دورية أكاديمية

Research Note: Prospects for early detection of breast muscle myopathies by automated image analysis

التفاصيل البيبلوغرافية
العنوان: Research Note: Prospects for early detection of breast muscle myopathies by automated image analysis
المؤلفون: Jonathan Dayan, Noam Goldman, Orna Halevy, Zehava Uni
المصدر: Poultry Science, Vol 103, Iss 6, Pp 103680- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
المجموعة: LCC:Animal culture
مصطلحات موضوعية: image analysis, automated myopathy detection, histology, breast muscle, broiler chicken, Animal culture, SF1-1100
الوصف: ABSTRACT: White Striping (WS), Wooden Breast (WB), and Spaghetti Meat (SM) are documented breast muscle myopathies (BMM) affecting broiler chickens’ product quality, profitability and welfare. This study evaluated the efficacy of our newly developed deep learning-based automated image analysis tool for early detection of morphometric parameters related to BMM in broiler chickens. Male chicks were utilized, and muscle samples were collected on d 14 of rearing. Histological procedures, including microscopic scoring, blood vessel count, and collagen quantification, were conducted. A previous study demonstrated our automated image analysis as a reliable tool for evaluating myofiber size, conforming with manual histological measurements. A threshold for BMM detection was established by normalizing and consolidating myofiber diameter and area into a unified metric based on automated measurements, also termed as “relative myofiber size value.” Results show that severe myopathy broilers consistently exhibited lower relative myofiber size values, effectively detecting myopathy severity. Our study, aimed as proof of concept, underscores the potential of our automated image analysis tool as an early detection method for BMM.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 0032-5791
Relation: http://www.sciencedirect.com/science/article/pii/S003257912400261X; https://doaj.org/toc/0032-5791
DOI: 10.1016/j.psj.2024.103680
URL الوصول: https://doaj.org/article/4daec4a5b0fc4100b6eb9e70b56f2e5f
رقم الأكسشن: edsdoj.4daec4a5b0fc4100b6eb9e70b56f2e5f
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:00325791
DOI:10.1016/j.psj.2024.103680