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

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

BackgroundReproducible 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 i...

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Bibliographic Details
Main Authors: Lei Zhang, Wayne LaBelle, Mathias Unberath, Haomin Chen, Jiazhen Hu, Guang Li, David Dreizin
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Medicine
Subjects:
artificial intelligence
deep learning
nnU-net
PACS
DICOM
OHIF
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1241570/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2023.1241570/full

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