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<p>Digitization of histological specimens enables new computer-assisted analysis and artificial intelligence (AI)-supported diagnostics, but is hampered by a&#xa0;lack of standards. Interoperability between proprietary formats and clinical systems such as the Picture Archiving and Communication System (PACS) or Laboratory Information Systems (LIS) poses a&#xa0;particular challenge. The Digital Imaging and COmmunications in Medicine (DICOM) format, adapted from radiology, offers an open, vendor-independent solution that integrates image data, metadata, and analysis results and enables interoperable exchange. A&#xa0;literature review shows a&#xa0;growing number of publications on digital and computer-assisted pathology, with DICOM increasingly being discussed as a&#xa0;key format. With an open-source, modular Docker pipeline, we demonstrate the practical implementation of DICOM-compliant workflows for storing and visualizing whole slide images and AI results. This creates the basis for standardized, transparent, and trustworthy digital pathology.</p>

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Digital, DICOM, Diagnostik – Einheit statt Chaos

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月29日

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  • Christoph Blattgerste,
  • Maximilian Legnar,
  • Cleo-Aron Weis

摘要

Digitization of histological specimens enables new computer-assisted analysis and artificial intelligence (AI)-supported diagnostics, but is hampered by a lack of standards. Interoperability between proprietary formats and clinical systems such as the Picture Archiving and Communication System (PACS) or Laboratory Information Systems (LIS) poses a particular challenge. The Digital Imaging and COmmunications in Medicine (DICOM) format, adapted from radiology, offers an open, vendor-independent solution that integrates image data, metadata, and analysis results and enables interoperable exchange. A literature review shows a growing number of publications on digital and computer-assisted pathology, with DICOM increasingly being discussed as a key format. With an open-source, modular Docker pipeline, we demonstrate the practical implementation of DICOM-compliant workflows for storing and visualizing whole slide images and AI results. This creates the basis for standardized, transparent, and trustworthy digital pathology.