System and method for one-shot automatic TI prediction for cardiac MRI

A system for determining an optimal inversion time (TI), comprising:

• a memory encoding processor-executable routines;
• and
• a processing system comprising one or more processors and configured to access the memory and to execute the processor-executable routines, wherein the processor-executable routines, when executed by the processing system, cause the processing system to:
• obtain a series of magnetic resonance (MR) scout temporal frames of a subject from MR scout imaging data acquired with an MR scanner utilizing a TI-scout sequence;
• obtain a TI-scout maximum intensity projection (MIP) image from the MR scout imaging data;
• utilize a first trained neural network to localize a cardiac region in the TI-scout MIP image to generate a region of interest (ROI) segmentation mask for the cardiac region;
• utilize the ROI segmentation mask on the TI-scout MIP image and the series of MR scout temporal frames to generate a ROI cropped TI-scout MIP image and ROI cropped MR scout temporal frames, respectively;
• generate a distance score plot by computing a distance between each ROI cropped MR scout temporal frame and the ROI cropped TI-scout MIP image;
• automatically analyze the distance score plot to approximate a span of the MR scout temporal frames for optimal TI frame estimation, wherein the span of the MR scout temporal frames encompasses a transition region comprising phase changes in the cardiac region including blood pool nulling, remote myocardium nulling, and initial recovery;
• and
• utilize a second trained neural network to determine an optimal TI frame from the span of the MR scout temporal frames, wherein determination of the optimal TI frame occurs in a single pass.

A non-transitory computer-readable medium, the computer-readable medium comprising processor-executable code that when executed by a processing system comprising one or more processors, causes the processing system to:

• obtain a series of magnetic resonance (MR) scout temporal frames of a subject from MR scout imaging data acquired with an MR scanner utilizing a TI-scout sequence;
• obtain a TI-scout maximum intensity projection (MIP) image from the MR scout imaging data;
• utilize a first trained neural network to localize a cardiac region in the TI-scout MIP image to generate a region of interest (ROI) segmentation mask for the cardiac region;
• utilize the ROI segmentation mask on the TI-scout MIP image and the series of MR scout temporal frames to generate a ROI cropped TI-scout MIP image and ROI cropped MR scout temporal frames, respectively;
• generate a distance score plot by computing a distance between each ROI cropped MR scout temporal frame and the ROI cropped TI-scout MIP image;
• automatically analyze the distance score plot to approximate a span of the MR scout temporal frames for optimal TI frame estimation, wherein the span of the MR scout temporal frames encompasses a transition region comprising phase changes in the cardiac region including blood pool nulling, remote myocardium nulling, and initial recovery;
• and
• utilize a second trained neural network to determine an optimal TI frame from the span of the MR scout temporal frames, wherein determination of the optimal TI frame occurs in a single pass.