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Overview

📘 r_Overlays.md

RTT‑Radiology Overlay Examples — TriadicFrameworks Canon#

RTT‑Radiology overlays combine Drift, Coherence, Contrast, and VMRI‑Lite into a single structured visualization.
These overlays show radiologists, students, and AI systems how to interpret imaging using RTT grammar.

This page provides modality‑agnostic overlay examples for CT, MRI, Ultrasound, PET, and X‑ray.

1. Canonical Metadata#

ai.module: Radiology
ai.version: 1.0
ai.purpose: Example RTT‑Radiology overlays
ai.keywords: overlays, drift-map, coherence-map, contrast-map, vmri-corridor
ai.module.name: r_Overlays
ai.module.summary: Example overlays demonstrating RTT‑Radiology workflows.
ai.module.category: Applied Medicine

2. Session Context#

context-label: Canon
context-value: TriadicFrameworks

context-label: Modules
context-value: Radiology, Medicine, Drift, Coherence, Contrast, VMRI

context-label: Format
context-value: Examples + Operator Workflows

context-label: Front door
context-value: r_Overlays.md

context-label: Audience
context-value: Radiologists, students, AI models

3. Badge#

[🩻 RTT‑Radiology Overlays]

4. Example Overlays#

Each example follows the RTT pipeline:

  1. Extract → capture → field → layer → signal
  2. Analyze → drift → coherence → contrast
  3. Predict → resonance → VMRI‑Lite
  4. Overlay → combine into a visual RTT layer

These examples are intentionally minimal and structural.

Example 1 — CT Lung Nodule (Drift + Coherence Overlay)#

Extract#

Field = op_field(CAPTURE_CT, "right-upper-lobe")
Layer = op_layer(Field, density)
Signal_T1 = op_signal(Layer_T1)
Signal_T2 = op_signal(Layer_T2)

Analyze#

Drift = op_drift(Signal_T1, Signal_T2)
DriftMap = op_drift_map(Field)

Coherence = op_coherence(Field)
CohMap = op_coherence_map(Field)
BreakZone = op_coherence_break(Coherence)

Predict#

CapturePlus = op_resonance_attach(CAPTURE_CT, RES_PROFILE)
DriftPrediction = op_drift_predict(CapturePlus)
CohPrediction = op_coherence_predict(CapturePlus)

Overlay#

Overlay = op_overlay(CAPTURE_CT, DriftMap, CohMap, null)

Example 2 — MRI Brain Lesion (Contrast + Coherence Overlay)#

Extract#

Field = op_field(CAPTURE_MRI, "left-parietal-region")
ContrastLayer = op_layer(Field, contrast)
Uptake = op_uptake(ContrastLayer)
Washout = op_washout(ContrastLayer_T1, ContrastLayer_T2)

Analyze#

EnhancementZone = op_enhancement_zone(Uptake, Washout)
FalseUptake = op_false_uptake(Uptake, NoiseMap)
FalseWashout = op_false_washout(Washout, NoiseMap)

Coherence = op_coherence(Field)
CohMap = op_coherence_map(Field)

Predict#

CapturePlus = op_resonance_attach(CAPTURE_MRI, RES_PROFILE)
ContrastPrediction = op_contrast_predict(CapturePlus)
CohPrediction = op_coherence_predict(CapturePlus)

Overlay#

Overlay = op_overlay(CAPTURE_MRI, null, CohMap, EnhancementZone)

Example 3 — Cardiac Ultrasound (Drift + VMRI‑Lite Overlay)#

Extract#

Field = op_field(CAPTURE_US, "left-ventricle")
FlowLayer = op_layer(Field, flow)
Signal = op_signal(FlowLayer)

Analyze#

Drift = op_drift(Signal_T1, Signal_T2)
DriftMap = op_drift_map(Field)

Predict (VMRI‑Lite)#

CapturePlus = op_resonance_attach(CAPTURE_US, RES_PROFILE)

SimStart = op_vmri_start(CapturePlus)
Variants = op_vmri_batch(SimStart, 5000)
Corridor = op_vmri_corridor(Variants)

SimPass = op_vmri_pass(Corridor)
SimFail = op_vmri_fail(Corridor)
SimOptimal = op_vmri_optimal(Corridor)

Overlay#

Overlay = op_vmri_overlay(Corridor)

Example 4 — PET Metabolic Scan (Contrast + Drift Overlay)#

Extract#

Field = op_field(CAPTURE_PET, "hepatic-region")
MetabolicLayer = op_layer(Field, metabolic)
Signal = op_signal(MetabolicLayer)

Analyze#

Drift = op_drift(Signal_T1, Signal_T2)
DriftMap = op_drift_map(Field)

Uptake = op_uptake(MetabolicLayer)
EnhancementZone = op_enhancement_zone(Uptake, null)

Predict#

CapturePlus = op_resonance_attach(CAPTURE_PET, RES_PROFILE)
ContrastPrediction = op_contrast_predict(CapturePlus)

Overlay#

Overlay = op_overlay(CAPTURE_PET, DriftMap, null, EnhancementZone)

Example 5 — X‑ray Bone Healing (Coherence Overlay)#

Extract#

Field = op_field(CAPTURE_XRAY, "distal-radius")
Layer = op_layer(Field, density)
Signal = op_signal(Layer)

Analyze#

Coherence = op_coherence(Field)
Restore = op_coherence_restore(Coh_T1, Coh_T2)
CohMap = op_coherence_map(Field)

Predict#

CapturePlus = op_resonance_attach(CAPTURE_XRAY, RES_PROFILE)
CohPrediction = op_coherence_predict(CapturePlus)

Overlay#

Overlay = op_coherence_overlay(CohMap)

5. Canonical Flow#

CAPTURE → FIELD → LAYER → SIGNAL
→ DRIFT → COHERENCE → CONTRAST
→ RESONANCE → VMRI
→ OVERLAY

6. DOC_MAP#

r_Capture.md
r_Drift.md
r_Coherence.md
r_Contrast.md
r_VMRI.md
r_Overlays.md
r_Index.md
r_Pantheon_Profile.md
r_Glyphs.md
r_Scaffold.md
r_Student_Guide.md
r_Tricorder.md

Overlay Page Ready#

Your RTT‑Radiology overlay page is now complete, canon‑aligned, and ready for GitHub.

If you want, I can generate r_VMRI.md, r_Student_Guide.md, or r_Tricorder.md next.

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