# MRecover: A Conditional Generative Model for Recovering Motion-Corrupted MR images Using AI Generated Contrast

Source: [MRecover: A Conditional Generative Model for Recovering Motion-Corrupted MR images Using AI Generated Contrast](<https://www.sota2.com/research/paper/6a0fe2ebf984739ed6739c24>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-05-23T05:00:04.712Z

Authors: Jinghang Li, Tales Santini, Courtney Clark, Bruno de Almeida, Cong Chu, Salem Alkhateeb, Andrea Sajewski, Jacob Berardinelli, Hecheng Jin, Tobias Campos, Jeremy J. Berardo, Joseph Mettenburg, Ariel Gildengers, Howard J. Aizenstein, Minjie Wu, Tamer S. Ibrahim

Published: 2026-05-20T19:23:03.000Z

## Abstract

Hippocampal subfield segmentation requires high-resolution T2w turbo spin echo (TSE) MRI, yet this sequence is susceptible to motion artifacts, leading to substantial data loss. We developed a conditional generative model (MRecover) that synthesizes routinely acquired T1w images to create TSE images with autoregressive slice conditioning for volumetric consistency. Trained on 7T MRI data (n=577), the model achieved high in-domain fidelity (n=148, SSIM=0.84, FSIM=0.94) and generalized well to out-of-domain 3T data: subfield volumes from synthesized and the as-acquired images closely matched: (n=416, r=0.87-0.97) and yielded 31.8% more analyzable subjects in the motion-affected ADNI3 dataset after quality control (593 vs 450). The synthesized images also achieved larger effect sizes due to increasing the sample size for diagnostic group differences in hippocampal subfield atrophy (whole hippocampus $\\epsilon^2$= 0.121-0.100 vs. 0.086-0.062, left-right hemispheres). Project page: https://jinghangli98.github.io/MRecover/

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Statistical Comparison of Hippocampal Subfield Volumes on ADNI3 cohort](<https://www.sota2.com/research/sota/statistical-comparison-of-hippocampal-subfield-volumes-on-adni3-cohort.md>): Diagnostic group separation analysis of hippocampal subfield volumes; ADNI3 cohort; Kruskal-Wallis H Statistic: 98.39.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2605.21669>)

[PDF](<https://arxiv.org/pdf/2605.21669.pdf>)