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Summary

Digitizing pathology slides for AI diagnostics faces standardization challenges. Implementing the Digital Imaging and COmmunications in Medicine (DICOM) format with an open-source pipeline enables interoperable digital pathology workflows.

Keywords:
Computational pathologyComputer visionData communicationStandardizationWhole slide images

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Area of Science:

  • Digital pathology
  • Medical imaging
  • Artificial intelligence in healthcare

Background:

  • Digitization of histological specimens is crucial for advanced computer-assisted analysis and AI-driven diagnostics.
  • Lack of standardization and interoperability between proprietary formats and clinical systems (PACS, LIS) hinders digital pathology adoption.
  • The Digital Imaging and COmmunications in Medicine (DICOM) format offers a potential solution for integrating image data, metadata, and analysis results.

Purpose of the Study:

  • To address the lack of standards in digital pathology.
  • To demonstrate a practical implementation of DICOM-compliant workflows for whole slide images and AI results.
  • To establish a foundation for standardized, transparent, and trustworthy digital pathology.

Main Methods:

  • Literature review on digital and computer-assisted pathology, focusing on DICOM adoption.
  • Development and implementation of an open-source, modular Docker pipeline.
  • Demonstration of DICOM-compliant workflows for storing and visualizing whole slide images and AI results.

Main Results:

  • A growing body of literature supports the use of DICOM in digital pathology.
  • Successful practical implementation of DICOM-compliant workflows using an open-source pipeline.
  • Demonstrated capability for storing and visualizing whole slide images and AI results in a standardized format.

Conclusions:

  • DICOM is emerging as a key format for enabling interoperability in digital pathology.
  • The developed Docker pipeline facilitates standardized, transparent, and trustworthy digital pathology.
  • This work provides a basis for wider adoption of digital pathology solutions.