cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15697195
title: Open dataset of annotated DICOM images of head CTA for intracranial aneurysm detection

description: Overview

We release a collection of computed tomography angiography (CTA) DICOM studies, including confirmed intracranial aneurysm (IA) cases and aneurysm-free controls. This dataset contains 172 anonymized CTA scan series (90 controls, 82 IA cases) with expert annotations of aneurysms and metadata. The data collected from three clinical centers addresses the critical shortage of high-quality, diverse cerebrovascular imaging data. A consecutive sampling method was used to collect the data. The dataset is characterized by a wide variety of pathology shapes and sizes, including a large number (24%) of difficult-to-diagnose miliary aneurysms.

Features

Image series

-        DICOM format

-        Full DICOM anonymized

-        Face removal (Defacing)

-        Slice thickness 0.5-2 mm

Annotations

-        Curation by two experts: a neurosurgeon and neuroradiologist, each with over 20 years of experience

-        Threshold-based segmentation after manual aneurysm isolation

-        STL format

Metadata

-        Table in CSV format

-        Contains:

·         Patient ID

·         Presence of pathology

·         Aneurysm ID

·         Sex

·         Age

·         Parent artery

·         Shape (saccular/nonsaccular)

·         Position classification (lateral/bifurcation/unclassifiable)

·         Type of nonsaccular aneurysm (blister-like/fusiform/eccentric-fusiform/fusiform-saccular/unclassifiable)

·         Size classification (miliary (<3mm)/middle (3-15mm)/large (15-25mm)/giant (≥25mm))

·         Measurements (neck size, maximum length, maximum width, aneurysm volume)

·         Complexity factors (rupture, bleb, thrombus, calcification, vessel arising from the dome)

·         Series description (number of images, slice thickness, inclusion of the carotid bifurcation area)

Applications

-        Training, validation and testing of artificial intelligence models for IA detection/segmentation

-        Hemodynamic risk simulation (computational fluid dynamics)

-        Morphometric analysis

Usage notes

Image data for each case is stored in a folder named with its unique identifier (`CaseID`). Segmentation masks are named `an_CaseID` for single aneurysms and `an_CaseID_N` for multiple aneurysms, where N is the specific aneurysm identifier from the metadata (e.g., an_123_1.stl, an_123_2.stl).

This study involving human data was conducted in accordance with the Declaration of Helsinki and approved by the Biomedical Ethics Committee of the N.V. Sklifosovsky Research Institute for Emergency Medicine (Protocol No. 2-23, March 28, 2023). The dataset is publicly accessible under CC-BY 4.0. We kindly request that any publication using this dataset cites the original paper describing its creation: ***.
DOI: 10.5281/zenodo.15697196
title: Open dataset of annotated DICOM images of head CTA for intracranial aneurysm detection

description: Overview

We release a collection of computed tomography angiography (CTA) DICOM studies, including confirmed intracranial aneurysm (IA) cases and aneurysm-free controls. This dataset contains 172 anonymized CTA scan series (90 controls, 82 IA cases) with expert annotations of aneurysms and metadata. The data collected from three clinical centers addresses the critical shortage of high-quality, diverse cerebrovascular imaging data. A consecutive sampling method was used to collect the data. The dataset is characterized by a wide variety of pathology shapes and sizes, including a large number (24%) of difficult-to-diagnose miliary aneurysms.

Features

Image series

-        DICOM format

-        Full DICOM anonymized

-        Face removal (Defacing)

-        Slice thickness 0.5-2 mm

Annotations

-        Curation by two experts: a neurosurgeon and neuroradiologist, each with over 20 years of experience

-        Threshold-based segmentation after manual aneurysm isolation

-        STL format

Metadata

-        Table in CSV format

-        Contains:

·         Patient ID

·         Presence of pathology

·         Aneurysm ID

·         Sex

·         Age

·         Parent artery

·         Shape (saccular/nonsaccular)

·         Position classification (lateral/bifurcation/unclassifiable)

·         Type of nonsaccular aneurysm (blister-like/fusiform/eccentric-fusiform/fusiform-saccular/unclassifiable)

·         Size classification (miliary (<3mm)/middle (3-15mm)/large (15-25mm)/giant (≥25mm))

·         Measurements (neck size, maximum length, maximum width, aneurysm volume)

·         Complexity factors (rupture, bleb, thrombus, calcification, vessel arising from the dome)

·         Series description (number of images, slice thickness, inclusion of the carotid bifurcation area)

Applications

-        Training, validation and testing of artificial intelligence models for IA detection/segmentation

-        Hemodynamic risk simulation (computational fluid dynamics)

-        Morphometric analysis

Usage notes

Image data for each case is stored in a folder named with its unique identifier (`CaseID`). Segmentation masks are named `an_CaseID` for single aneurysms and `an_CaseID_N` for multiple aneurysms, where N is the specific aneurysm identifier from the metadata (e.g., an_123_1.stl, an_123_2.stl).

This study involving human data was conducted in accordance with the Declaration of Helsinki and approved by the Biomedical Ethics Committee of the N.V. Sklifosovsky Research Institute for Emergency Medicine (Protocol No. 2-23, March 28, 2023). The dataset is publicly accessible under CC-BY 4.0. We kindly request that any publication using this dataset cites the original paper describing its creation: ***.
DOI: 10.5281/zenodo.15495917
title: Proplyd Line Ratios

description: An example script for plotting line ratios is available on the github at: https://github.com/TygerPeake/Proplyd-Line-Ratios

 

lines.csv 

3 columns with headers :

'Lines' - The species and wavelength for all 5911 lines are given in either units of angstroms A or micrometres m. 

'Mean Luminosity' - The mean luminosity of the line across all distances over the same mean for H alpha. 

'LM' - The line measure of each line as described in the paper (see equations 9, 10, 11).

 

luminosity_ratios.npy

A 10 x 5911 x 5911 matrix of emission line luminosity ratios for the base-case proplyd (see the paper for a description). 

The lines are ordered as in lines.csv for the axes of length 5911.

The 1st index spans 10 distances of the proplyd from the UV source (see position.csv).

The 2nd index is the luminosity of the line on the top of the ratio.

The 3rd index is the luminosity of the line on the bottom of the ratio.

 

position.csv

2 columns with headers:

'Distance [pc]' - The 10 distances used in luminosity_ratios.npy. 

'FUV [G0]' - The FUV field strength associated with each distance.
DOI: 10.5281/zenodo.15495918
title: Proplyd Line Ratios

description: An example script for plotting line ratios is available on the github at: https://github.com/TygerPeake/Proplyd-Line-Ratios

 

lines.csv 

3 columns with headers :

'Lines' - The species and wavelength for all 5911 lines are given in either units of angstroms A or micrometres m. 

'Mean Luminosity' - The mean luminosity of the line across all distances over the same mean for H alpha. 

'LM' - The line measure of each line as described in the paper (see equations 9, 10, 11).

 

luminosity_ratios.npy

A 10 x 5911 x 5911 matrix of emission line luminosity ratios for the base-case proplyd (see the paper for a description). 

The lines are ordered as in lines.csv for the axes of length 5911.

The 1st index spans 10 distances of the proplyd from the UV source (see position.csv).

The 2nd index is the luminosity of the line on the top of the ratio.

The 3rd index is the luminosity of the line on the bottom of the ratio.

 

position.csv

2 columns with headers:

'Distance [pc]' - The 10 distances used in luminosity_ratios.npy. 

'FUV [G0]' - The FUV field strength associated with each distance.
DOI: 10.6084/m9.figshare.30010723
title: Neurodiversity Aware or Hyperaware AI? Visual stereotypes of autism spectrum in Janus-Pro-7B, DALL-E, Stable Diffusion, SDXL, FLUX, and Midjourney. Research Protocol

description: Avoiding systemic discrimination of neurodiverse individuals is an ongoing challenge in training language models, which often propagate negative stereotypes. This study examined whether six text-to-image models (Janus-Pro-7B VL2 vs. VL3, DALL-E 3 v. April 2024 vs. August 2025, Stable Diffusion v. 1.6 vs. 3.5, SDXL v. April 2024 vs. FLUX.1 Pro, and Midjourney v. 5.1 vs. 7) perpetuate non-rational beliefs regarding autism by comparing images generated in 2024-2025 with controls. 53 prompts aimed at neutrally visualizing concrete objects and abstract concepts related to autism were used against 53 controls (baseline total N=302, follow-up experimental 280 images plus 265 controls). Expert assessment measuring the presence of common autism-related stereotypes employed a framework of 10 deductive codes followed by statistical analysis. Autistic individuals were depicted with striking homogeneity in skin color (white), gender (male), and age (young), often engaged in solitary activities, interacting with objects rather than people, and exhibiting stereotypical emotional expressions such as sadness, anger, or emotional flatness. In contrast, the images of neurotypical individuals were more diverse and lacked such traits. We found significant differences between the models; however, with a moderate effect size (baseline $\eta^2 = 0.05$ and follow-up η = 0.08$), and no differences between baseline and follow-up summary values, with the ratio of stereotypical themes to the number of images similar across all models. The control prompts showed a significantly lower degree of stereotyping with large size effects (DALL·E 3 η = 0.39; Midjourney η = 0.41; FLUX η = 0.20; Stable Diffusion η = 0.34; DeepSeek-VL3 η = 0.45) confirming the hidden biases of the models. In summary, despite improvements in the technical aspects of image generation, the level of reproduction of potentially harmful autism-related stereotypes remained largely unaffected.
DOI: 10.6084/m9.figshare.30010723.v1
title: Neurodiversity Aware or Hyperaware AI? Visual stereotypes of autism spectrum in Janus-Pro-7B, DALL-E, Stable Diffusion, SDXL, FLUX, and Midjourney. Research Protocol

description: Avoiding systemic discrimination of neurodiverse individuals is an ongoing challenge in training language models, which often propagate negative stereotypes. This study examined whether six text-to-image models (Janus-Pro-7B VL2 vs. VL3, DALL-E 3 v. April 2024 vs. August 2025, Stable Diffusion v. 1.6 vs. 3.5, SDXL v. April 2024 vs. FLUX.1 Pro, and Midjourney v. 5.1 vs. 7) perpetuate non-rational beliefs regarding autism by comparing images generated in 2024-2025 with controls. 53 prompts aimed at neutrally visualizing concrete objects and abstract concepts related to autism were used against 53 controls (baseline total N=302, follow-up experimental 280 images plus 265 controls). Expert assessment measuring the presence of common autism-related stereotypes employed a framework of 10 deductive codes followed by statistical analysis. Autistic individuals were depicted with striking homogeneity in skin color (white), gender (male), and age (young), often engaged in solitary activities, interacting with objects rather than people, and exhibiting stereotypical emotional expressions such as sadness, anger, or emotional flatness. In contrast, the images of neurotypical individuals were more diverse and lacked such traits. We found significant differences between the models; however, with a moderate effect size (baseline $\eta^2 = 0.05$ and follow-up η = 0.08$), and no differences between baseline and follow-up summary values, with the ratio of stereotypical themes to the number of images similar across all models. The control prompts showed a significantly lower degree of stereotyping with large size effects (DALL·E 3 η = 0.39; Midjourney η = 0.41; FLUX η = 0.20; Stable Diffusion η = 0.34; DeepSeek-VL3 η = 0.45) confirming the hidden biases of the models. In summary, despite improvements in the technical aspects of image generation, the level of reproduction of potentially harmful autism-related stereotypes remained largely unaffected.
DOI: 10.5517/ccdc.csd.cc2jdfds
title: CCDC 2335645: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfft
title: CCDC 2335646: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfgv
title: CCDC 2335647: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfhw
title: CCDC 2335648: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfjx
title: CCDC 2335649: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfky
title: CCDC 2335650: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdflz
title: CCDC 2335651: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfm0
title: CCDC 2335652: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfn1
title: CCDC 2335653: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jdfp2
title: CCDC 2335654: Experimental Crystal Structure Determination

description: Related Article: Maximilian P. Müller, Alexander Hinz|2024|Angew.Chem.,Int.Ed.|63|e202405319|doi:10.1002/anie.202405319
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l54jg
title: CCDC 2388225: Experimental Crystal Structure Determination

description: Related Article: Emilie Delahaye, Marie Noelle Lalloz-Vogel, Carine Duhayon, Jean-Pascal Sutter|2024|Eur.J.Inorg.Chem.|28|e202500048|doi:10.1002/ejic.202500048
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l54kh
title: CCDC 2388226: Experimental Crystal Structure Determination

description: Related Article: Emilie Delahaye, Marie Noelle Lalloz-Vogel, Carine Duhayon, Jean-Pascal Sutter|2024|Eur.J.Inorg.Chem.|28|e202500048|doi:10.1002/ejic.202500048
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2mggdz
title: CCDC 2426971: Experimental Crystal Structure Determination

description: Related Article: Haozhe Dong, Xuejie Wang, Pingsen Shi, Nian Chen, Zhiqiang Zhang, Jia Yan, Aiwen Lei, Hong Yi|2025|J.Am.Chem.Soc.|147|29423|doi:10.1021/jacs.5c09431
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2n08hg
title: CCDC 2443125: Experimental Crystal Structure Determination

description: Related Article: Daniel J. SantaLucia, Laxmi Devkota, Sergey V. Lindeman, Andrew Ozarowski, J. Krzystek, Mykhaylo Ozerov, Samuel M. Greer, Daniel C. Cummins, Klaus H. Theopold, Mihail Atanasov, Joshua Telser, Adam T. Fiedler|2025|Inorg.Chem.|64|16135|doi:10.1021/acs.inorgchem.5c02691
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ng5z9
title: CCDC 2456501: Experimental Crystal Structure Determination

description: Related Article: Zainab Haidar Ahmad, Marie Cordier, Daoud Naoufal, Christophe Darcel|2025|Dalton Trans.|54|12135|doi:10.1039/D5DT01302J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ng60c
title: CCDC 2456502: Experimental Crystal Structure Determination

description: Related Article: Zainab Haidar Ahmad, Marie Cordier, Daoud Naoufal, Christophe Darcel|2025|Dalton Trans.|54|12135|doi:10.1039/D5DT01302J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ng61d
title: CCDC 2456503: Experimental Crystal Structure Determination

description: Related Article: Zainab Haidar Ahmad, Marie Cordier, Daoud Naoufal, Christophe Darcel|2025|Dalton Trans.|54|12135|doi:10.1039/D5DT01302J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ng62f
title: CCDC 2456504: Experimental Crystal Structure Determination

description: Related Article: Zainab Haidar Ahmad, Marie Cordier, Daoud Naoufal, Christophe Darcel|2025|Dalton Trans.|54|12135|doi:10.1039/D5DT01302J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.57903/uj/qsspll
title: Ho et al. PLOS Computational Biology 2024 - research data

description: Source data for Figs. 1-8 and Figs. S1-S8 published in Ho et al, PLOS Computational Biology, 2024. The short description is provided within the data file. The detailed description of data is provided within the publication.