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Semantic annotation for computational pathology: multidisciplinary experience and best practice recommendations.

Noorul Wahab¹, Islam M Miligy^2,3, Katherine Dodd⁴

¹Tissue Image Analytics Centre, University of Warwick, Coventry, UK.

The Journal of Pathology. Clinical Research

|January 11, 2022

Summary

This summary is machine-generated.

This study addresses the lack of guidelines for annotating whole-slide images (WSIs) in computational pathology (CPath). It presents best practices for accurate WSI annotation to improve machine learning model validation and diagnostic algorithms.

Keywords:

annotations computational pathology guidelines whole-slide images

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Area of Science:

Computational pathology
Digital pathology
Machine learning in healthcare

Background:

Whole-slide imaging (WSI) enables advanced computational pathology (CPath) algorithms.
Accurate annotations are crucial for validating machine learning (ML) models in CPath.
Current lack of standardized annotation guidelines hinders CPath project development.

Purpose of the Study:

To establish best practices and guidelines for annotating pathology WSIs.
To address the shortcomings in current annotation methodologies for CPath projects.
To improve the interpretability and accuracy of ML algorithms in digital pathology.

Main Methods:

Conducted a large-scale annotation exercise with pathologists, ML experts, and researchers.
Developed a real-world case study within the PathLAKE consortium.
Defined annotation constructs, data dictionaries, and diagnostic algorithms.

Main Results:

Identified critical best practices for WSI annotation in CPath.
Demonstrated the impact of annotation quality on ML model performance.
Provided a framework for annotation guidelines throughout the CPath project lifecycle.

Conclusions:

Standardized annotation guidelines are essential for reliable CPath.
The presented best practices enhance the development and validation of digital pathology algorithms.
Adopting these guidelines will improve the consistency and accuracy of CPath research and diagnostics.