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In this study, we address the limitations of existing approaches for hematoxylin and eosin-stained muscle fibers by manually and semiautomatically labeling over 660\u00a0000 muscle fibers to create a large dataset. Subsequently, an automated image segmentation and quantification tool named MyoV is designed using mask regions with convolutional neural networks and a residual network and feature pyramid network as the backbone network. This design enables the tool to allow muscle fiber processing with different sizes and ages. MyoV, which achieves impressive detection rates of 0.93\u20130.96 and precision levels of 0.91\u20130.97, exhibits a superior performance in quantification, surpassing both manual methods and commonly employed algorithms and software, particularly for whole slide images (WSIs). Moreover, MyoV is proven as a powerful and suitable tool for various species with different muscle development, including mice, which are a crucial model for muscle disease diagnosis, and agricultural animals, which are a significant meat source for humans. Finally, we integrate this tool into visualization software with functions, such as segmentation, area determination and automatic labeling, allowing seamless processing for over 400\u00a0000 muscle fibers within a WSI, eliminating the model adjustment and providing researchers with an easy-to-use visual interface to browse functional options and realize muscle fiber quantification from WSIs.<\/jats:p>","DOI":"10.1093\/bib\/bbad528","type":"journal-article","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T18:12:01Z","timestamp":1706206321000},"source":"Crossref","is-referenced-by-count":13,"title":["MyoV: a deep learning-based tool for the automated quantification of muscle fibers"],"prefix":"10.1093","volume":"25","author":[{"given":"Shuang","family":"Gu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University , Beijing 100193, China"},{"name":"National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University , Beijing 100193, China"},{"name":"Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University , Beijing, 100193, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoliang","family":"Wen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University , Beijing 100193, China"},{"name":"National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University , Beijing 100193, China"},{"name":"Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University , Beijing, 100193, China"},{"name":"Sanya Institute of China Agricultural University , Hainan 572025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Hefei University of Technology , Anhui 230009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University , Beijing 100193, China"},{"name":"National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University , Beijing 100193, China"},{"name":"Department of Animal Genetics and Breeding, College of Animal Science and Technology, China 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