Fetal MRI by robust deep generative prior reconstruction and diffeomorphic registration: application to gestational age prediction

TL;DR

This paper introduces a robust deep generative prior for fetal MRI reconstruction that improves image quality and gestational age prediction accuracy by integrating volumetric reconstruction with diffeomorphic registration, outperforming existing methods.

Contribution

The study presents a novel deep generative prior integrated with diffeomorphic registration for fetal MRI reconstruction, enhancing image resolution and gestational age prediction accuracy.

Findings

Improved image resolution over state-of-the-art methods.

More accurate gestational age prediction, with a mean absolute error of 0.618 weeks.

Enhanced prediction accuracy by combining brain and organ information.

Abstract

Magnetic resonance imaging of whole fetal body and placenta is limited by different sources of motion affecting the womb. Usual scanning techniques employ single-shot multi-slice sequences where anatomical information in different slices may be subject to different deformations, contrast variations or artifacts. Volumetric reconstruction formulations have been proposed to correct for these factors, but they must accommodate a non-homogeneous and non-isotropic sampling, so regularization becomes necessary. Thus, in this paper we propose a deep generative prior for robust volumetric reconstructions integrated with a diffeomorphic volume to slice registration method. Experiments are performed to validate our contributions and compare with a state of the art method in a cohort of $72$ fetal datasets in the range of $20-36$ weeks gestational age. Results suggest improved image resolution and more accurate prediction of gestational age at scan when comparing to a state of the art reconstruction method. In addition, gestational age prediction results from our volumetric reconstructions compare favourably with existing brain-based approaches, with boosted accuracy when integrating information of organs other than the brain. Namely, a mean absolute error of $0.618$ weeks ($R^2=0.958$) is achieved when combining fetal brain and trunk information.