The Ankle Fracture dataset includes radiological images for diagnosing and evaluating ankle fractures. The dataset focuses on X-ray imaging, providing annotations for fracture identification, classification, and severity grading.

Keywords: Ankle fractures, Radiology, Annotations, Medical imaging, AO/OTA.

Sample images

Sample images with reduced image quality. Please click to preview.

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Dataset information

Short name	ANKLEFX
Origin	Clinical
Cite as	Jakub Olczak, Filip Emilson, Ali Razavian, Tone Antonsson, Andreas Stark, and Max Gordon (2024) Annotated radiographs of ankle fractures for research doi:10.23698/aida/anklefx [BibTeX format] @misc{ olczak_2024_anklefx, author = { Jakub Olczak and Filip Emilson and Ali Razavian and Tone Antonsson and Andreas Stark and Max Gordon }, title = { Annotated radiographs of ankle fractures for research }, year = 2024, publisher = { AIDA }, doi = { 10.23698/aida/anklefx }, howpublished = { Available: AIDA Data Hub }, url = { https://datahub.aida.scilifelab.se/10.23698/aida/anklefx } }
Field	Radiology
Organ	Ankle
Age span	15+
Title	Annotated radiographs of ankle fractures for research
Author	Jakub Olczak Filip Emilson Ali Razavian Tone Antonsson Andreas Stark Max Gordon
Year	2024
DOI	doi:10.23698/aida/anklefx
Status	Completed
Version	1.0.0
Scans	1751
Annotations	400
Size	3.22GB
Resolution
Modality	CR
Scanner
Stain
Phase
References	Olczak J, Prijs J, IJpma F, Wallin F, Akbarian E, Doornberg J, et al. External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classification. BMC Musculoskelet Disord. 2024 Oct 4;25(1):788. Olczak J, Emilson F, Razavian A, Antonsson T, Stark A, Gordon M. Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification. Acta Orthopaedica. 2021 Jan 2;92(1):102–8.
Copyright	Copyright 2021 Karolinska Institutet, Max Gordon
Access	Available under the following licenses, described in the License section below. Controlled access Free for use in legal and ethical medical diagnostics research. AIDA BY license Free for use within AIDA with attribution.

Annotation

Annotations are manually created and validated by clinical experts, including fracture classification, severity grading, and localization markers on X-rays.

License

Controlled access

Free for use in legal and ethical medical diagnostics research.

To request access to the dataset, use the Apply for access button below. Note that the recipient researcher must hold at least a PhD degree in a relevant field and that the applicant should be an authorized signatory who can legally enter into data sharing agreements on the behalf of the institution.

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AIDA BY license

Copyright 2021 Karolinska Institutet, Max Gordon

Permission to use, copy, modify, and/or distribute this data within Analytic Imaging Diagnostics Arena (AIDA) for the purpose of medical diagnostics research with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies, and that publications resulting from the use of this data cite the following works:

Jakub Olczak, Filip Emilson, Ali Razavian, Tone Antonsson, Andreas Stark, and Max Gordon (2024) Annotated radiographs of ankle fractures for research doi:10.23698/aida/anklefx.

Olczak J, Prijs J, IJpma F, Wallin F, Akbarian E, Doornberg J, et al. External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classification. BMC Musculoskelet Disord. 2024 Oct 4;25(1):788.

Olczak J, Emilson F, Razavian A, Antonsson T, Stark A, Gordon M. Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification. Acta Orthopaedica. 2021 Jan 2;92(1):102–8.

THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS DATA.