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Recent Advances in Bioimage Analysis Methods for Detecting Skeletal Deformities in Biomedical and Aquaculture Fish Species.
Kumar, Navdeep; Marée, Raphaël; Geurts, Pierre; Muller, Marc.
Afiliación
  • Kumar N; Department of Computer Science and Electrical Engineering, Montefiore Institute, University of Liège, 4000 Liège, Belgium.
  • Marée R; Department of Computer Science and Electrical Engineering, Montefiore Institute, University of Liège, 4000 Liège, Belgium.
  • Geurts P; Department of Computer Science and Electrical Engineering, Montefiore Institute, University of Liège, 4000 Liège, Belgium.
  • Muller M; Laboratory for Organogenesis and Regeneration (LOR), GIGA Institute, University of Liège, 4000 Liège, Belgium.
Biomolecules ; 13(12)2023 12 14.
Article en En | MEDLINE | ID: mdl-38136667
ABSTRACT
Detecting skeletal or bone-related deformities in model and aquaculture fish is vital for numerous biomedical studies. In biomedical research, model fish with bone-related disorders are potential indicators of various chemically induced toxins in their environment or poor dietary conditions. In aquaculture, skeletal deformities are affecting fish health, and economic losses are incurred by fish farmers. This survey paper focuses on showcasing the cutting-edge image analysis tools and techniques based on artificial intelligence that are currently applied in the analysis of bone-related deformities in aquaculture and model fish. These methods and tools play a significant role in improving research by automating various aspects of the analysis. This paper also sheds light on some of the hurdles faced when dealing with high-content bioimages and explores potential solutions to overcome these challenges.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Óseas / Inteligencia Artificial Límite: Animals Idioma: En Revista: Biomolecules Año: 2023 Tipo del documento: Article País de afiliación: Bélgica

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Óseas / Inteligencia Artificial Límite: Animals Idioma: En Revista: Biomolecules Año: 2023 Tipo del documento: Article País de afiliación: Bélgica