Regularized inversion of noisy, incomplete MR spectroscopic imaging data with anatomical prior

Justin P. Haldar, Mathews Jacob, Andreas Ebel, Xiaoping Zhu, Norbert Schuff, Diego Hernando, Bradley P. Sutton, Zhi Pei Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the image reconstruction problem in MR spectroscopic imaging experiments where noisy, limited Fourier data are often collected due to temporal constraints. A parametric method is proposed which is capable of incorporating exact and uncertain boundary information. Experimental results show that the technique can generate metabolic images with much higher spatial resolution than the conventional Fourier method and existing constrained reconstruction methods.

Original languageEnglish (US)
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages718-721
Number of pages4
StatePublished - Nov 17 2006
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: Apr 6 2006Apr 9 2006

Publication series

Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Volume2006

Other

Other2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period4/6/064/9/06

ASJC Scopus subject areas

  • Engineering(all)

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