公开(公告)号：US20210106301A1

公开(公告)日：2021-04-15

申请号：US15733498

申请日：2019-03-27

Applicant: Siemens Medical Solutions USA, Inc.

Inventor： Paul Schleyer ,  Inki Hong ,  Judson P. Jones

IPC: A61B6/00 ,  A61B6/03

Abstract: Embodiments provide a computer-implemented method of deriving a periodic motion signal from imaging data for continuous bed motion acquisition, including: acquiring a time series of three dimensional image volumes; estimating a first motion signal through a measurement of distribution of each three dimensional image volume; dividing the time-series of three dimensional image volumes into a plurality of axial sections overlapping each other by a predetermined amount; performing a spectral analysis on each axial section to locate a plurality of three dimensional image volumes which are subject to a periodic motion; performing a phase optimization on each axial section to obtain a three dimensional mask; estimating a second motion signal through the three dimensional mask and the time-series of three dimensional image volumes; and estimating a final motion signal based on the first motion signal and the second motion signal.

公开(公告)号：US11622742B2

公开(公告)日：2023-04-11

申请号：US15733498

申请日：2019-03-27

Applicant: Siemens Medical Solutions USA, Inc.

Inventor： Paul Schleyer ,  Inki Hong ,  Judson P. Jones

IPC: A61B6/03 ,  A61B6/00 ,  G06T7/20

Abstract: Embodiments provide a computer-implemented method of deriving a periodic motion signal from imaging data for continuous bed motion acquisition, including: acquiring a time series of three dimensional image volumes; estimating a first motion signal through a measurement of distribution of each three dimensional image volume; dividing the time-series of three dimensional image volumes into a plurality of axial sections overlapping each other by a predetermined amount; performing a spectral analysis on each axial section to locate a plurality of three dimensional image volumes which are subject to a periodic motion; performing a phase optimization on each axial section to obtain a three dimensional mask; estimating a second motion signal through the three dimensional mask and the time-series of three dimensional image volumes; and estimating a final motion signal based on the first motion signal and the second motion signal.