ArticleBMC veterinary research2022
A method for labelling lesions for machine learning and some new observations on osteochondrosis in computed tomographic scans of four pig joints.
Article in BMC veterinary research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Automated identification of bones and joints in whole-body CT-scan images of pigs.Journal of animal science · 2026Article
- Science-in-brief: Recent advances in failure of the blood supply to growth cartilage, osteochondrosis and developmental orthopaedic disease.Equine veterinary journal · 2025Article
- Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review.Veterinary medicine and science · 2025Review
- Classification of racehorse limb radiographs using deep convolutional neural networks.Veterinary record open · 2023Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundOsteochondrosis is a major cause of leg weakness in pigs. Selection against osteochondrosis is currently based on manual scoring of computed tomographic (CT) scans for the presence of osteochondrosis manifesta lesions. It would be advantageous if osteochondrosis could be diagnosed automatically, through artificial intelligence methods using machine learning. The aim of this study was to describe a method for labelling articular osteochondrosis lesions in CT scans of four pig joints to guide development of future machine learning algorithms, and to report new observations made during the labelling process. The shoulder, elbow, stifle and hock joints were evaluated in CT scans of 201 pigs.
resultsSix thousand two hundred fifty osteochondrosis manifesta and cyst-like lesions were labelled in 201 pigs representing a total volume of 211,721.83 mm
conclusionsThe described labelling method is an important step towards developing a machine learning algorithm that will enable automated diagnosis of osteochondrosis manifesta and cyst-like lesions. Both lesion number and volume should be considered during breeding selection. The apparent inverse relationship between lesion number and volume warrants further investigation.
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