Pregled bibliografske jedinice broj: 1195588
A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning
A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning // Scientific Data, 9 (2022), 1; 222, 10 doi:10.1038/s41597-022-01328-z (međunarodna recenzija, članak, znanstveni)
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Naslov
A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning
Autori
Nagy, Eszter ; Janisch, Michael ; Hržić, Franko ; Sorantin, Erich ; Tschauner, Sebastian
Izvornik
Scientific Data (2052-4463) 9
(2022), 1;
222, 10
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
wrist fracture ; pronator quadratus sign ; AO classifiction ; soft tissue swelling ; metal implant ; osteopenia ; plaster cast ; bone Lesion ; subperiosteal bone formation
Sažetak
Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in computer vision algorithms, automated fracture detection has become a topic of research interest. This paper presents the GRAZPEDWRI-DX dataset containing annotated pediatric trauma wrist radiographs of 6, 091 patients, treated at the Department for Pediatric Surgery of the University Hospital Graz between 2008 and 2018. A total number of 10, 643 studies (20, 327 images) are made available, typically covering posteroanterior and lateral projections. The dataset is annotated with 74, 459 image tags and features 67, 771 labeled objects. We de-identified all radiographs and converted the DICOM pixel data to 16-Bit grayscale PNG images. The filenames and the accompanying text files provide basic patient information (age, sex). Several pediatric radiologists annotated dataset images by placing lines, bounding boxes, or polygons to mark pathologies like fractures or periosteal reactions. They also tagged general image characteristics. This dataset is publicly available to encourage computer vision research.
Izvorni jezik
Engleski
Znanstvena područja
Interdisciplinarne prirodne znanosti, Interdisciplinarne tehničke znanosti, Informacijske i komunikacijske znanosti
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- Social Science Citation Index (SSCI)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE