DocumentCode :
3504314
Title :
Model-based compressive diffusion tensor imaging
Author :
Pu, Lingling ; Trouard, Theodore P. ; Ryan, Lee ; Huang, Chuan ; Altbach, Maria I. ; Bilgin, Ali
Author_Institution :
Dept. of Psychol., Univ. of Arizona, Tucson, AZ, USA
fYear :
2011
fDate :
March 30 2011-April 2 2011
Firstpage :
254
Lastpage :
257
Abstract :
Diffusion tensor imaging (DTI) is a Magnetic Resonance Imaging (MRI) technique that can reveal in vivo tissue microstructure by measuring diffusion of water in tissue. DTI has become an important tool in many clinical applications, such as assessment of white matter maturation, locating white matter lesions, and providing anatomical connectivity information. However, DTI usually requires long examination times due to the repetitive nature of the acquisition and is very sensitive to motion. These drawbacks have become the largest obstacles to full utilization of DTI. In this work, we propose to overcome these obstacles by using a model-based compressive imaging approach. Our approach consist of models to efficiently represent diffusion-encoded images and the corresponding recovery schemes based on compressive sensing (CS) principles. Our results indicate that the proposed model-based approach can allow reliable recovery of DTI signal from undersampled measurements and outperforms conventional CS recovery.
Keywords :
biomedical MRI; data acquisition; image sampling; medical image processing; tumours; DTI signal; MRI; anatomical connectivity information; diffusion-encoded images; in vivo tissue microstructure; magnetic resonance imaging; model-based compressive diffusion tensor imaging; model-based compressive imaging approach; recovery schemes; undersampled measurements; water diffusion; white matter lesions; white matter maturation; Compressed sensing; Diffusion tensor imaging; Image reconstruction; Joints; Principal component analysis; Transforms; Compressive sensing; DTI;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
ISSN :
1945-7928
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2011.5872400
Filename :
5872400
Link To Document :
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