DICOM format and protocol standardization—A core requirement for digital pathology success
Abstract
As the use of digital techniques in toxicologic pathology expands, challenges of scalability and interoperability come to the fore. Proprietary formats and closed single-vendor platforms prevail but depend on the availability and maintenance of multiformat conversion libraries. Expedient for small deployments, this is not sustainable at an industrial scale. Primarily known as a standard for radiology, the Digital Imaging and Communications in Medicine (DICOM) standard has been evolving to support other specialties since its inception, to become the single ubiquitous standard throughout medical imaging. The adoption of DICOM for whole slide imaging (WSI) has been sluggish. Prospects for widespread commercially viable clinical use of digital pathology change the incentives. Connectathons using DICOM have demonstrated its feasibility for WSI and virtual microscopy. Adoption of DICOM for digital and computational pathology will allow the reuse of enterprise-wide infrastructure for storage, security, and business continuity. The DICOM embedded metadata allows detached files to remain useful. Bright-field and multichannel fluorescence, Z-stacks, cytology, and sparse and fully tiled encoding are supported. External terminologies and standard compression schemes are supported. Color consistency is defined using International Color Consortium profiles. The DICOM files can be dual personality Tagged Image File Format (TIFF) for legacy support. Annotations for computational pathology results can be encoded.
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DICOM has become the de facto standard for most radiology images, but its adoption in digital pathology remains in an earlier stage.
“For example, although the DICOM format has become the de facto standard for most radiology images, the adoption of DICOM in digital pathology remains in an earlier stage (Clunie, 2020).”
From Navigating the landscape of multimodal AI in medicine: A scoping review on technical challenges and clinical applications (2025) · cites this paper as Clunie, 2020
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References 26 · Cited by 73
- Authors
- Clunie, D. A.
- Affiliations
- PixelMed Publishing, LLC, Bangor, PA, USA
- Corresponding author
- Clunie, David A.
- ORCID
- Clunie, David A.
- Venue
- Toxicologic Pathology
- Publisher
- SAGE Publications
- Published
- 2020-10-16
- Volume
- 49
- Issue
- 4
- Pages
- 738-749
- ISSN
- 0192-6233 (ISSN-L)
- 1533-1601
- OpenAlex
- W3093002967
- Cited by
- 73
- References
- 26
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 15 · 2023: 8 · 2022: 12 · 2021: 4
- FWCI
- 2.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Toxicologic Pathology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- DICOM, digital pathology, whole slide imaging, interoperability, virtual microscopy, embedded metadata, TIFF, color consistency, computational pathology, image compression
- MeSH terms
- Diagnostic Imaging, Humans, Radiology Information Systems, Reference Standards
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