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Naimat Amaan Unified Radiology Platform
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Unified Platform One Window Solution | Production Ready

Everything in One: PACS + RIS + Teleradiology + Viewer + Router + AI MWL

This page explains the complete platform architecture in depth | how data flows from modality to storage, from storage to viewer, how routing rules automate delivery, how RIS manages patient workflow, how AI MWL can be integrated safely, and how we harden and monitor production deployments.

Unified Workflow (How Everything Connects)

A simplified view of real-world data flow. This is the operational backbone of stable deployments.

End-to-End Flow

From acquisition to reporting and delivery: studies are ingested safely, validated, stored, routed automatically, and opened in the viewer with performance tuning, while RIS tracks status lifecycle and ownership.

Modalities CT / MRI / DR / CR / US / MG / XA
DICOM Ingest + Validation C-STORE, tag sanity, SOP class rules
PACS Storage + Lifecycle hot/warm/cold tiers, retention, archive
DICOM Router + Auto-Send routing rules + queue + retries
Viewer + Radiologist Worklist fast load + tools + controlled access
Note: The same platform can connect multi-sites: clinic ? hospital ? teleradiology hub ? archive ? AI pipeline.
ARCHITECTURE / NETWORK IMAGE
Above is the diagram of Network deployment.

Modules (Deep Technical Scope)

Each module is designed to integrate cleanly with the rest, keeping workflows consistent and audit-ready.

P

PACS System (Enterprise Storage)

Study ingestion, storage architecture, retention policies, compression, and safe performance for high study volume.

  • DICOM ingest rules: modality allowlist, SOP class checks
  • Storage tiers: NVMe/SSD hot, HDD warm, cold archive
  • Retention & cleanup policy design per client rules
  • Prefetch concept for scheduled patient studies (optional)
R

RIS (Workflow + Roles)

Appointment, patient flow, study status lifecycle, reporting pipeline and operational control for staff.

  • Roles: admin, reception, technologist, radiologist
  • Status lifecycle: scheduled ? arrived ? acquired ? reported
  • Work queues: STAT, routine, pending, assigned
  • Audit trail and operational timestamps
T

Teleradiology (Multi-Site)

Reading pools, assignment rules, remote radiologist access, and safe delivery across hospitals and time zones.

  • Multi-hospital routing, per-site permission model
  • Reading pools: by modality, subspecialty, or schedule
  • STAT escalation logic and SLA discipline
  • Branding per client site for report PDFs
V

Customized DICOM Viewer

Viewer UI/UX customization aligned to radiologist workflow, fast load, secure access, and tool presets.

  • Tool presets (W/L, measurement, annotations)
  • Hanging protocols mindset (modality layouts)
  • Secure sharing logic (time-based / permission-based)
  • Performance tuning for remote networks
D

DICOM Router (Web-Based)

Rule-based routing engine with auto-send scheduling, queue design, retries, and traceable delivery logs.

  • Routing rules: AE, modality, station, description, tags
  • Auto-send: immediate and scheduled sending
  • Retries + failure capture + audit logs
  • Multi-destination fan-out routing
AI

AI Solution + MWL Worklist

AI integration strategy that fits operational workflow without breaking acquisition or reporting pipelines.

  • AI MWL queue designed for safe workflow
  • Auto-tagging for AI-reviewed studies
  • Priority logic & routing to reading pools
  • Separation of clinical vs AI access controls

Deployment Engineering (Servers, Security, Monitoring, Backup)

Clients pay for stability. Below is how deployments are structured to stay fast, secure, and predictable.

S

Server Sizing & Environment Planning

Right sizing depends on modalities, daily studies, retention policy, and viewer concurrency.

  • Compute sizing: CPU cores based on ingestion + routing + viewer
  • RAM sizing: caching, metadata operations, DB performance
  • Storage sizing: hot tier + warm tier + archive planning
  • Network planning: LAN, VPN, and remote access constraints
S

Security Hardening & Audit Discipline

Medical imaging platforms require strict access control, safe exposure, and traceability.

  • RBAC roles, least privilege and site isolation
  • IP allowlists, VPN segmentation, and AE control
  • Audit logs: access, export, and admin actions
  • Backup strategy: DB + storage + restore testing
Architecture — Unified Platform (High-Level)
ARCHITECTURE IMAGE (placeholder)
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Unified Architecture (Production Mindset)

A stable imaging ecosystem is designed around predictable data flow, safe exposure, routing automation, and performance under load. The platform supports on-prem, hybrid, and cloud deployments.

Architecture Layers
  • Ingestion Layer: AE validation + SOP class controls
  • Storage Layer: tiering + retention + compression options
  • Routing Layer: rule engine + queue + retry discipline
  • Workflow Layer: RIS statuses + assignment logic
  • Access Layer: viewer + RBAC + audit logs
Server Setup — Sizing & Configuration
SERVER SETUP IMAGE (placeholder)
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Deployment Sizing (Example Blueprint)

Server configurations depend on volume, modalities, retention, and viewer concurrency. Below is a sample direction for clients.

Example Sizing Guide (Typical)
  • CPU: 8–32 cores (ingest + routing + viewer load)
  • RAM: 32–128 GB (DB + caching + services)
  • Storage: NVMe/SSD hot + HDD warm + archive tier
  • Network: stable LAN + VPN for remote + firewall design
  • Backups: DB snapshots + object/file storage strategy
Security Hardening — Production Approach
SECURITY / FIREWALL IMAGE (placeholder)
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Security Controls That Matter

Secure exposure is planned. Viewer access, DICOM access, routing endpoints, and admin panels are protected with layered controls.

Hardening Checklist
  • RBAC role definitions + least privilege
  • Firewall allowlists for DICOM and web endpoints
  • VPN segmentation for remote radiologists (when required)
  • Audit logging for critical actions and exports
  • Backup and restore validation strategy
PACS System — Deep Scope
PACS STORAGE IMAGE (placeholder)
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PACS Storage + Lifecycle Engineering

Stable ingest, tiered storage planning, retention discipline, compression strategy, and operational predictability.

What is included
  • AE mapping + modality rules + safe ingest strategy
  • Storage tiering plan aligned with retention
  • Archive integration design (local / cloud / object)
  • Performance tuning for high volume environments
RIS — Deep Scope
RIS WORKFLOW IMAGE (placeholder)
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RIS Workflow that Matches Real Clinics

Roles, statuses, queues, and reporting flow designed to reduce staff confusion and keep operations traceable.

Key components
  • Patient + appointment scheduling framework
  • Status lifecycle tracking and queue control
  • Radiologist assignment rules and workload visibility
  • Audit logs for workflow accountability
Teleradiology — Deep Scope
TELERAD SETUP IMAGE (placeholder)
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Multi-Site Teleradiology Operations

Reading pools, priority handling, routing safety, and controlled remote access across hospitals and time zones.

Included
  • Routing rules for multi-sites + reading hubs
  • STAT escalation and SLA discipline strategy
  • Role isolation per site and controlled access
  • Delivery path: viewer + report PDF workflows
DICOM Viewer — Deep Scope
VIEWER UI IMAGE (placeholder)
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Viewer Customization & Performance

Branding, tool presets, layouts, controlled sharing, and performance tuning for remote and local reading.

Focus areas
  • Branding + UX refinements for radiologist flow
  • Hanging protocols mindset and modality layouts
  • Secure access and time-limited sharing approach
  • Performance optimization foundations (cache/stream)
DICOM Router — Deep Scope
ROUTING RULES IMAGE (placeholder)
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Web Router + Auto-Send Engine

Routing rules reduce human mistakes. Queue-based sending ensures stability even when networks fail.

Key routing capability
  • Rules by AE, modality, station, description, tags
  • Queue + retry logic with traceable delivery logs
  • Fan-out routing: 1 study to multiple systems
  • Failure handling strategy for remote sites
AI MWL — Deep Scope
AI WORKLIST IMAGE (placeholder)
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AI MWL Integration that Fits Workflow

AI becomes valuable only when it is inserted safely into existing clinical workflows without breaking operations.

Approach
  • AI MWL queue aligned with RIS lifecycle
  • Auto tagging and routing based on AI results (optional)
  • Priority logic for AI triage workflows (optional)
  • Access control separation for clinical and AI pipelines