A vendor-agnostic, PACS integrated, and DICOMcompatible software-server pipeline for testing segmentation algorithms within the clinical radiology workflow

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BACKGROUND: Reproducible approaches are needed to bring AI/ML for medical image analysis closer to the bedside. Investigators wishing to shadow test cross-sectional medical imaging segmentation algorithms on new studies in real-time will benefit from simple tools that integrate PACS with on-premises...

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Detalles Bibliográficos
Autores principales: Zhang, Lei, LaBelle, Wayne, Unberath, Mathias, Chen, Haomin, Hu, Jiazhen, Li, Guang, Dreizin, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168465/
https://www.ncbi.nlm.nih.gov/pubmed/37163064
http://dx.doi.org/10.21203/rs.3.rs-2837634/v1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168465/
https://www.ncbi.nlm.nih.gov/pubmed/37163064
http://dx.doi.org/10.21203/rs.3.rs-2837634/v1

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