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Article

Automated phenotyping of mammary gland tissues using computer vision systems.

Journal of dairy science - 1 Jul 2026

Casella E, Menezes G L, Vang A L, Frizzarini W S, Cunha T, Rosa G J M, Hernandez L L, Dórea J R R

Abstract excerpt

Quantifying mammary gland tissue composition is crucial for understanding growth patterns and future lactation potential in dairy heifers, yet conventional histological analysis is labor-intensive and time-consuming. This study developed an automated phenotyping framework using deep learning-based semantic segmentation to classify tissues in mammary gland biopsies collected from Holstein heifers at 10, 26, 39,...

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Identifiers

PMID: 41850381
DOI: 10.3168/jds.2025-28114

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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