Abstract: A method for generating a perfusion weighted image using arterial spin labeling (ASL) with segmented acquisitions includes dividing an anatomical area of interest into a plurality of slices and performing a multi-band (MB) echo planar imaging (EPI) acquisition process using a magnetic resonance imaging (MRI) system to acquire a control image dataset representative of the plurality of slices using a central-to-peripheral or peripheral-to-central slice acquisition order. An ASL preparation process is performed using the MRI system to magnetically label protons in arterial blood water in an area upstream from the anatomical area of interest. Following a post-labeling delay time period, the MB EPI acquisition process is performed to a labeled image dataset corresponding to the slices using the central-to-peripheral or peripheral-to-central slice acquisition order. A perfusion weighted image of the anatomical area is generated by subtracting the labeled image dataset from the control image dataset.

Abstract: A method for generating a perfusion weighted image using arterial spin labeling (ASL) with segmented acquisitions includes dividing an anatomical area of interest into a plurality of slices and performing a multi-band (MB) echo planar imaging (EPI) acquisition process using a magnetic resonance imaging (MRI) system to acquire a control image dataset representative of the plurality of slices using a central-to-peripheral or peripheral-to-central slice acquisition order. An ASL preparation process is performed using the MRI system to magnetically label protons in arterial blood water in an area upstream from the anatomical area of interest. Following a post-labeling delay time period, the MB EPI acquisition process is performed to a labeled image dataset corresponding to the slices using the central-to-peripheral or peripheral-to-central slice acquisition order. A perfusion weighted image of the anatomical area is generated by subtracting the labeled image dataset from the control image dataset.

Abstract: A method for iteratively calibrating a reconstruction kernel for use in accelerated magnetic resonance imaging (MRI) is provided. An MRI system is used to acquire k-space data from multiple slice locations following the application of a multiband radio frequency (RF) excitation pulse. An initial reconstruction kernel is generated from the acquired k-space data, and this initial reconstruction kernel is used to produce an initial image for each of the multiple slice locations by applying the initial reconstruction kernel to the acquired k-space data. The average phase of each slice location is then calculated from these images, and used to shift the phase values of the subsequently acquired k-space data. From the phase-shifted k-space data, an updated reconstruction kernel is then generated. This process is repeated iteratively until a stopping criterion is satisfied.

Abstract: A method for iteratively calibrating a reconstruction kernel for use in accelerated magnetic resonance imaging (MRI) is provided. An MRI system is used to acquire k-space data from multiple slice locations following the application of a multiband radio frequency (RF) excitation pulse. An initial reconstruction kernel is generated from the acquired k-space data, and this initial reconstruction kernel is used to produce an initial image for each of the multiple slice locations by applying the initial reconstruction kernel to the acquired k-space data. The average phase of each slice location is then calculated from these images, and used to shift the phase values of the subsequently acquired k-space data. From the phase-shifted k-space data, an updated reconstruction kernel is then generated. This process is repeated iteratively until a stopping criterion is satisfied.