AI AUTO-LABEL · PRESET MODEL

Langhui Right Lung AI Medical Imaging Annotation Platform

“Right Lung” is a preset AI auto-label model in the Langhui medical annotation platform. Default modality: MR / MRI. Region: Chest. Type: Organ / structure. 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.

Modality MR / MRI Region Chest Organ / structure Version v1.0

Model snapshot

Chest imaging tasks usually cover lung, mediastinum, and thoracic structures. Attachment note: Preset model in the Langhui medical annotation platform. Triggers AI auto-labeling.

Right LungModel name
MRList modality
ChestAnatomy region
Organ / structureLabel type

How three expert roles accept “Right Lung”

One system, three acceptance questions. Answers must map to the status machine.

Annotation expert

Check windowing and anatomy before accepting the AI contour for Right Lung. Then revise pixels, continuity, and negatives.

  • Draft vs final kept apart
  • Disputes go to multi-blind review
  • Export only reviewed results

Algorithm engineer

Reproducibility first: DICOM in, model version v1.0, Mask/Contour out, MPR continuity, review status on labels.

  • Batch inference by selecting Right Lung
  • Failures return to fine labeling
  • Exports align with frozen guideline versions

Industry / procurement

Match task to Chest / MR, then confirm whether data leaves the hospital network. No diagnostic claims. No company-wide accuracy.

  • On-prem and training-set paths can be separate contracts
  • YY/T 1833.3 is process reference only
  • No HIPAA claim; no efficacy promise

Run Right Lung on the Langhui platform

Same main path: manage → AI pre-label → refine → review → export.

01DICOM ingest & de-ID
02Select “Right Lung” auto-label
03Human revise / MPR check
04Single- or multi-blind review
05Export after approved

Platform default path remains CT / MR / PET · DICOM. This list modality is MR; US/MG entries need project assessment. Endoscopy video, pathology WSI, and clinical NLP are out of default scope.

How it connects to the business system

Annotation workbench

Task assignment and status (to-annotate → annotated → pending review → approved) stay visible. AI output for Right Lung is a draft by default.

QC & final review

High-risk or lesion tasks can force final review. Dice/Kappa rules are defined by the project — not a company-wide accuracy score.

Delivery & buying

After sample review confirms fit, agree batch, license, and export formats. Public pages do not provide diagnosis or registration promises.

FAQ

Is Right Lung a disease or a model?

“Right Lung” 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.

Can AI auto-label results be gold standard?

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.

How do algorithm teams reproduce Right Lung labels?

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.

How should hospitals assess Right Lung deployment?

Confirm whether data leaves the network, upload de-identification, and permissions. Then pilot: ingest → trigger Right Lung → revise → blind review → export. YY/T 1833.3 is educational alignment only.

Next step

Bring anatomy, modality, and on-prem needs to request a Right Lung sample review.