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Radiological data processing system: lifecycle management and annotation.

Tatiana Bobrovskaya1, Yuriy Vasilev2, Anton Vladzymyrskyy2

  • 1Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department, Moscow, Russia. BobrovskayaTM@zdrav.mos.ru.

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Summary
This summary is machine-generated.

A new platform automates radiological dataset processing independently of existing systems. This system manages the entire data lifecycle, from retrieval to annotation and presentation, enhancing workflow efficiency.

Keywords:
Artificial intelligenceDatasetDataset curationRadiology

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Area of Science:

  • Medical Imaging Informatics
  • Radiology Data Management

Background:

  • Radiological datasets require robust management throughout their lifecycle.
  • Existing medical information systems present challenges for independent dataset processing.

Purpose of the Study:

  • To develop an automated platform for radiological dataset processing.
  • To ensure the platform operates independently of medical information systems.
  • To manage datasets from retrieval through annotation and presentation.

Main Methods:

  • A modular platform architecture allowing independent or combined module operation.
  • Sequential processing of data through interconnected modules.
  • Integration of a local database for study protocols, a radiology information system (RIS), and storage for labeled studies and reports.

Main Results:

  • A functional platform with local storage for efficient radiological dataset processing.
  • Modules facilitate data search, extraction, anonymization, and annotation.
  • Automated generation of annotated files and standardized dataset documentation.

Conclusions:

  • The developed platform offers a comprehensive workflow for radiological dataset management.
  • The system is operational at the Center for Diagnostics and Telemedicine.
  • Future work will expand the platform's capabilities.