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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Lei Zhang, Wayne LaBelle, Mathias Unberath, Haomin Chen, Jiazhen Hu, Guang Li, David Dreizin
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Frontiers Media S.A. 2023-10-01
Sarja:	Frontiers in Medicine
Aiheet:	artificial intelligence deep learning nnU-net PACS DICOM OHIF
Linkit:	https://www.frontiersin.org/articles/10.3389/fmed.2023.1241570/full
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