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A vendor-agnostic, PACS integrated, and DICOMcompatible software-server pipeline for testing segmentation algorithms within the clinical radiology workflow
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...
Autores principales: | Zhang, Lei, LaBelle, Wayne, Unberath, Mathias, Chen, Haomin, Hu, Jiazhen, Li, Guang, Dreizin, David |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
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 |
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