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

• URL: http://arxiv.org/abs/2110.04140v1
• Date: Fri, 8 Oct 2021 13:59:05 GMT
• Title: Rapid head-pose detection for automated slice prescription of fetal-brain MRI
• Authors: Malte Hoffmann, Esra Abaci Turk, Borjan Gagoski, Leah Morgan, Paul Wighton, M. Dylan Tisdall, Martin Reuter, Elfar Adalsteinsson, P. Ellen Grant, Lawrence L. Wald, Andr\'e J. W. van der Kouwe
• Abstract summary: In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views. We propose a robust head-pose detection algorithm using full-uterus scout scans (EPI) which take 5 seconds to acquire. The success rate of the method exceeds 94% in the third trimester, outperforming a trained technologist by up to 20%.
• Score: 2.0526610003396657
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical assessment. As motion limits acquisitions to thick slices that preclude retrospective resampling, technologists repeat ~55-second stack-of-slices scans (HASTE) with incrementally reoriented field of view numerous times, deducing the head pose from previous stacks. To address this inefficient workflow, we propose a robust head-pose detection algorithm using full-uterus scout scans (EPI) which take ~5 seconds to acquire. Our ~2-second procedure automatically locates the fetal brain and eyes, which we derive from maximally stable extremal regions (MSERs). The success rate of the method exceeds 94% in the third trimester, outperforming a trained technologist by up to 20%. The pipeline may be used to automatically orient the anatomical sequence, removing the need to estimate the head pose from 2D views and reducing delays during which motion can occur.

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