ArticleDiagnostics (Basel, Switzerland)2020
Deep Learning-Based Segmentation to Establish East Asian Normative Volumes Using Multisite Structural MRI.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Exploring approaches to tackle cross-domain challenges in brain medical image segmentation: a systematic review.Frontiers in neuroscience · 2024Pooled it
- MRI-guided personalized tDCS planning for target engagement of the swallowing motor cortex after stroke: a finite-element modeling study.Frontiers in neurology · 2026Article
- Deep Learning-based Hierarchical Brain Segmentation with Preliminary Analysis of the Repeatability and Reproducibility.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Reliability of brain volume measures of accelerated 3D T1-weighted images with deep learning-based reconstruction.Neuroradiology · 2025Article
- Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study.Journal of medical Internet research · 2024Article
- Feasibility and usefulness of cognitive monitoring using a new home-based cognitive test in mild cognitive impairment: a prospective single arm study.BMC geriatrics · 2024Article
- Development of Efficient Brain Age Estimation Method Based on Regional Brain Volume From Structural Magnetic Resonance Imaging.Psychiatry investigation · 2024Article
- Modulation of associations between education years and cortical volume in Alzheimer's disease vulnerable brain regions by Aβ deposition andFrontiers in aging neuroscience · 2023Article
- Development and validation of deep learning-based automatic brain segmentation for East Asians: A comparison with Freesurfer.Frontiers in neuroscience · 2023Article
- [Brain MRI-Based Artificial Intelligence Software in Patients with Neurodegenerative Diseases: Current Status].Taehan Yongsang Uihakhoe chi · 2022Review
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
Normative brain magnetic resonance imaging (MRI) is essential to interpret the state of an individual's brain health. However, a normative study is often expensive for small research groups. Although several attempts have been made to establish brain MRI norms, the focus has been limited to certain age ranges. This study aimed to establish East Asian normative brain data using multi-site MRI and determine the robustness of these data for clinical research. Normative MRI was gathered covering a wide range of cognitively normal East Asian populations (age: 18-96 years) from two open sources and three research sites. Eight sub-regional volumes were extracted in the left and right hemispheres using an in-house deep learning-based tool. Repeated measure consistency and multicenter reliability were determined using intraclass correlation coefficients and compared to a widely used tool, FreeSurfer. Our results showed highly consistent outcomes with high reliability across sites. Our method outperformed FreeSurfer in repeated measure consistency for most structures and multicenter reliability for all structures. The normative MRI we constructed was able to identify sub-regional differences in mild cognitive impairments and dementia after covariate adjustments. Our investigation suggests it is possible to provide a sound normative reference for neurodegenerative or aging research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.