“Thyroid Lymph Node (Longitudinal)” is a preset AI auto-label model in the Langhui medical annotation platform. Default modality: Ultrasound (US). Region: Head and Neck. Type: Lesion. Batch inference outputs Mask or Contour drafts; drafts enter training sets only after revision and blind review. This page describes model capability and workflow — not a disease product and not in-stock case volume.
Head-and-neck imaging tasks usually cover thyroid and cervical structures. Attachment note: Thyroid-Lymph Node-Longitudinal-2D
One system, three acceptance questions. Answers must map to the status machine.
Check windowing and anatomy before accepting the AI contour for Thyroid Lymph Node (Longitudinal). Then revise pixels, continuity, and negatives.
Reproducibility first: DICOM in, model version v1.0, Mask/Contour out, MPR continuity, review status on labels.
Match task to Head and Neck / US, then confirm whether data leaves the hospital network. No diagnostic claims. No company-wide accuracy.
Same main path: manage → AI pre-label → refine → review → export.
Platform default path remains CT / MR / PET · DICOM. This list modality is US; US/MG entries need project assessment. Endoscopy video, pathology WSI, and clinical NLP are out of default scope.
Task assignment and status (to-annotate → annotated → pending review → approved) stay visible. AI output for Thyroid Lymph Node (Longitudinal) is a draft by default.
High-risk or lesion tasks can force final review. Dice/Kappa rules are defined by the project — not a company-wide accuracy score.
After sample review confirms fit, agree batch, license, and export formats. Public pages do not provide diagnosis or registration promises.
“Thyroid Lymph Node (Longitudinal)” is a preset AI auto-label model name. The platform has 186 preset models, not 186 disease products. Project fit depends on task definition, authorization, and the data card.
No. Model output is a draft. Revision plus single- or multi-blind review is required before export. Pre-labeling is not diagnosis and does not promise sensitivity or Dice.
Exports should align images, contours, guideline version, model version (v1.0), and review status. Use MPR for 3D continuity. Version changes go to the next dataset freeze.
Confirm whether data leaves the network, upload de-identification, and permissions. Then pilot: ingest → trigger Thyroid Lymph Node (Longitudinal) → revise → blind review → export. YY/T 1833.3 is educational alignment only.
Bring anatomy, modality, and on-prem needs to request a Thyroid Lymph Node (Longitudinal) sample review.