Rapid head‐pose detection for automated slice prescription of fetal‐brain MRI

Synopsis

This project includes an automated fetal-head pose detection from a full-uterus
scout scan acquired as a stack of echo planar imaging (EPI) slices.
Specifically, the algorithm derives the left-right, posterior-anterior and
inferior-superior axes of the arbitrarily oriented fetal brain, which enables
automatic prescription of a subsequent scan in standard anatomical planes. The
brain and eyes are identified by detecting maximally stable extremal regions
(MSER) on each slice of the scout and combining them in 3D space. The location
and shape of these landmarks provide sufficient information to fully determine
the head pose.

Motivation

In fetal-brain magnetic resonance imaging (MRI), head-pose changes between
prescription and acquisition present a challenge to obtaining the standard
sagittal, coronal and axial views needed for clinical assessment. Unfortunately,
subject motion limits acquisitions to thick slices that preclude retroactive
resampling to provide standard planes. Throughout the session, technologists
therefore repeat incrementally rotated stacks of slices, deducing the head pose
from the previous stack until they obtain appropriately oriented images. The
algorithm seeks to address this inefficient workflow.

Requirements

MATLAB version 9.1/R2016b or later is required. If needed, the pre-compiled MEX
function for MSER detection can be rebuilt by running
mex -output mser mser/mser.cpp mexmser.cpp in MATLAB.

Where to start

For a demo showcasing the different stages of the algorithm, run demo. The
printstats script compares the landmarks derived by the algorithm to manually
localized eye and brain centers.

Included data

The included test data comprise 41 EPI stacks from fetuses at 26-37 weeks’
gestation. Except for ep2d_34.nii.gz and
ep2d_41.nii.gz, the pipeline should accurately detect
the head pose.

IO scripts

The IO scripts in the freesurfer directory are subject to the
FreeSurfer Software License Agreement. For more
information about FreeSurfer see https://surfer.nmr.mgh.harvard.edu.

Further reading

A detailed description of the pipeline is freely available online. If you find
the code or data useful, please consider citing:

Rapid head-pose detection for automated slice prescription of fetal-brain MRI.
Hoffmann M, Abaci Turk E, Gagoski B, Morgan L, Wighton P, Tisdall MD, Reuter M, Adalsteinsson E, Grant PE, Wald LL, van der Kouwe AJW.
International Journal of Imaging Systems and Technology (IMA), 31 (3), pp 1136-1154, 2021.

@article{hoffmann2021rapid,
    title={Rapid head-pose detection for automated slice prescription of fetal-brain MRI},
    author={Hoffmann, Malte and Abaci Turk, Esra and Gagoski, Borjan and Morgan, Leah and Wighton, Paul and Tisdall, M Dylan and Reuter, Martin and Adalsteinsson, Elfar and Grant, P Ellen and Wald, Lawrence L and van der Kouwe, André JW},
    journal={International Journal of Imaging Systems and Technology},
    volume={31},
    number={3},
    pages={1136-1154},
    year={2021},
    publisher={Wiley Online Library}
}