chehablab/DLBS_t1w_t2w

This dataset is derived from the Dallas Lifespan Brain Study (DLBS), a comprehensive longitudinal neuroimaging dataset spanning the adult lifespan. The study integrated brain and cognition across the adult lifespan, with participants between ages 21 and 89 at the time of first assessment, returning approximately every 3.5–5 years for up to three waves of data collection. At each wave, participants contributed T1-weighted images, T2-weighted images, functional MRI images, arterial spin labeling (ASL) images, and diffusion tensor imaging (DTI) images. Here, we provide a 2D slice-based version of T1-weighted (T1w) and T2-weighted (T2w) MRI volumes, extracted from cognitively normal subjects across all available waves.

📦 Dataset Structure

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

• —volume_id → Unique identifier for the subject/volume
• —wave_id→ Longitudinal collection epoch (1, 2, or 3)
• —type → 't1w'/'t2w'
• —slice_id → Index of the slice within the volume
• —image → 2D MRI slice

⚙️ Preprocessing

• —Only T1-weighted (T1w) and T2-weighted (T2w) volumes were used
• —Volumes were converted into 2D axial slices
• —Slices were normalized and resized to 256×256

🚀 Usage

from datasets import load_dataset
import matplotlib.pyplot as plt

ds = load_dataset("chehablab/DLBS_t1w_t2w", split="train")

sample = ds[314]
img = sample["image"]

plt.imshow(img, cmap="gray")
plt.title(f"Volume {sample['volume_id']} | Wave {sample['wave_id']} | Slice {sample['slice_id']} | Type {sample['type']}")
plt.axis("off")
plt.show()

📚 Citation

If you use this dataset, please acknowledge our lab [Chehab Lab](https://chehablab.com/) and cite the original DLBS dataset:

@article{Park2025,
author = {Park, Denise C. and Wig, Gagan S. and others},
title = {The Dallas Lifespan Brain Study: A Comprehensive Adult Lifespan Data Set of Brain and Cognitive Aging},
journal = {Scientific Data},
year = {2025},
doi = {10.1038/s41597-025-04847-7},
}

📜 License

This dataset is released under the Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain Dedication. You may copy, modify, distribute, and use the data, even for commercial purposes, without asking permission. 

Chehab Lab @ 2026