A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations

The hippocampus plays a critical role in memory and is prone to neural degenerative diseases. Its complex structure and distinct subfields pose challenges for automatic segmentation in 3 T MRI because of its limited resolution and contrast. While 7 T MRI offers superior anatomical details and better gray-white matter contrast, aiding in clearer differentiation of hippocampal structures, its use is restricted by high costs. To bridge this gap, algorithms synthesizing 7T-like images from 3 T scans are being developed, requiring paired datasets for training. However, the scarcity of such high-quality paired datasets, particularly those with manual hippocampal subfield segmentations as ground truth, hinders progress. Herein, we introduce a dataset comprising paired 3 T and 7 T MRI scans from 20 healthy volunteers, with manual hippocampal subfield annotations on 7 T T2-weighted images. This dataset is designed to support the development and evaluation of both 3T-to-7T MR image synthesis models and automated hippocampal segmentation algorithms on 3 T images. We assessed the image quality using MRIQC. The dataset is freely accessible on the Figshare+.

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Publication Details

Journal
Scientific Data
Published
2025-02-13
DOI
https://doi.org/10.1038/s41597-025-04586-9
Citations
5
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
6.80

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article

A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations

Debin Zeng, Baoqiang Ma, Lei Chu, Tongtong Che et al.
5 citations
Scientific Data
Advanced MRI Techniques and Applications
6.80
article

A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations

Debin Zeng, Baoqiang Ma, Lei Chu, Tongtong Che, Xiaoxi Dong, Zihao Zhang, Shuyu Li, Yirong He
article en
5 citations

Abstract

The hippocampus plays a critical role in memory and is prone to neural degenerative diseases. Its complex structure and distinct subfields pose challenges for automatic segmentation in 3 T MRI because of its limited resolution and contrast. While 7 T MRI offers superior anatomical details and better gray-white matter contrast, aiding in clearer differentiation of hippocampal structures, its use is restricted by high costs. To bridge this gap, algorithms synthesizing 7T-like images from 3 T scans are being developed, requiring paired datasets for training. However, the scarcity of such high-quality paired datasets, particularly those with manual hippocampal subfield segmentations as ground truth, hinders progress. Herein, we introduce a dataset comprising paired 3 T and 7 T MRI scans from 20 healthy volunteers, with manual hippocampal subfield annotations on 7 T T2-weighted images. This dataset is designed to support the development and evaluation of both 3T-to-7T MR image synthesis models and automated hippocampal segmentation algorithms on 3 T images. We assessed the image quality using MRIQC. The dataset is freely accessible on the Figshare+.

Scientific DataVol. 12(1)
University Medical Center Groningen (NL), University of Groningen (NL), Chinese Academy of Sciences (CN), Beijing Normal University (CN), Institute of Biophysics (CN), University of Chinese Academy of Sciences (CN), Beihang University (CN)
National Natural Science Foundation of China, Beijing Normal University, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Youth Innovation Promotion Association
Openalex Percentile: Top 4%
Advanced MRI Techniques and Applications
6.80
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