Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) is currently a free one-stop-shop collaboratory for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, or computing power.
NITRC scientific focus includes: PET/SPECT, CT, EEG/MEG, optical imaging, clinical neuroinformatics, computational neuroscience, and imaging genomics software tools, data, and computational resources.
NITRC database currently contains 14 projects, 6845 subjects, and 8285 imaging sessions.
ID | Name | Description | Access type ------|------------|------------------------------|------------- fcon_1000|1000 Functional Connectomes|The 1000 Functional Connectomes Project.|Public project ixi|IXI dataset|IXI (Information eXtraction from Images) dataset. 600 MR images from normal, healthy subjects.|Public project. cs_schizbull08|CANDI Share: Schizophrenia Bulletin 2008|Version 1.1 of the CANDI Share Schizophrenia Bulletin 2008 data.|Public project. parktdi|High-quality diffusion-weighted imaging of Parkinson's disease|Data for a set of 53 subjects in a cross-sectional Parkinson's disease (PD) study.|Public project. studyforrest_rev003|Study Forrest rev003|Study Forrest rev00 3. http://studyforrest.org/ Supported by BMBF 01GQ1112 and NSF 1129855.|Public project. ABIDE|ABIDE|Autism Brain Imaging Data Exchange.|Access required. adhd_200|ADHD-200|The ADHD-200 sample from the 1000 Functional Connectomes project.|Access required. beijing_enh|Beijing Enhanced|INDI Beijing Enhanced.|Access required. beijing_eoec|Beijing Eyes Open Eyes Closed|INDI Beijing Eyes Open Eyes Closed Study.|Access required. short_tr|Beijing Short TR|INDI Beijing Short TR Study.|Access required. corr|Consortium for Reliability and Reproducibility (CoRR)|The goal of CoRR was to create an open science resource for the imaging community that facilitates the assessment of test-retest reliability and reproducibility.|Access required. nki_rockland|INDI NKI/Rockland Sample||Access required. kin|Kurtosis Imaging Network (KIN)|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.|Access required. PING|Pediatric Imaging, Neurocognition, and Genetics (PING) Study|The Data Resource includes neurodevelopmental histories, information about developing mental and emotional functions, multimodal brain imaging data, and genotypes for well over 1000 children and adolescents between the ages of 3 and 20.|Access required.
In order to access the NITRC data, a user account is required. One can be requested here. Some of the projects are public and can be accessed right away, while some others will need an additional access request.
You can install
nitrcbot from github with:
# install.packages("devtools") devtools::install_github("adigherman/nitrcbot")
nitrcbot package, set_credentials will set the username and password:
set_credentials(username = "XXX", password = "YYY")
or they can be stored in
NITRC_WEB_PASS environment variables.
Once the username and password are set,
nitrcbot functions can be used. To test the username and password, one can run
list_image_sets, a simple function that will retrieve all available NITRC projects summary.
nitrc_sets <- nitrcbot::list_image_sets() nitrc_sets_summary <- nitrc_sets[,c("ID","Name","Subjects")]
nitrc_sets_summary ID Name Subjects 1 kin Kurtosis Imaging Network 81 2 studyforrest_rev003 Study Forrest rev003 20 3 nki_rockland INDI NKI/Rockland Sample 207 4 PING Pediatric Imaging, Neurocognition, and Genetics (PING) Study 0 5 ixi IXI dataset 584 6 parktdi High-quality diffusion-weighted imaging of Parkinson's disease 53 7 cs_schizbull08 CANDI Share: Schizophrenia Bulletin 2008 103 8 short_tr Beijing Short TR 28 9 beijing_eoec Beijing Eyes Open Eyes Closed 48 10 beijing_enh Beijing Enhanced 180 11 ABIDE ABIDE 1112 12 corr Consortium for Reliability and Reproducibility (CoRR) 1386 13 fcon_1000 1000 Functional Connectomes 1288 14 adhd_200 ADHD-200 973
The username and password are valid and we have a list of all 14 NITRC projects. If a project has 0 subjects (e.g. PING) this means we need to request access to the PING project through the NITRC website.
As an example we will download a directory of images from the
ixi project. The first step is to read the project data into a data.frame and for that we'll use the
ixi_project <- read_nitrc_project('ixi') head(ixi_project) ID label project gender handedness session_ID scan_ID age 1 NITRC_IR_S05189 2 ixi female NITRC_IR_E10452 PD 35.8 2 NITRC_IR_S05189 2 ixi female NITRC_IR_E10452 T1 35.8 3 NITRC_IR_S05189 2 ixi female NITRC_IR_E10452 MRA 35.8 4 NITRC_IR_S05189 2 ixi female NITRC_IR_E10452 DTI 35.8 5 NITRC_IR_S05189 2 ixi female NITRC_IR_E10452 T2 35.8 6 NITRC_IR_S05190 12 ixi male NITRC_IR_E10453 T1 38.78
We can subset the
ixi subjects that are
male and have
ixi_T1_males = ixi_project %>% filter(gender %in% "male") %>% filter(scan_ID %in% "T1") %>% select(ID, session_ID) %>% unique head(ixi_T1_males)
ID session_ID 1 NITRC_IR_S05190 NITRC_IR_E10453 2 NITRC_IR_S05191 NITRC_IR_E10454 3 NITRC_IR_S05193 NITRC_IR_E10456 4 NITRC_IR_S05194 NITRC_IR_E10457 5 NITRC_IR_S05196 NITRC_IR_E10459 6 NITRC_IR_S05197 NITRC_IR_E10460
We can now download the full directory (individual files) of T1 data using
download_nitrc_dir and providing the
t1_res <- download_nitrc_dir("NITRC_IR_E10453", scan_type="T1") t1_res$files  "77390_IXI012-HH-1211-T1.nii.gz" "77391_qc_t.gif" "77391_qc.gif"
If we'd rather download a zipped file containing the full directory, we need to specify
zipped = TRUE as argument for the
> download_nitrc_dir("NITRC_IR_E10453", scan_type="T1", zipped = TRUE)  "/var/folders/kr/05bm5krj0r3fpwxfdmx4xthm0000gn/T//RtmpVWPpmG/NITRC_IR_E10453.zip"
We can also download a single file using
download_nitrc_file. To identify the file URI, we'll use the
r <- get_scan_resources('NITRC_IR_E10453') > head(r$URI)  "/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-00.nii.gz"  "/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-01.nii.gz"  "/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-02.nii.gz"  "/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-03.nii.gz"  "/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-04.nii.gz"  "/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-05.nii.gz"
> download_nitrc_file("/data/experiments/NITRC_IR_E10453/scans/DTI/resources/77382/files/IXI012-HH-1211-DTI-05.nii.gz")  "/var/folders/kr/05bm5krj0r3fpwxfdmx4xthm0000gn/T//RtmpVWPpmG/IXI012-HH-1211-DTI-05.nii.gz"
To retrieve the scan paramaters for a specific subject we can use the
> get_scan_params('NITRC_IR_E11033') type imagescandata_id TR TE flip matrix_X matrix_Y voxel_X voxel_Y voxel_Z frames partitions fieldStrength quality 1 DTI 44882 9054.01 80.0 90 2 MRA 44883 20.0 6.9052 25 3 PD 44884 8178.34 8.0 90 4 T1 44885 9.813 4.603 8 5 T2 44886 8178.34 100.0 90
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