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2026, Vol: 16, Issue: 6
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Short Communication


Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning

Susumu Iwaide, Kumiko Kimura, Ryo Sugiura, Yu Oishi, Tomoyuki Shibahara.


Abstract
Background:
Liver lesions occur in livestock due to various causes, including infection and poisoning. Liver diseases can affect multiple organs, making accurate and efficient pathological diagnosis essential. Therefore, a model capable of automatically classifying various lesions could assist in diagnosis.

Aim:
This study aimed to classify common lesions in bovine livers—lymphoma, necrosis, and fibrosis—using deep learning based on convolutional neural network to develop a potential pathological diagnosis support model.

Methods:
We prepared 10 bovine cases for 4 groups: lymphoma, necrosis, fibrosis, and normal liver. After scanning the slides as whole slide images, we divided the images into patches and collected 50 patches per slide containing the target tissue. The patches were split into 2 groups: training cross-validation (80%) and test (20%) groups. A DenseNet-based convolutional neural network was trained via cross-validation and its performance was evaluated with the test set.

Results:
The model achieved a classification accuracy of 84.5% on the test data with an average F1-score of 83.5% across the four labels. The precision and recall for each label were 92.6% and 50% (lymphoma), 95.8% and 92.0% (necrosis), 89.8% and 97.0% (fibrosis), and 69.7% and 99.0% (normal liver), respectively.

Conclusion:
Image classification using a deep learning model based on a convolutional neural network showed promising performance for classifying common lesions in bovine livers, particularly necrosis and fibrosis. However, further improvement is required for reliable lymphoma detection.

Key words: Cattle; Convolutional neural network; Digital pathology; Liver; Machine learning.


 
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How to Cite this Article
Pubmed Style

Iwaide S, Kimura K, Sugiura R, Oishi Y, Shibahara T. Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. Open Vet. J.. 2026; 16(5): 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65

Web Style

Iwaide S, Kimura K, Sugiura R, Oishi Y, Shibahara T. Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. https://www.openveterinaryjournal.com/?mno=301293 [Access: June 10, 2026]. doi:10.5455/OVJ.2026.v16.i5.65

AMA (American Medical Association) Style

Iwaide S, Kimura K, Sugiura R, Oishi Y, Shibahara T. Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. Open Vet. J.. 2026; 16(5): 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65


Vancouver/ICMJE Style

Iwaide S, Kimura K, Sugiura R, Oishi Y, Shibahara T. Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. Open Vet. J.. (2026), [cited June 10, 2026]; 16(5): 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65


Harvard Style

Iwaide, S., Kimura, . K., Sugiura, . R., Oishi, . Y. & Shibahara, . T. (2026) Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. Open Vet. J., 16 (5), 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65


Turabian Style

Iwaide, Susumu, Kumiko Kimura, Ryo Sugiura, Yu Oishi, and Tomoyuki Shibahara. 2026. Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. Open Veterinary Journal, 16 (5), 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65


Chicago Style

Iwaide, Susumu, Kumiko Kimura, Ryo Sugiura, Yu Oishi, and Tomoyuki Shibahara. "Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning." Open Veterinary Journal 16 (2026), 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65


MLA (The Modern Language Association) Style

Iwaide, Susumu, Kumiko Kimura, Ryo Sugiura, Yu Oishi, and Tomoyuki Shibahara. "Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning." Open Veterinary Journal 16.5 (2026), 3255-3263. Print. doi:10.5455/OVJ.2026.v16.i5.65


APA (American Psychological Association) Style

Iwaide, S., Kimura, . K., Sugiura, . R., Oishi, . Y. & Shibahara, . T. (2026) Differentiation of common histological lesions in bovine liver using convolutional neural network-based deep learning. Open Veterinary Journal, 16 (5), 3255-3263. doi:10.5455/OVJ.2026.v16.i5.65


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