# Ghost Reduction in Echo-Planar Imaging by Joint Reconstruction of Images and Line-to-Line Delays and Phase Errors

## TL;DR

EPI-TrACR is an iterative method that automatically corrects line-to-line delays and phase errors in echo-planar imaging, significantly reducing ghosting artifacts in various imaging scenarios without requiring calibration data.

## Contribution

The paper introduces EPI-TrACR, a novel joint reconstruction technique that corrects trajectory delays and phase errors in EPI using data redundancy, improving image quality.

## Key findings

- Reduced ghosting by 27% on average compared to calibrated methods.
- Effective correction across multishot, accelerated, and dynamic EPI.
- Maintains low ghosting in dynamic time series.

## Abstract

PURPOSE: To correct line-to-line delays and phase errors in echo-planar imaging (EPI). THEORY AND METHODS: EPI- trajectory auto-corrected image reconstruction (EPI-TrACR) is an iterative maximum-likelihood technique that exploits data redundancy provided by multiple receive coils between nearby lines of k-space to determine and correct line-to-line trajectory delays and phase errors that cause ghosting artifacts. EPI-TrACR was applied to in vivo data acquired at 7 Tesla across acceleration and multishot factors, and in a dynamic time series. The method was efficiently implemented using a segmented FFT and compared to a conventional calibrated reconstruction. RESULTS: Compared to conventional calibrated reconstructions, EPI-TrACR reduced ghosting up to moderate acceleration factors and across multishot factors. It also maintained low ghosting in a dynamic time series. Averaged over all cases, EPI-TrACR reduced root-mean-square ghosted signal outside the brain by 27% compared to calibrated reconstruction. CONCLUSION: EPI-TrACR is effective in automatically correcting line-to-line delays and phase errors in multishot, accelerated, and dynamic EPI. While the method benefits from additional calibration data, it is not a requirement.