Data Element Extractor: Input Protocol DICOM (ISO 12052)

Component Specifications

Definition

A software-based industrial component designed to parse, validate, and extract specific data elements from DICOM (Digital Imaging and Communications in Medicine) protocol streams within automated medical device manufacturing and quality control systems. It operates as part of larger industrial automation frameworks to ensure medical imaging equipment meets manufacturing specifications and regulatory requirements.

Working Principle

The component uses protocol parsing algorithms to decode DICOM binary streams, applies validation rules against manufacturing specifications, extracts predefined data elements (such as image parameters, device metadata, and quality metrics), and outputs structured data for downstream industrial processes including quality assurance, compliance logging, and production analytics.

Materials

Software-based component with no physical materials; implemented using programming languages like C++, Python, or Java with specific libraries for DICOM protocol handling (e.g., DCMTK, pydicom).

Technical Parameters

Parameter	Typical range	Notes & selection driver
Output Format	JSON/XML structured data
Error Handling	Automatic retry and logging mechanisms
Input Protocol	DICOM (ISO 12052)
Processing Speed	≥100 DICOM objects/second
Integration Interface	REST API, Message Queue (e.g., RabbitMQ)
Supported Data Elements	Manufacturing parameters, image metadata, device identifiers

Ranges are indicative industry figures for RFQ preparation, not a supplier commitment. Confirm every value and standard with the legal manufacturer before ordering.

Standards

ISO 12052, IEC 62564, DIN 6868-57

Parent Products

This component is used in the following industrial products

DICOM Protocol Parser

A software component that interprets and processes DICOM protocol data within a medical imaging system's communication stack.

View Product Details

Engineering Analysis

Risks & Mitigation

Protocol version incompatibility
Data extraction errors due to corrupted DICOM streams
Integration failures with legacy systems

FMEA Triads

Trigger: Outdated DICOM protocol libraries
Failure: Inability to parse newer DICOM versions, causing production line stoppages
Mitigation: Regular software updates and protocol version testing

Trigger: High-volume data throughput exceeding processing capacity
Failure: Data loss or delayed extraction affecting real-time quality control
Mitigation: Implement load balancing and scalable cloud processing

Industrial Ecosystem

Compatible With

Typical Suppliers & Equivalents

Compliance & Inspection

Tolerance

Data extraction accuracy ≥99.9%, protocol compliance 100% with ISO 12052

Test Method

Automated testing with DICOM conformance statements, simulated production line validation, and third-party certification (e.g., FDA 21 CFR Part 11 for electronic records)

Procurement Evaluation Criteria

A practical evidence checklist for RFQ preparation and supplier evaluation.

Technical documentation

Request current drawings, revision history, and a signed specification sheet.

Manufacturing capability

Verify equipment lists, process limits, capacity, and representative production evidence.

Inspection readiness

Confirm test methods, calibrated equipment, sampling plans, and traceable reports.

Supplier transparency

Check the legal entity, factory address, ownership, certifications, and direct contacts.

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Manufacturers of Data Element Extractor

Manufacturer profiles associated with Data Element Extractor.

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Frequently Asked Questions

What industrial applications use the Data Element Extractor?

It is used in manufacturing lines for medical imaging equipment (CT, MRI, ultrasound) to validate device outputs, ensure regulatory compliance, and automate quality assurance processes.

How does it integrate with existing industrial systems?

Through standard interfaces like REST APIs or message queues, allowing seamless connection with Manufacturing Execution Systems (MES), quality databases, and compliance monitoring tools.

Data Basis

Editorial classification, named public sources where available, and source-reviewed manufacturer records. See the editorial policy.

Preliminary Technical Classification

This page supports structured research, RFQ preparation, and supplier evaluation. It does not replace buyer-led supplier qualification, standards review, or technical approval.

Data Element Extractor