NEC-NET: segmentation and feature extraction network for the neurocranium in early childhood

Di Fan; Niharika Gajawelli; Athelia Paulli; Eryn Perry; Jeff Tanedo; Sean Deoni; Yalin Wang; Marius George Linguraru; Natasha Lepore

doi:10.1117/12.2670281

6 March 2023 NEC-NET: segmentation and feature extraction network for the neurocranium in early childhood

Di Fan, Niharika Gajawelli, Athelia Paulli, Eryn Perry, Jeff Tanedo, Sean Deoni, Yalin Wang, Marius George Linguraru, Natasha Lepore

Author Affiliations +

Proceedings Volume 12567, 18th International Symposium on Medical Information Processing and Analysis; 125671K (2023) https://doi.org/10.1117/12.2670281
Event: 18th International Symposium on Medical Information Processing and Analysis, 2022, Valparaíso, Chile

Abstract

In early life, the neurocranium undergoes rapid changes to accommodate the expanding brain. Neurocranial maturation can be disrupted by developmental abnormalities and environmental factors such as sleep position. To establish a baseline for the early detection of anomalies, it is important to understand how this structure typically grows in healthy children. Here, we designed a deep neural network pipeline NEC-NET, including segmentation and classification, to analyze the normative development of the neurocranium in T1 MR images from healthy children aged 12 to 60 months old. The pipeline optimizes the segmentation of the neurocranium and shows the preliminary results of age-based regional differences among infants.

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Di Fan, Niharika Gajawelli, Athelia Paulli, Eryn Perry, Jeff Tanedo, Sean Deoni, Yalin Wang, Marius George Linguraru, and Natasha Lepore "NEC-NET: segmentation and feature extraction network for the neurocranium in early childhood", Proc. SPIE 12567, 18th International Symposium on Medical Information Processing and Analysis, 125671K (6 March 2023); https://doi.org/10.1117/12.2670281

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