A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain
Abstract Recently, imaging investigation of brain development has increasingly captured the attention of researchers and clinicians in an attempt to understand the link between the brain and behavioral changes. Although high-field MR imaging of infants is feasible, the necessary customizations have...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04450-w |
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| author | Zhexian Sun Jian Huang Xiaohui Ma Jiawei Liang Chensheng Sun Lanyin Hu Hongjian He Gang Yu |
| author_facet | Zhexian Sun Jian Huang Xiaohui Ma Jiawei Liang Chensheng Sun Lanyin Hu Hongjian He Gang Yu |
| author_sort | Zhexian Sun |
| collection | DOAJ |
| description | Abstract Recently, imaging investigation of brain development has increasingly captured the attention of researchers and clinicians in an attempt to understand the link between the brain and behavioral changes. Although high-field MR imaging of infants is feasible, the necessary customizations have limited its accessibility, affordability, and reproducibility. Low-field MR, as an emerging solution for scrutinizing developing brain, has exhibited its unique advantages in safety, portability, and cost-effectiveness. The presented low-field infant structural MR data aims to manifest the feasibility of using low-field MR image to exam brain structural changes during early life in infants. The dataset comprises 100 T2 weighed MR images from infants with in-plane resolution of ~0.85 mm and ~6 mm slice thickness. To demonstrate the potential utility, we conducted atlas-based whole brain segmentations and volumetric quantifications to analyze brain development features in first 10 week in postnatal life. This dataset addresses the scarcity of a large, extended-span infant brain dataset that restricts the further tracking of infant brain development trajectories and the development of routine low-field MR imaging pipelines. |
| format | Article |
| id | doaj-art-a4ab7c306b8f420d98ee088d5195c87a |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-a4ab7c306b8f420d98ee088d5195c87a2025-01-26T12:14:42ZengNature PortfolioScientific Data2052-44632025-01-011211810.1038/s41597-025-04450-wA Low-Field MRI Dataset For Spatiotemporal Analysis of Developing BrainZhexian Sun0Jian Huang1Xiaohui Ma2Jiawei Liang3Chensheng Sun4Lanyin Hu5Hongjian He6Gang Yu7National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of MedicineNational Clinical Research Center for Child Health, National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of MedicineNational Clinical Research Center for Child Health, National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of MedicineNational Clinical Research Center for Child Health, National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of MedicineNational Clinical Research Center for Child Health, National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of MedicineSchool of Physics, Zhejiang UniversitySchool of Physics, Zhejiang UniversityNational Clinical Research Center for Child Health, National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of MedicineAbstract Recently, imaging investigation of brain development has increasingly captured the attention of researchers and clinicians in an attempt to understand the link between the brain and behavioral changes. Although high-field MR imaging of infants is feasible, the necessary customizations have limited its accessibility, affordability, and reproducibility. Low-field MR, as an emerging solution for scrutinizing developing brain, has exhibited its unique advantages in safety, portability, and cost-effectiveness. The presented low-field infant structural MR data aims to manifest the feasibility of using low-field MR image to exam brain structural changes during early life in infants. The dataset comprises 100 T2 weighed MR images from infants with in-plane resolution of ~0.85 mm and ~6 mm slice thickness. To demonstrate the potential utility, we conducted atlas-based whole brain segmentations and volumetric quantifications to analyze brain development features in first 10 week in postnatal life. This dataset addresses the scarcity of a large, extended-span infant brain dataset that restricts the further tracking of infant brain development trajectories and the development of routine low-field MR imaging pipelines.https://doi.org/10.1038/s41597-025-04450-w |
| spellingShingle | Zhexian Sun Jian Huang Xiaohui Ma Jiawei Liang Chensheng Sun Lanyin Hu Hongjian He Gang Yu A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain Scientific Data |
| title | A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain |
| title_full | A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain |
| title_fullStr | A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain |
| title_full_unstemmed | A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain |
| title_short | A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain |
| title_sort | low field mri dataset for spatiotemporal analysis of developing brain |
| url | https://doi.org/10.1038/s41597-025-04450-w |
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