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Related Experiment Video

Updated: Jul 11, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Developing a smart and scalable tool for histopathological education-PATe 2.0.

Lina Winter¹, Annalena Artinger¹, Hendrik Böck¹

¹Institute of Pathology, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Journal of Pathology Informatics

|January 8, 2026

Summary

PATe 2.0 enhances pathology education with a scalable, web-based digital microscopy platform. This redeveloped system offers improved usability, faster image processing, and greater flexibility for educational and research applications.

Keywords:

Artificial intelligence integration Digital pathology Interactive learning Medical education Microservices architecture Scalability User-centric design Virtual microscope Whole-slide imaging (WSI)

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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

Area of Science:

Digital pathology
Medical education technology

Background:

Digital microscopy is vital for pathology education, offering scalable and standardized learning resources.
Previous systems like PATe (2015) provided foundational digital microscopy capabilities.

Purpose of the Study:

To redevelop and enhance the PATe system into PATe 2.0, a scalable web-application for digital microscopy in pathology education.
To improve usability, performance, and flexibility for pathology education and research.

Main Methods:

Agile, iterative development process utilizing a microservices architecture.
Integration of a modern, responsive web-based user interface for desktop and tablet use.
Automation of whole-slide image uploads and processing, supporting open formats (DICOM, OpenSlide).

Main Results:

PATe 2.0 demonstrates significantly reduced tile request times compared to the original PATe system.
The platform ensures modularity, scalability, and reliability through its microservices architecture.
Enhanced interoperability and adaptability across different institutions due to open format support.

Conclusions:

PATe 2.0 offers a robust digital microscopy solution, improving usability, performance, and flexibility in pathology education.
The platform's design facilitates future integration of research algorithms.
PATe 2.0 is a pivotal tool for advancing pathology education and research through digital microscopy.