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.

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.

Abstract: Methods and computer-readable mediums are provided. In one embodiment, the method acquires patient data. The peak value in the patient data is determined. The patient data is divided into two data segments (i.e., one data segment representing the data before the peak value occurs and a second data segment representing the patient data after the peak occurs). The slopes of the first and second data segments are calculated. Thereafter the slopes are used to determine an appropriate adaptive framing protocol. A number of frames and duration of each frame in the adaptive framing protocol can be calculated or the adaptive framing protocol can be selected from a plurality of framing protocols. Embodiments of the invention also include computer-readable mediums that contain features similar to the features in the above described method.

Abstract: Methods and computer-readable mediums are provided. In one embodiment, the method acquires patient data. The peak value in the patient data is determined. The patient data is divided into two data segments (i.e., one data segment representing the data before the peak value occurs and a second data segment representing the patient data after the peak occurs). The slopes of the first and second data segments are calculated. Thereafter the slopes are used to determine an appropriate adaptive framing protocol. A number of frames and duration of each frame in the adaptive framing protocol can be calculated or the adaptive framing protocol can be selected from a plurality of framing protocols. Embodiments of the invention also include computer-readable mediums that contain features similar to the features in the above described method.