Anatomy segmentation in laparoscopic surgery: comparison of machine learning and human expertise – an experimental study

BACKGROUND: Lack of anatomy recognition represents a clinically relevant risk in abdominal surgery. Machine learning (ML) methods can help identify visible patterns and risk structures; however, their practical value remains largely unclear. MATERIALS AND METHODS: Based on a novel dataset of 13 195...

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Detalles Bibliográficos
Autores principales: Kolbinger, Fiona R., Rinner, Franziska M., Jenke, Alexander C., Carstens, Matthias, Krell, Stefanie, Leger, Stefan, Distler, Marius, Weitz, Jürgen, Speidel, Stefanie, Bodenstedt, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583931/
https://www.ncbi.nlm.nih.gov/pubmed/37526099
http://dx.doi.org/10.1097/JS9.0000000000000595

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583931/
https://www.ncbi.nlm.nih.gov/pubmed/37526099
http://dx.doi.org/10.1097/JS9.0000000000000595

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