Automatic planning of T2-weighted fetal scans at 0.55T using fetal brain landmark detection

Motivation: Fetal MRI plays an important role in clinical and research settings. The variability of the fetal position and extensive fetal motion, however, create challenges limiting the use of fetal MRI mainly to specialist centres. Goal(s): Real-time fully automatic planning of true radiological fetal brain planes for anatomical TSE scans. Approach: Deep-learning based detection of key landmarks in the fetal brain on a whole-uterus EPI scan enables the subsequent automatic calculation of the radiological plane for the TSE scan. Results: Prospective results on three fetal MRI scans on a clinical low-field 0.55T MRI scanner illustrate the ability of the framework to perform diagnostic planning. Impact: Fully automated planning of radiological planes for low-field fetal MRI demonstrates time efficiency and carries the potential to significantly widen accessibility to fetal MRI beyond specialist centres.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/0279
Primary Topic
Fetal and Pediatric Neurological Disorders
Type
article
Field-Weighted Citation Impact
0.00
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article

Automatic planning of T2-weighted fetal scans at 0.55T using fetal brain landmark detection

Kuberan Pushparajah, Megan Hall, Sarah McElroy, Jana Hutter et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Fetal and Pediatric Neurological Disorders
article

Automatic planning of T2-weighted fetal scans at 0.55T using fetal brain landmark detection

Kuberan Pushparajah, Megan Hall, Sarah McElroy, Jana Hutter, Jordina Aviles Verdera, Valéry Ozenne, Mary Rutherford, Joseph V. Hajnal, Kathleen Colford, Lisa Story, Sara Neves Silva, Michela Cleri
article en

Abstract

Motivation: Fetal MRI plays an important role in clinical and research settings. The variability of the fetal position and extensive fetal motion, however, create challenges limiting the use of fetal MRI mainly to specialist centres. Goal(s): Real-time fully automatic planning of true radiological fetal brain planes for anatomical TSE scans. Approach: Deep-learning based detection of key landmarks in the fetal brain on a whole-uterus EPI scan enables the subsequent automatic calculation of the radiological plane for the TSE scan. Results: Prospective results on three fetal MRI scans on a clinical low-field 0.55T MRI scanner illustrate the ability of the framework to perform diagnostic planning. Impact: Fully automated planning of radiological planes for low-field fetal MRI demonstrates time efficiency and carries the potential to significantly widen accessibility to fetal MRI beyond specialist centres.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 67%
Fetal and Pediatric Neurological Disorders
DOISourceOpenAlex
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