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07-04-2022 | Original Paper

Volumetric Analysis of Amygdala and Hippocampal Subfields for Infants with Autism

Auteurs: Guannan Li, Meng-Hsiang Chen, Gang Li, Di Wu, Chunfeng Lian, Quansen Sun, R. Jarrett Rushmore, Li Wang

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 6/2023

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Abstract

Previous studies have demonstrated abnormal brain overgrowth in children with autism spectrum disorder (ASD), but the development of specific brain regions, such as the amygdala and hippocampal subfields in infants, is incompletely documented. To address this issue, we performed the first MRI study of amygdala and hippocampal subfields in infants from 6 to 24 months of age using a longitudinal dataset. A novel deep learning approach, Dilated-Dense U-Net, was proposed to address the challenge of low tissue contrast and small structural size of these subfields. We performed a volume-based analysis on the segmentation results. Our results show that infants who were later diagnosed with ASD had larger left and right volumes of amygdala and hippocampal subfields than typically developing controls.
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Metagegevens
Titel
Volumetric Analysis of Amygdala and Hippocampal Subfields for Infants with Autism
Auteurs
Guannan Li
Meng-Hsiang Chen
Gang Li
Di Wu
Chunfeng Lian
Quansen Sun
R. Jarrett Rushmore
Li Wang
Publicatiedatum
07-04-2022
Uitgeverij
Springer US
Gepubliceerd in
Journal of Autism and Developmental Disorders / Uitgave 6/2023
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI
https://doi.org/10.1007/s10803-022-05535-w

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