BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy (BONBID-HIE): I. MRI and Manual Lesion Annotation
Description
BOston Neonatal Brain Injury Dataset for Hypoxic Ischemic Encephalopathy (BONBID-HIE): Part I. MRI and Manual Lesion AnnotationHypoxic ischemic encephalopathy (HIE) is a brain injury that occurs in 1 ∼ 5/1000 term neonates. Accurate identification and segmentation of HIE-related lesions in neonatal brain magnetic resonance images (MRIs) is the first step toward predicting prognosis, identifying high-risk patients, and evaluating treatment effects. It will lead to a more accurate estimation of prognosis, a better understanding of neurological symptoms, and a timely prediction of response to therapy. We release the first public dataset containing neonatal brain diffusion MRI and expert annotation of lesions from 133 patients diagnosed with HIE. HIE-related lesions in brain MRI are often diffuse (i.e., multi-focal), and small (over half the patients in our data having lesions occupying <1% of brain volume). Segmentation for HIE MRI data is remarkably different from, and arguably more challenging than, other segmentation tasks such as brain tumors with focal and relatively large lesions. We hope that this dataset can help fuel the development of MRI lesion segmentation methods for HIE and small diffuse lesions in general.Contact: Rina Bao: [email protected] Yangming Ou: [email protected]: All data has been made publicly available under the CC BY license (https://creativecommons.org/licenses/by/4.0/legalcode).If you use this data, please cite our paper:@article{bao2023boston, title={BOston Neonatal Brain Injury Dataset for Hypoxic Ischemic Encephalopathy (BONBID-HIE): Part I. MRI and Manual Lesion Annotation}, author={Bao, Rina and Song, Ya’nan and Bates, Sara V and Weiss, Rebecca J and Foster, Anna N and Cobos, Camilo Jaimes and Sotardi, Susan and Zhang, Yue and Gollub, Randy L and Grant, P Ellen and others}, journal={bioRxiv}, year={2023}, publisher={Cold Spring Harbor Laboratory Preprints}}
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Publication Details
DOI
Publisher
Zenodo
Subfield
Radiology, Nuclear Medicine and Imaging
Field
Medicine
Domain
Health Sciences
Confidence Score
58%
Source
Scholar Data Model