An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics.

Area of Science:

• Digital pathology
• Computational pathology
• Biomedical imaging

Background:

• Precision medicine relies on high-resolution, multi-modal tissue-based pathology image analytics.
• Existing tools often lack accessibility for diverse research and clinical users.
• There is a need for integrated platforms supporting advanced tissue analysis.

Purpose of the Study:

• To develop a publicly available, web-based platform called Digital Pathology Laboratory (DPLab).
• To facilitate whole-slide image visualization, annotation, analysis, and sharing for biomedical researchers and clinicians.
• To enable the reconstruction and analysis of three-dimensional (3D) tissue volumes.

Main Methods:

• Developed methods to reconstruct 3D tissue volumes by registering 2D whole-slide images from serial tissue sections (H&E, IHC).
• Integrated diverse staining methods to provide multi-modal cellular and pathophysiologic context within a 3D micro-environment.
• Hosted DPLab on a public server connected to a computational cluster for intensive image analysis, with results accessible via a web interface.

Main Results:

• DPLab provides an analysis toolbox with numerous image processing algorithms.
• The platform supports the integration of community-contributed algorithms.
• It offers an effective solution for improving the accessibility and dissemination of image analysis tools.

Conclusions:

• DPLab is a novel platform for next-generation tissue investigation.
• It facilitates the discovery of clinically relevant disease mechanisms in a digital 3D tissue space.
• The platform democratizes access to advanced digital pathology tools for the research community.