Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jun 13, 2026

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

Published on: June 6, 2025

A straightforward framework to harmonize computational pathology.

Amanda Dy¹, Jochen K Lennerz²

¹Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada.

Journal of Pathology Informatics

|June 12, 2026

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Reliability of foundation models for image retrieval in histopathology.

Npj imaging·2026

Same author

How does AI perform compared to human expert panels in medical Delphi studies? A pilot study through the lens of pathology.

Journal of pathology informatics·2026

Same author

Unintended consequences of legacy oversight in digital medicine.

Nature medicine·2026

Same author

Ki-67 as a treatment decision modifier in breast cancer.

The oncologist·2026

Same author

Authors' Reply.

The Journal of molecular diagnostics : JMD·2026

Same author

The critical role of standards for AI in digital pathology: Digital Pathology Association Concept Paper.

Journal of pathology informatics·2026

Same journal

Erratum to "Pathologists in Venice - Real world cases for an immersive training experience": Education, gaming, and show. <i>Journal of Pathology Informatics</i>, Volume 17, 2025, 100418.

Journal of pathology informatics·2026

Same journal

Erratum to PIRO: A web-based search platform for pathology reports, leveraging large language models to generate discrete searchable insights. <i>Journal of Pathology Informatics</i>, Volume 17, 2025, 100436.

Journal of pathology informatics·2026

Same journal

Erratum regarding missing Declaration of Competing Interest statements in previously published articles.

Journal of pathology informatics·2026

Same journal

An integrated AI pipeline for automated cytogenetic analysis of bone marrow karyograms in hematological malignancies: A Pix2Pix enhancement and deep learning detection approach.

Journal of pathology informatics·2026

Same journal

Deployment of AI-driven automated quality control of whole-slide images in a large tertiary cancer center.

Journal of pathology informatics·2026

Same journal

Comparative analysis of whole-slide scanner tissue detection algorithms: Implications for scan area, scan time, and file size in high-volume digital pathology workflows.

Journal of pathology informatics·2026

See all related articles

Computational pathology dataset descriptions lack standardization, hindering research comparability. We propose a DICOM-aligned framework for clear, hierarchical reporting of clinical, lab, and digital data to improve AI in pathology.

Area of Science:

Computational pathology
Digital pathology
Medical informatics

Background:

Inconsistent terminology in computational pathology datasets conflates biological units, lab preparations, and digital data.
This ambiguity complicates data interpretation, limits cross-study comparability, and impacts claims on dataset scale and clinical relevance.
Existing foundation models show significant variability in reporting disease representation, necessitating a standardized framework.

Purpose of the Study:

To propose a harmonization framework for computational pathology dataset descriptions.
To align dataset reporting with the DICOM hierarchical information model.
To enable transparent characterization, improve reproducibility, and facilitate clinical translation of AI in pathology.

Main Methods:

Keywords:

Biomarker DICOM Foundation model Standard

More Related Videos

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Related Experiment Videos

Last Updated: Jun 13, 2026

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

Published on: June 6, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Review of widely cited foundation models in computational pathology.
Identification of variability in disease representation reporting.
Development of a hierarchical framework distinguishing clinical, lab, and digital domains.

Main Results:

Substantial variability observed in how disease representation is reported across foundation models.
A proposed framework that aligns with DICOM, distinguishing key data domains.
Recommendations for explicit reporting across hierarchical levels.

Conclusions:

Adoption of the proposed framework enables transparent dataset characterization in computational pathology.
Standardized terminology improves reproducibility and facilitates regulatory and clinical translation.
The framework offers an immediately implementable pathway towards harmonized reporting in AI-driven pathology research.