hayyanmustafa14/abcd dataset hosted on Hugging Face and contributed by the HF Datasets community

Single-echo/multi-echo comparison pilot

This dataset contains ABCD-protocol single-echo BOLD scans, along with complex-valued, multi-echo BOLD scans for comparison. The multi-echo BOLD protocol uses the CMRR MB-EPI sequence, and comes from collaborators at UMinn. These scans include five echoes with both magnitude and phase reconstruction.

The primary goal of this dataset was to evaluate the usability of the multi-echo fMRI protocol in a larger study, via direct comparison to the ABCD fMRI protocol, as well as via test-retest reliability analyses. However, these data may be useful to others (e.g., for testing complex-valued models, applying phase regression to multi-echo data, testing multi-echo denoising methods).

Dataset contents

This dataset includes 8 participants, each with between 1 and 3 sessions. MR data were acquired using a 3-Tesla Siemens Prisma MRI scanner.

The imaging data were converted to NIfTI-1 format with dcm2niix v1.0.20220505, using heudiconv 0.13.1.

In each session, the following scans were acquired:

Structural data

A T1-weighted anatomical scan (256 slices; repetition time, TR=1900 ms; echo time, TE=2.93 ms; flip angle, FA=9 degrees; field of view, FOV=176x262.144 mm, matrix size=176x256; voxel size=1x0.977x0.977 mm).

Functional data

One run of Penn fractal n-back task five-echo fMRI data (72 slices; repetition time, TR=1761 ms; echo times, TE=14.2, 38.93, 63.66, 88.39, 113.12 ms; flip angle, FA=68 degrees; field of view, FOV=220x220 mm, matrix size=110x110; voxel size=2x2x2 mm; multiband acceleration factor=6). Both magnitude and phase data were reconstructed for this run. The run was 7:03 minutes in length, including the three no-radiofrequency-excitation volumes at the end. After the _noRF volumes were split into separate files, each run was 6:58 minutes long.

Two runs of open-eye resting-state five-echo fMRI data (72 slices; repetition time, TR=1761 ms; echo times, TE=14.2, 38.93, 63.66, 88.39, 113.12 ms; flip angle, FA=68 degrees; field of view, FOV=220x220 mm, matrix size=110x110; voxel size=2x2x2 mm; multiband acceleration factor=6). Both magnitude and phase data were reconstructed for these runs. Each run was 5:59 minutes in length, including the three no-radiofrequency-excitation volumes at the end. After the _noRF volumes were split into separate files, each run was 5:54 minutes long.

Two runs of open-eye resting-state single-echo fMRI data acquired according to the ABCD protocol (60 slices; repetition time, TR=800 ms; echo time, TE=30 ms; flip angle, FA=52 degrees; field of view, FOV=216x216 mm, matrix size=90x90; voxel size=2.4x2.4x2.4 mm; multiband acceleration factor=6). Only magnitude data were reconstructed for these runs. Each run was 6:00 minutes in length.

Field maps

Two sets of field maps were acquired for the multi-echo fMRI scans.

One set was a multiband, multi-echo gradient echo PEpolar-type field map (acq-MEGE), acquired with the same parameters as the multi-echo fMRI scans (except without magnitude+phase reconstruction). For each acquisition, we have created a copy of the single-band reference image from the first echo as the primary field map.

The other set was a multi-echo spin-echo PEpolar-type field map (acq-MESE). We have also created a copy of the first echo for each direction as a standard field map.

The single-echo copies of both the acq-MEGE and the acq-MESE field maps have B0FieldIdentifier fields and IntendedFor fields, though we used the acq-MESE field maps for the B0FieldSource fields of the multi-echo fMRI scans. Therefore, tools which leverage the B0* fields, such as fMRIPrep, should use the single-echo acq-MESE scans for distortion correction.

Single-echo PEpolar-type EPI field maps (acq-SESE) with parameters matching the single-echo fMRI data were also acquired for distortion correction.

Dataset idiosyncrasies

Multi-echo field maps

There are two sets of PEpolar-style field maps for the multi-echo BOLD scans: one gradient echo and one spin echo. Each field map set contains five echoes, like the BOLD scans. However, because distortion shouldn't vary across echoes (at least not at 3T), there is no need for multi-echo PEpolar-style field maps, and tools like fMRIPrep can't use them. As such, we have made a copy of the spin echo field map's first echo without the echo entity for BIDS compliance, as well as a copy of the gradient echo field map's first echo's single-band reference image.

No radio frequency excitation scans

The multi-echo BOLD scans included three no-radio-frequency noise scans acquired at the end of the scan, which have been split off into files with the _noRF suffix. These noise scans can be used to suppress thermal noise with NORDIC denoising. BOLD runs that were stopped early or failed to fully reconstruct may be missing these noise scans.

The _noRF suffix is not (as of 2024/03/22) supported within BIDS, but there is an open pull request adding it (https://github.com/bids-standard/bids-specification/pull/1451).

NORDIC-denoised BOLD runs

We have run NORDIC on the multi-echo scans, using the noRF files when available. The NORDIC-denoised data have the rec-nordic entity in the filenames.

We have made copies of the associated single-band reference images as well.

sub-08 ses-noHC

Subject 08's ses-noHC was accidentally acquired without the head coil plugged in. We included the session in the dataset in case anyone might find it useful, but do not recommend using the data for analyses.

sub-04 ses-2 and ses-3

Subject 04 had to stop session 2 early, so a separate session was acquired to finish acquiring the remaining scans.

Excluded data

Physio (PPG + chest belt) data were acquired for a subset of the scans, but, due to equipment issues, the data were unusable and have been excluded from the dataset.

There was also an MEGRE field map sequence in the protocol, provided by Dr. Andrew Van, but there were reconstruction errors at the scanner, so these field maps were not usable. We've chosen to exclude the remaining files from the dataset.

In some cases, we noticed reconstruction errors on final volumes in the multi-echo BOLD runs. When that happened, we dropped any trailing volumes, so that all files from a given run are the same length. For some runs, this involved entirely removing the noRF scans.

Penn Fractal N-Back events files

The events files for the fractal n-back task are not included in version 1.0.0 of the dataset. We will add them in a future patch release.

Notes about acquisition

The multi-echo BOLD scans were acquired on a 3T Siemens Prisma scanner running VE11C. The same protocol has exhibited consistent reconstruction errors on XA30.

ABCD A

## Overview

ABCD A is a dataset for instance segmentation tasks - it contains 123 annotations for 260 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

In vitro data from cell-based assays on the inhibition of BDE and its hydroxylated metabolite on ABC transporters. This dataset is associated with the following publication: Marchitti, S., C. Mazur, C. Dillingham, S. Rawat, A. Sharma, J. Zastre, and J. Kenneke. Inhibition of the Human ABC Efflux Transporters P-gp and BCRP by the BDE-47 Hydroxylated Metabolite 6-OH-BDE-47: Considerations for Human Exposure. TOXICOLOGICAL SCIENCES. Society of Toxicology, 155(1): 270-282, (2017).

San Diego State University Traveling Subjects Diffusion MRI (SDSU-TS) Dataset

The San Diego State University Traveling Subjects Diffusion MRI (SDSU-TS) dataset was designed to facilitate the harmonization of MRI data acquired across autism neuroimaging studies conducted at San Diego State University (SDSU). The dataset includes MRI scans from 9 healthy adult participants (aged 22-55 years) collected at 2 imaging sites: SDSU Imaging Center (SDSU-MRI) and Center for Functional MRI, UC San Diego (CFMRI). Each participant was scanned at least once at both sites, with rescan data available for 5 participants at SDSU-MRI and 6 participants at CFMRI. The average interval between scan sessions within a participant was 7 days (range: 1-19 days).

The scan protocols we collected reflect those used in SDSU autism MRI studies over the last 10-15 years and include the following:

• 5 diffusion-weighted (3 at CFMRI, 2 at SDSU-MRI)
• 3 T1-weighted (2 at CFMRI, 1 at SDSU-MRI)
• 2 T2-weighted (1 at each site)

Additionally, diffusion-weighted MRI protocols matching the publicly available Adolescent Brain Cognitive Development (ABCD) and Lifespan Human Connectome Project (HCP) studies were collected.

Scan Protocols

The MRI protocols acquired at each site are shown below:

SDSU-MRI (GE Discovery MR750 3T)

CFMRI (Siemens Prisma 3T)

Note: - TE = Echo time (ms); TR = Repetition time (s); Res = spatial resolution. - Reversed phase-encoding fieldmaps were acquired for all protocols. - All data were acquired using a 32-channel head coil, except for the legacy sequences at CFMRI, which were acquired using an 8-channel head coil.

The unprocessed MRI data are provided along with anonymized participant demographic data.

The imaging data was converted to BIDS using ezBIDS (https://brainlife.io/ezbids) and custom scripts. All anatomical scans have been defaced using the Quickshear method in ezBIDS.

Data Notes

Please note the following:

• The 1shell61dir data in the cfmri1 session of subjects ts001, ts002, and ts004 were acquired with a variant spatial resolution (0.94x0.94mm instead of 1.875x1.875mm in-plane resolution).
• The 3shell45dir data in the cfmri1 session of subject ts002 was acquired with a variant spatial resolution (2mm instead of 2.5mm slice thickness).
• The 1shell61dir data in the cfmri1 session of subject ts010 was acquired with a variant TE (0.0843 instead of 0.0818s).
• The sdsu1 session hcplifespan protocol for subjects ts002 and ts003 was not acquired with reversed phase-encoding directions (needed for distortion correction) and are not included in the dataset but are available upon request.

Reference

Hau, J., Scarlett, S., & Arantes de Oliveira Campos, G. (2025). A traveling subjects dataset for diffusion MRI harmonization benchmarking [Poster presentation]. International Society for Magnetic Resonance in Medicine Workshop on 40 Years of Diffusion: Past, Present & Future Perspectives, Kyoto, Japan.

This dataset is about book subjects. It has 9 rows and is filtered where the books is The ABC murders. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This file contains pressure level parameters from ensemble member 6. For more information, please visit https://github.com/metno/NWPdocs/wiki

This dataset is about book subjects. It has 5 rows and is filtered where the books is ABC of Egyptian hieroglyphs. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

cnfatal/abc dataset hosted on Hugging Face and contributed by the HF Datasets community

imadchougle/abc dataset hosted on Hugging Face and contributed by the HF Datasets community

Register of protected and endangered fungi of Poland (GREJ) is an online database that gathers information on the occurrence of mushrooms rarely listed, protected or threatened, and alien in Poland. The database is available on-line at: https://www.grzyby.pl/rejestr-grzybow-chrononych-i-zagrozonych.htm. The regulations of the database are available at: https://www.grzyby.pl/regulamin-GREJ.htm. Most of the records are finds made by non-professional mycologists. The finder, posting a report in GREJ, does so for the good of science and for his own satisfaction; agrees to the use of data in research. The database is strictly moderated. This means that the records pass the approval of the curators. The curators of information in the database and at the same time moderators of the records are: Anna Kujawa, Błażej Gierczyk and Tomasz Ślusarczyk. The database administrator is Marek Snowarski. Register of protected and endangered fungi of Poland (GREJ) is an online database that gathers information on the occurrence of mushrooms rarely listed, protected or threatened, and alien in Poland. The database is available on-line at: https://www.grzyby.pl/rejestr-grzybow-chrononych-i-zagrozonych.htm. The regulations of the database are available at: https://grzyby.pl/regulamin-GREJ.htm. Most of the records are finds made by non-professional mycologists. The finder, posting a report in GREJ, does so for the good of science and for his own satisfaction; agrees to the use of data in research. The database is strictly moderated. This means that the records pass the approval of the curators. The curators of information in the database and at the same time moderators of the records are: Anna Kujawa, Błażej Gierczyk, and Tomasz Ślusarczyk. The database administrator is Marek Snowarski. The current version (2022) of the database consists of all records uploaded to GREJ before 14.03.2022, excluding data without registeredBy and atpol information. Taxonomy was aligned to GBIF backbone on 11.07.2022.

abidlabs/abc-love2 dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset contains the digitized treatments in Plazi based on the original journal article Supeleto, Fernanda A., Santos, Bernardo F., Aguiar, Alexandre P. (2022): Revision of Fortipalpa Kasparyan & Ruíz-Cancino, (Ichneumonidae, Cryptinae). Zootaxa 5219 (6): 501-533, DOI: 10.11646/zootaxa.5219.6.1

The dataset contains longitudinal bulk sequencing data of FACS sorted T cells (CD3+CD4+, CD3+CD8+, CD3+CD4+CCR7+, CD3+CD4+CCR7-, CD3+CD8+CCR7+, CD3+CD8+CCR7-) from peripheral blood mononuclear cells (PBMCs) of 4 Multiple Sclerosis (MS) patients treated with fingolimod (FTY720) compared to 2 untreated controls. For treated patients TP1: Baseline; TP2: 6-12 months. For untreated controls TP1: m1; TP2: 6-12 months

The dataset contains bulk sequencing data of FACS sorted B cells (naive B cells-NB; memory B cells - MB) and T cells (CD4+, CD8+) T cells from peripheral blood mononuclear cells (PBMCs) of 1 Multiple Sclerosis (MS) patients treated with Ocrelizumab (Ocrevuz). For treated patient TP1: 6m before baseline; TP2: Baseline; TP3: cycle 1 + 3 months; TP4: cycle 1 + 6 months; TP5: cycle 2 + 5 months.

The dataset of airborne LiDAR mission in the Dayekou flight zone on Jun. 20, 2008 included peak pulse data (*.LAS), full waveform data (.lgc), CCD photos, DEM, DSM and DOM. The DEM, DSM and DOM data are stored along with the Dataset of airborne LiDAR mission in the Dayekou flight zone on Jun. 23, 2008. The flight routes were as follows:

{| ! flight route ! startpoint lat ! startpoint lon ! endpoint lat ! endpoint lon ! altitude (m) ! length (km) ! photos |- | 1 || 38°32′05.38″ || 100°12′24.59″ || 38°29′32.76″ || 100°18′35.69″ || 3650 || 10.1 || 49 |- | 2 || 38°32′11.13″ || 100°12′28.42″ || 38°29′42.06″ || 100°18′30.89″ || 3650 || 9.9 || 46 |- | 3 || 38°32′16.88″ || 100°12′32.24″ || 38°29′47.81″ || 100°18′34.72″ || 3650 || 9.9 || 47 |- | 4 || 38°32′22.63″ || 100°12′36.07″ || 38°29′56.20″ || 100°18′32.15″ || 3650 || 9.7 || 45 |- | 5 || 38°32′28.38″ || 100°12′39.90″ || 38°30′02.62″ || 100°18′34.33″ || 3650 || 9.7 || 47 |- | 6 || 38°32′37.44″ || 100°12′35.66″ || 38°30′10.63″ || 100°18′32.68″ || 3650 || 9.8 || 44 |- | 7 || 38°32′46.50″ || 100°12′31.43″ || 38°30′19.72″ || 100°18′28.37″ || 3650 || 9.8 || 47 |}

lvwerra/abc-test dataset hosted on Hugging Face and contributed by the HF Datasets community