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End of preview. Expand in Data Studio

This dataset is derived from the Southwest University Adult Lifespan Dataset (SALD), a large-scale cross-sectional neuroimaging dataset designed to characterize brain structure and function across the adult lifespan. The study recruited community-dwelling adults between ages 19 and 80 from Southwest University in Chongqing, China. At each session, participants contributed T1-weighted structural MRI images alongside behavioral and cognitive assessments. Here, we provide a 2D slice-based version of T1-weighted (T1w) MRI volumes, extracted from cognitively normal subjects across the full age range.

πŸ“¦ Dataset Structure

Each entry corresponds to a single 2D slice from a 3D MRI volume:

  • volume_id β†’ Unique identifier for the subject/volume
  • slice_id β†’ Index of the slice within the volume
  • age β†’ Age of the participant at time of scan
  • sex β†’ Biological sex of the participant ('M' / 'F')
  • image β†’ 2D MRI slice

βš™οΈ Preprocessing

  • Only T1-weighted (T1w) volumes were used
  • Volumes were converted into 2D axial slices
  • Slices were normalized and resized to 256Γ—256

⚠️ Caveat

Late slices in each volume have noise in them.

πŸš€ Usage

from datasets import load_dataset
import matplotlib.pyplot as plt

ds = load_dataset("chehablab/SALD_t1w", split="train")
sample = ds[314]
img = sample["image"]
plt.imshow(img, cmap="gray")
plt.title(f"Volume {sample['volume_id']} | Slice {sample['slice_id']} | Age {sample['age']} | Sex {sample['sex']}")
plt.axis("off")
plt.show()

πŸ“š Citation

If you use this dataset, please acknowledge our lab Chehab Lab and cite the original SALD dataset:

@article {Wei177279,
    author = {Wei, Dongtao and Zhuang, Kaixiang and Chen, Qunlin and Yang, Wenjing and Liu, Wei and Wang, Kangcheng and Sun, Jiangzhou and Qiu, Jiang},
    title = {Structural and functional MRI from a cross-sectional Southwest University Adult lifespan Dataset (SALD)},
    year = {2018},
    doi = {10.1101/177279},
    publisher = {Cold Spring Harbor Laboratory},
    journal = {bioRxiv}
}

License

This work is licensed under a Creative Commons CC BY-NC-SA 4.0 License. CC BY-NC-SA 4.0

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