Rayoscan AI Diagnostics

Model Families

Four branded AI models powering the Rayoscan diagnostic roadmap.

Each model family is designed for a specific radiology workflow — so teams can adopt the right lane first, then expand.

OPG models

RayoNova

Broad panoramic review and report-ready OPG annotations for full-arch dental diagnostics.

Tooth numbering Caries Impaction Nerve proximity Periapical

RVG models

RayoApex

Detailed intraoral analysis with layer-aware RVG review and restorative diagnostics.

Tooth type Caries severity Implants RCT detection Tooth layers

Bone loss models

RayoSpectra

Dedicated periodontal review built for bone level analysis and severity-guided reporting.

Landmark review Severity staging Root-side analysis Dedicated reports

Coming soon

Full diagnostic AI

RayoQuantum

Unified OPG, RVG, bone loss, and reporting into one cross-model diagnostic intelligence layer.

Unified workflow Cross-model review Platform AI

What we predict

Real AI outputs from our models — across every dental radiology workflow.

Every image below is an actual Rayoscan model output. Each detection is explainable, visually grounded, and report-ready.

RayoNova · OPG

Full Arch OPG Analysis

Panoramic detection across all 32 tooth positions

FDI tooth numbering — every visible tooth labeled by position (Maxilla + Mandible)
Impacted tooth detection with angulation classification (mesioangular, vertical, horizontal)
Caries detection and surface localization from panoramic view
Nerve proximity and relation mapping for surgical planning (e.g. inferior alveolar nerve)
Color-coded overlays per finding type with confidence scoring

RayoApex · RVG · 95% confidence

Caries Detection & Tooth Segmentation

Severity-graded caries with full tooth and pulp mapping

Four-tier caries severity grading — Severe, Moderate, Mild, and Enamel-level caries
Multi-surface localization — Occlusal, Mesial, and Distal surfaces identified per tooth
Tooth segmentation boundary drawn per tooth unit
Pulp chamber detection for proximity-to-nerve assessment
Per-detection confidence score reported inline

RayoApex · RVG

Implant Detection

Implant localization with segmentation

Detects dental implants on periapical RVG images
Segmentation boundary drawn around each implant body
Handles multiple implants in the same frame
Works across varying radiographic densities and angulations

RayoApex · RVG · 96% confidence

RCT Tooth Detection

Root canal fill and restoration identification

Gutta percha fill material detected within canal space
Crown and restoration (coronal seal) identified separately
Full tooth segmentation boundary alongside RCT findings
Confidence scoring per anatomical structure identified

RayoSpectra · Bone Loss

Bone Loss Analysis

CEJ–ABL measurement and severity staging

Cemento-Enamel Junction (CEJ) and Alveolar Bone Level (ABL) landmark detection
Bone loss distance measured and displayed per tooth
Stage-based severity interpretation (mild / moderate / severe)
Visual measurement lines overlaid on the radiograph for clinical review

Why Rayoscan

Built for real diagnostic workflows, not isolated demos.

We focus on practical radiology value: faster review, clearer findings, better communication, and a strong foundation for pilot adoption and product rollout.

What we do

✓Analyze OPG and RVG images with dedicated model families tailored to each study type.
✓Detect caries, impacted teeth, nerve proximity, implants, RCT-treated teeth, and bone loss with visual overlays.
✓Support model validation through pilot review lanes so dental experts can help improve accuracy.
✓Generate structured patient-friendly reports that help clinics communicate clearly and document faster.

Best for

Private clinics

Speed up review, build structured reports, and improve patient explanation workflows.

Dental colleges

Access pilot-ready models for training, academic review, and collaborative validation.

Internal dental teams

Inspect edge cases, review model output quality, and shape future Rayoscan releases.

External researchers

Request live demos, explore the platform, and evaluate before joining a pilot lane.

Founders

The founding team building Rayoscan for modern dental diagnostics.

Founder-led product direction across OPG, RVG, bone loss, and reporting workflows. Connect directly through LinkedIn.

Why the founder section matters

Rayoscan is not a generic imaging demo. It is being built as a branded dental AI platform with model families, pilot programs, review loops, and product rollout paths that clinics and colleges can actually adopt.

✓Founder-led product direction across OPG, RVG, bone loss, and reporting workflows.
✓Direct access to the team through pilot programs, live demos, and LinkedIn connections.
✓Clear focus on explainable Dental AI, visual reporting, and deployable clinical experiences.

Co-Founder & CEO

Dr. Sanjana Rajesh Upadhyay

Leading the Rayoscan vision across Dental AI product strategy, radiology workflows, pilot access programs, and branded clinical experiences.

Co-Founder & CTO

Diya Rao Joginipally

Driving the Rayoscan technology stack with a focus on scalable Dental AI systems, platform engineering, and deployable clinical workflows.

Rayoscan Dental AI
built for OPG, RVG
and bone loss.

Four branded AI models powering the Rayoscan diagnostic roadmap.

Real AI outputs from our models — across every dental radiology workflow.

Panoramic detection across all 32 tooth positions