Editing Medical Segmentation (section)

== <span style="color: #FFFFFF;">Creating</span> ==
Deploying medical segmentation AI:
# Start with nnU-Net — it auto-configures and routinely beats custom models.
# Data: minimum 30–50 annotated cases; more for rare structures/pathology.
# Multi-site validation: test on data from different hospitals/scanners than training.
# Clinical integration: DICOM RT-STRUCT output for radiotherapy; FHIR integration for EHR.
# QA workflow: every AI segmentation reviewed and approved by radiologist before clinical use.
# Regulatory: FDA 510(k) or CE Mark required for clinical deployment in US/EU; document training data, performance, and bias analysis.

[[Category:Artificial Intelligence]]
[[Category:Medical Imaging]]
[[Category:Segmentation]]
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