Denoising diffusion-weighted MR magnitude image sequences using low rank and edge constraints

Fan Lam, S. Derin Babacan, Justin P. Haldar, Norbert Schuff, Zhi Pei Liang

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

Abstract

This paper addresses the denoising problem associated with diffusion MR imaging. Building on previous approaches to this problem, this paper presents a new method for joint denoising of a sequence of diffusion-weighted (DW) magnitude images. The proposed method uses a maximum a posteriori (MAP) estimation formulation to incorporate a Rician likelihood (for modeling the noisy magnitude data), a low rank model (for the DW image sequences) and a spatial prior (for imposing joint edge constraints). An efficient algorithm to solve the associated optimization problem is also described. The proposed method has been evaluated using both simulated and experimental diffusion tensor imaging (DTI) data, which yields very encouraging results both qualitatively and quantitatively.

Original languageEnglish (US)
Title of host publication2012 9th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2012 - Proceedings
Pages1401-1404
Number of pages4
DOIs
StatePublished - Aug 15 2012
Event2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Barcelona, Spain
Duration: May 2 2012May 5 2012

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012
CountrySpain
CityBarcelona
Period5/2/125/5/12

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Keywords

  • diffusion-tensor imaging
  • Diffusion-weighted imaging
  • edge constraints
  • low rank
  • Rician noise

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Lam, F., Babacan, S. D., Haldar, J. P., Schuff, N., & Liang, Z. P. (2012). Denoising diffusion-weighted MR magnitude image sequences using low rank and edge constraints. In 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings (pp. 1401-1404). [6235830] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2012.6235830