Data Sheet 1_Evaluating reliability of automated quantitative brain morphometry from fetal

30 typically developing fetuses between 22 and 36 weeks gestational age were scanned to evaluate the within-session reliability of automated cortical morphometry pipelines. The study, authored by Seungyoon Jeong and last updated in June 2026, assessed metrics like cortical plate volume and surface area using two reconstruction methods, NeSVoR and SVRTK. Results showed high reliability for both methods, with mean absolute percent differences under 5%.

Use Cases

• Benchmarking automated fetal brain measurement pipelines based on the described within-session reliability design.
• Assessing the impact of MRI stack count and quality on measurement consistency based on the regression analysis.
• Comparing the performance of Neural Slice-to-Volume Reconstruction (NeSVoR) and Slice-to-Volume Reconstruction Toolkit (SVRTK) methods for cortical morphometry.

Strengths

• Dataset includes 30 fetal MRI subjects, providing a basis for reliability analysis.
• Results report specific reliability metrics, including mean APD < 3% and ICC > 0.99 for NeSVoR.
• Analysis considers multiple factors affecting reliability, such as gestational age, stack count, and image quality.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 1.1 MB size suggests the primary file is a document, and the underlying data tables may not be directly accessible.

Provenance

Source

figshare

Collection Method

MRI scans of 30 typically developing fetuses, processed through automated reconstruction and morphometry pipelines.

Freshness

Last updated 2026-06-01 05:23:08; freshness should be verified.