstruction from highly undersampled data using

low-rank approximation

Lecture 7: Parallel imaging basic principles

Day 2 (March 3, Sunday)

Lecture 8: Parallel imaging advanced techniques

Lecture 9: Singular Function Analysis and its use in MRI

Lecture 10: Accelerating MRI by skipped phase encoding and edge

deghosting (SPEED)

Lecture 11: Parallel imaging for artifact reduction

Lecture 12: Compressed sensing a premier

Lecture 13: Image quality assessment in MR image reconstruction

9

4. (Remarks)

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250/

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159 8669 4141

E-mail: wanglan@sinorad.com

11001085400059610940

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