MO‐F‐CAMPUS‐J‐03: Sorting 2D Dynamic MR Images Using Internal Respiratory Signal for 4D MRI

TL;DRAbstract

Purpose: To develop a novel algorithm to extract internal respiratory signal (IRS) for sorting dynamic magnetic resonance (MR) images in order to achieve four‐dimensional (4D) MR imaging. Methods: Dynamic MR images were obtained with the balanced steady state free precession by acquiring each two‐dimensional sagittal slice repeatedly for more than one breathing cycle. To generate a robust IRS, we used 5 different representative internal respiratory surrogates in both the image space (body area) and the Fourier space (the first two low‐frequency phase components in the anterior‐posterior direction, and the first two low‐frequency phase components in the superior‐inferior direction). A clustering algorithm was then used to search for a group of similar individual internal signals, which was then used to formulate the final IRS. A phantom study and a volunteer study were performed to demonstrate the effectiveness of this algorithm. The IRS was compared to the signal from the respiratory b

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