A deep learning-based automated image analysis for histological evaluation of broiler pectoral muscle

被引:2
|
作者
Dayan, Jonathan [1 ]
Goldman, Noam [2 ]
Waiger, Daniel [3 ]
Melkman-Zehavi, Tal [1 ]
Halevy, Orna [1 ]
Uni, Zehava [1 ]
机构
[1] Hebrew Univ Jerusalem, Robert H Smith Fac Agr Food & Environm, Dept Anim Sci, IL-7610001 Rehovot, Israel
[2] Hebrew Univ Jerusalem, Robert H Smith Fac Agr Food & Environm, Koret Sch Vet Med, IL-7610001 Rehovot, Israel
[3] Hebrew Univ Jerusalem, Robert H Smith Fac Agr Food & Environm, Ctr Scienti Imaging, IL-7610001 Rehovot, Israel
关键词
automated image analysis; histology; breast muscle; broiler; chicken; FED REPRESENTATIVE 1957; THERMAL MANIPULATIONS; GROWTH; PROLIFERATION; PERFORMANCE; YIELD;
D O I
10.1016/j.psj.2023.102792
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Global market demand for chicken breast muscle with high yield and quality, together with the high incidence rate of breast muscle abnormalities in recent years highlights the need for tools that can pro-vide a rapid and precise evaluation of breast muscle development and morphology. In this study, we used a novel deep learning-based automated image analysis workflow combining Fiji (ImageJ) with Cellpose and MorphoLibJ plugins to generate an automated diameter and cross-sectional area quantification for broiler breast muscle. We compared data of myofiber diameter from 14-day-old broiler chicks, generated either by manual analysis or by automated analysis. Comparison between manual and automated analysis methods exhibited a striking accuracy rate of up to 99.91%. Moreover, the automated analysis method was much faster. When the automated analysis method was implemented on 84 breast muscle cross-section images it characterized 59,128 myofibers within 4.2 h, while manual analysis of 27 breast muscle cross-section images enabled analysis of 17,333 myofibers in 54 h. The automated image analy-sis method was also more productive, producing data sets of both diameter and cross-sectional area at an 80-fold higher rate than the manual analysis (26,279 vs. 321 data sets per hour, respectively). In order to demon-strate the ability of this automated image analysis tool to detect differences in breast muscle histomorphology, we applied it on cross sections from chicks of control and in ovo feeding group, injected with a methionine source [2-hydroxy-4-(methylthio) butanoic calcium salt (HMTBa)], known to effect skeletal muscle histomor-phology. Analysis was performed on 19,807 myofibers from the control group and 21,755 myofibers from the HMTBa group and was completed in less than 1 h. The clear advantages of this automated image analysis work-flow characterized by high precision, high speed, and high productiveness demonstrate its potential to be implemented as a reproducible and readily adaptable research or diagnostic tool for chicken breast muscle development and morphology.
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页数:6
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