aceSheep Pulmonary Image Recognition (SPIRO): an explainable deep learning framework for macroscopic assessment of ovine pulmonary lesions
Accurate detection and classification of pulmonary diseases in sheep are critical for ensuring animal welfare, food safety, and effective disease surveillance in abattoir settings. In this study, we propose a two-stage, explainable, histopathology-informed deep learning framework for the automated classification of ovine lung lesions. The dataset comprises 1,052 sheep lung images, annotated through a dual-level diagnostic process involving macroscopic inspection and histopathological confirmation, and classified…
A YOLOv11 plus EfficientNetB0 pipeline classified ovine lungs as healthy, inflammatory, or neoplastic with 90% test accuracy, supporting objective post-mortem assessment for abattoir surveillance.
The source describes feasibility rather than deployment, and performance was noticeably lower for healthy and inflammatory lungs than for neoplastic ones.
Evidence
- Peer-reviewedThe Veterinary Journal2026-10-14
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Truvace Impact Record TRV-2026-1919, v1: “Sheep Pulmonary Image Recognition (SPIRO): an explainable deep learning framework for macroscopic assessment of ovine pulmonary lesions.” Truvace, 2026-10-19. /record/TRV-2026-1919 (accessed at citation time). sha256 e960c17de4c72c4f…
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