The NITRC Image Repository allows you to search for and freely download public datasets. It includes millions of dollars worth of DICOM and NIfTI images with normal and diagnoses such as child development disorders, Aspergers, Autism, ADHD, Parkinson’s and Schizophrenia.

Recently Registered DataSets

  • High-quality diffusion-weighted imaging of Parkinson's disease - This project contains data and analysis pipelines for a set of 53 subjects in a cross-sectional Parkinson's disease (PD) study. The dataset contains diffusion-weighted images (DWI) of 27 PD patients and 26 age, sex, and education-matched control subjects. The DWIs were acquired with 120 unique gradient directions, b=1000 and b=2500 s/mm2, and isotropic 2.4 mm3 voxels. The acquisition used a twice-refocused spin echo sequence in order to avoid distortions induced by eddy currents. Processing scripts for the paper can be found on Github:

  • IXI Dataset - The IXI Dataset is a collection of nearly 600 MR images from normal, healthy subjects. The MR image acquisition protocol for each subject includes T1, T2 and PD-weighted images, MRA images, and diffusion-weighted images (15 directions). The data was collected at three different hospitals in London using 1.5T and 3T scanners.

  • Kurtosis Imaging Network - KIN - KIN has an alternative website please go to: Kurtosis Imaging Network (KIN) is an open source database for normal healthy controls as well as various pathologies in an attempt to establish a standard range of kurtosis values within each population. This database of diffusional kurtosis images will also allow for quantitative comparisons between sites, vendors, and various protocol parameters. Finally, KIN will also help develop a strong collaborative network for researchers to troubleshoot current projects and create future projects. By downloading or uploading data from and to KIN you automatically accept the KIN data use agreement which certifies that you understand and agree to all applicable terms contained herein.

  • studyforrest - We provide extensive functional brain imaging data from natural stimulation, a rich set of auxiliary data, (such as structural brain scans, measurements of physiological, and technical confounds), as well as stimulus annotations.

  • CANDI Share: Schizophrenia Bulletin 2008 - This project hosts data for CANDI Share Schizophrenia Bulletin 2008 (reference below) as part of the CANDI Neuroimaging Access Point. This set includes preprocessed MRI images and segmentation results of all 4 diagnostic groups (Healthy Controls, N=29; Schizophrenia Spectrum, N=20; Bipolar Disorder with Psychosis, N=19; and Bipolar Disorder without Psychosis, N=35). Frazier JA, Hodge SM, Breeze JL, Giuliano AJ, Terry JE, Moore CM, Kennedy DN, Lopez-Larson MP, Caviness VS, Seidman LJ, Zablotsky B, Makris N. Diagnostic and sex effects on limbic volumes in early-onset bipolar disorder and schizophrenia. Schizophr Bull. 2008 Jan;34(1):37-46.

  • 1000 Functional Connectomes Project - ATTENTION: The 1000 Functional Connectomes Project has a new home page at NITRC. Please visit us at: This is the parent project for ABIDE, ADHD-200 (ADHD200), INDI, CORR, NKI-Rockland (NKI), Healthy Brain Network (HBN) and other projects.

  • PING - Pediatric Imaging, Neurocognition, and Genetics - PING for short. PING represents an ambitious, multi-site project involving a Coordinating Center, and 4 Scientific Cores. Leading pediatric researchers across the country are participating at nine universities nation-wide: UC San Diego, the University of Hawaii, UCLA, UC Davis, Kennedy Krieger Institute at Johns Hopkins, Sackler Institute at Cornell University, the University of Massachusetts, Massachusetts General Hospital at Harvard University, and Yale. The overarching goal of the project is to create a large MRI and genetics data resource to be shared openly with the scientific community. The data resource will also include information about the developing mental and emotional functions of the children. Investigators on the project are studying 1400 children between the ages of 3 and 20 years so that links between genetic variation and developing patterns of brain connectivity can be examined.

  • Brain Genomics Superstruct Project (GSP) Open Access Data Release - Instructions for accessing the GSP Open Access Data may be found at