Magnetic particle imaging(MPI)is an emerging molecular imaging technique with high sensitivity and temporal-spatial resolution.Image reconstruction is an important research topic in MPI,which converts an induced volta...Magnetic particle imaging(MPI)is an emerging molecular imaging technique with high sensitivity and temporal-spatial resolution.Image reconstruction is an important research topic in MPI,which converts an induced voltage signal into the image of superparamagnetic iron oxide particles concentration distribution.MPI reconstruction primarily involves system matrix-and x-space-based methods.In this review,we provide a detailed overview of the research status and future research trends of these two methods.In addition,we review the application of deep learning methods in MPI reconstruction and the current open sources of MPI.Finally,research opinions on MPI reconstruction are presented.We hope this review promotes the use of MPI in clinical applications.展开更多
基金This work was supported in part by the National Key Research and Development Program of China,Nos.2017YFA0700401 and 2017YFA0205200the National Natural Science Foundation of China,Nos.62027901,81827808,81527805,and 81671851+2 种基金the CAS Youth Innovation Promotion Association,No.2018167the CAS Key Technology Talent Programand the Project of High-Level Talents Team Introduction in Zhuhai City,No.Zhuhai HLHPTP201703。
文摘Magnetic particle imaging(MPI)is an emerging molecular imaging technique with high sensitivity and temporal-spatial resolution.Image reconstruction is an important research topic in MPI,which converts an induced voltage signal into the image of superparamagnetic iron oxide particles concentration distribution.MPI reconstruction primarily involves system matrix-and x-space-based methods.In this review,we provide a detailed overview of the research status and future research trends of these two methods.In addition,we review the application of deep learning methods in MPI reconstruction and the current open sources of MPI.Finally,research opinions on MPI reconstruction are presented.We hope this review promotes the use of MPI in clinical applications.
