Inverse Problem Analysis in Magnetic Nanoparticle Tomography using Minimum Variance Spatial Filter

研究成果: Contribution to journalArticle査読

抄録

In magnetic nanoparticle tomography (MNT), the reduction of artefacts and the calculation time can be used to estimate the position of magnetic nanoparticles (MNPs). Non-negative least squares (NNLS) inverse problem analysis has been used in MNT systems for this task. However, owing to the presence of measurement noise and the high sensitivity of the NNLS method, it often estimates certain MNPs inaccurately, i.e., it generates artefacts. In addition, its calculation time is very high. In this study, we applied the minimum variance spatial filter (MV-SF) inverse problem analysis to MNT and estimated the position of an MNP sample containing 100 μ g of Fe. Using the MV-SF method, MNP samples placed at a depth of 25–40 mm were observed to have no artefacts. Moreover, the MV-SF method was also observed to be faster than the NNLS method by a factor of approximately 20. These results verify the feasibility of the MV-SF method for estimating the MNP positions in an MNT system.

本文言語英語
ジャーナルIEEE Transactions on Magnetics
DOI
出版ステータス受理済み/印刷中 - 2021

All Science Journal Classification (ASJC) codes

  • 電子材料、光学材料、および磁性材料
  • 電子工学および電気工学

フィンガープリント

「Inverse Problem Analysis in Magnetic Nanoparticle Tomography using Minimum Variance Spatial Filter」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル