TAN Yiheng, ZONG Fangrong. Construction of a Paired MRI Brain Imaging Dataset Across Field StrengthsJ. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2026-0431
Citation: TAN Yiheng, ZONG Fangrong. Construction of a Paired MRI Brain Imaging Dataset Across Field StrengthsJ. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2026-0431

Construction of a Paired MRI Brain Imaging Dataset Across Field Strengths

  • Objective This study aimed to construct a paired low-field and high-field healthy-brain MRI dataset to provide a valuable resource for low-field MRI super-resolution (SR) research. Methods Post-graduate students enrolled at Beijing University of Posts and Telecommunications from January to March 2026 were recruited and underwent brain MRI scans on both a 0.2 T low-field scanner and a 3.0 T high-field scanner. The low-field protocol comprised three axial sequences—fluid-attenuated inversion recovery (FLAIR),fast spin echo (FSE),and multi-spin-echo (MSSE). The high-field protocol included a magnetization-prepared rapid gradient echo (MPRAGE) sequence with isotropic resolution,as well as diffusion-weighted imaging (DWI).Post-acquisition processing included format conversion,orientation unification,bias-field correction,intensity normalization,automated brain parcellation,and SynthSR-hyperfine SR reconstruction using paired 0.2T MSSE/FSE inputs. Results After quality control and selection,a total of 76 imaging volumes were obtained,including complete 0.2 T/3.0 T paired data for 10 subjects and 0.2 T-only data for 2 additional subjects. 32-label brain parcellations were successfully generated for all 10 paired subjects. SR volumes generated from MSSE/FSE pairs showed a certain level of improvement in image quality. Across the 10 paired subjects,mean metrics were: SNR 168.470±60.329,CNR 1.729±0.087. Conclusions This dataset provides a multi-sequence paired brain MRI resource at 0.2 T and 3.0 T. It can serve as a benchmark for training and evaluating low-field MRI super-resolution models and for cross-field-strength image quality studies.
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