MEDICAL_IMAGING_AI
X-ray&CT AI
Production-grade segmentation and classification with MONAI Label, MONAI Deploy, and OHIF v3.11
2024–2025 Stack
•
DICOM-Native
•
Viewer-Ready
LIVE_PROCESSING
1847
studies processed
104
anatomies segmented
4.2s
segmentation time
MONAI Label
v2024.11
MONAI Deploy SDK
v3.2.0
OHIF Viewer
v3.11
Research AUCs without DICOM I/O don't make it to the reading room
Hospitals need workflow-integrated AI, not one-shot demos
1
Ingest DICOM from PACS/VNA
[Required]
2
Fast, reproducible on-prem inference
[Required]
3
Reviewable overlays (SEG/RTSTRUCT)
[Required]
4
Provenance & audit logging
[Required]
5
Scale to thousands of studies/day
[Required]
Production stack with MONAI Label for serving, MONAI Deploy SDK for packaging, and OHIF v3.11 for in-viewer overlays
STACK
2024–2025 Releases
Open, Current, Clinic-Ready
1
MONAI Label
v2024.11 (Nov 22, 2024)
Whole-Body CT (104 anatomies in ~4s)
Keycloak multi-user RBAC
2
MONAI Deploy App SDK
v3.0.0 (Apr 2025) / v3.2.0 (Sep 2025)
Holoscan v3 alignment
PyTorch 2.7–2.8 / CUDA ≥12.6
3
OHIF Viewer
v3.10 / v3.11 (2025)
WebGPU GrowCut (one-click 3D)
DICOM Labelmap Segmentations IOD
Clinic-Ready Flow
PACS/VNA
→
Informatics Gateway
C-STORE/C-MOVE, FHIR links
↓
MONAI Deploy Orchestrator
App SDK v3.x • MAP routing
↓
MONAI Label Server
GPU • RBAC via Keycloak
• CT bundles (Whole-Body 104 anatomies)
• X-ray classifiers / 2D segmenters
↓
DICOM SEG / RTSTRUCT / Labelmap
+ JSON metadata
→
OHIF v3.11 VIEWER
Gateway handles DICOM I/O • App SDK binds series → inputs/outputs • OHIF renders overlays with WebGPU tools
Model Portfolio
Curated for X-ray & CT
1
MONAI Label Whole-Body CT
CLASSES
104 anatomies
SPEED/INFO
~4 seconds
USE_CASE
Default coverage model for multi-organ CT
2
TotalSegmentator v2
CLASSES
≥117 classes
SPEED/INFO
SNOMED mappings
USE_CASE
Exhaustive anatomy list with clinical codes
3
nnU-Net v2
CLASSES
Site-specific
SPEED/INFO
Auto-config
USE_CASE
Task-adaptive fine-tuning for local protocols
4
SAM-Med2D
CLASSES
31 organs
SPEED/INFO
4.6M images trained
USE_CASE
Promptable 2D segmentation for X-ray & QA
Modalities & I/O
🏥
CT (3D)
PIPELINE
Import via Gateway → resample/normalize → model → DICOM SEG (preferred) or RTSTRUCT
VIEWER
OHIF 3.11 can load Labelmap for speed on big volumes
📷
X-ray (2D)
PIPELINE
Classify/triage → heatmap/contour to Secondary Capture or SEG for key regions
VIEWER
SAM-Med2D for promptable masks and reader QA
OHIF WebGPU GrowCut (v3.10)
Rapid edits directly in the viewer for one-click 3D segmentation
Case Blueprints
A
Chest CT — Lungs/Lobes/Airways + Nodule Assist
Speed quantification & review
01
PIPELINE
Series selection → Whole-Body CT or TotalSegmentator → lobe split, airway pruning → lung/lobe volumes → nodule candidates → SEG + JSON
VIEWER
OHIF shows masks and radiomics table; GrowCut for edits
TARGETS
Lung/lobe Dice ≥ 0.95/0.90 • P95 < 25s • >95% overlay acceptance
B
Abdomen CT — Liver/Pancreas/Spleen + Vessels
Planning support; consistent volumetry
02
PIPELINE
Multi-organ bundle + vessel centerlines → organ volumes, aortic diameter map → export RTSTRUCT for planning
VIEWER
Treatment planning system import
TARGETS
Organ Dice ≥ 0.90 • Centerline continuity > 98% • P95 < 40s
C
Chest X-ray — Triage + Explainability
Flag likely abnormal CXRs; interpretable regions
03
PIPELINE
Classifier → heatmap → prompt SAM-Med2D for ROI mask → SC or SEG back
VIEWER
OHIF for overlay review
TARGETS
AUC ≥ 0.92 on site validation • Overlay render < 2s
Performance & Rollout
PERFORMANCE_TARGETS
CT multi-organ
≤60s/study (batch)
Scale via GPU pools
X-ray triage
<1s classify
Heatmaps return first
Viewer overlay
Near-instant
Labelmap reduces latency
PACS→AI→PACS
≥99.5% success
Retries & back-pressure
ROLLOUT_TIMELINE
1–2
Connect PACS↔Gateway • 100-case golden set • Baseline Dice
3–4
Site tuning (spacing, windowing) • nnU-Net fine-tunes • OHIF workflow
5
Shadow deploy • Nightly batch • Reader feedback instrumented
6–8
Canary 10% • KPI gates (success, latency, Dice) • Scale
Packaging
Orchestration
Monitoring
Promotion
Not just models
the operational substrate
104
Anatomies Segmented
<4s
Whole-Body CT
99.5%
Success Rate
v3.11
OHIF Viewer
MONAI_LABEL_v2024.11
•
MONAI_DEPLOY_SDK_v3.2.0
•
OHIF_v3.11