Fast Spin Echo Imaging-Based Electric Property Tomography with K-Space Weighting via ${T}-{2}$ Relaxation (rEPT)

Jaewook Shin, Min Oh Kim, Sungmin Cho, Dong Hyun Kim

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Magnetic resonance electrical property tomography (MREPT) is a technique used to extract the electrical properties of tissues (conductivity in particular) using a magnetic resonance imaging system. In this paper, we propose an improved data acquisition scheme for the electrical property tomography technique by utilizing T2 modulation in fast spin echo (FSE) imaging. This technique was motivated by a numerical analysis of conductivity reconstruction in the frequency domain; results reveal the spatial frequency-dependent noise texture of conventional methods. A data-acquisition scheme using the FSE sequence was formulated to concentrate the signal within a specific frequency range where notable noise amplification is observed in the conventional method. Through numerical studies, the performance of the proposed acquisition was investigated. Furthermore, a compensation scheme was applied to reduce quantification errors due to tissue-specific T2 modulation, which is inherent in FSE imaging. The technique was applied to phantom and in vivo experiments. Results showed improved conductivity contrasts in both experiments, as compared with conventional MREPT methods.

Original languageEnglish
Article number7880627
Pages (from-to)1615-1625
Number of pages11
JournalIEEE Transactions on Medical Imaging
Issue number8
Publication statusPublished - 2017 Aug

Bibliographical note

Funding Information:
Manuscript received December 23, 2016; revised March 4, 2017; accepted March 13, 2017. Date of publication March 17, 2017; date of current version July 30, 2017. This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning under Grant NRF-2015R1A2A1A15052174 and NRF-2016R1A2B3016273. Asterisk indicates corresponding author.

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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