SUCCESS STORY

Reimagining Digital Pathology at Scale:
A Cloud-Native Transformation on
Google Cloud

Modernized digital pathology infrastructure
using Google Cloud

Digital pathology is transforming how pathology teams access, manage, and work with diagnostic images. But as image volumes continue to grow, organizations face a familiar challenge: how to make these environments more scalable and efficient without compromising speed, security, or interoperability.

This success story looks at how a global healthcare imaging leader worked with CitiusTech to address these challenges through a cloud-native digital pathology architecture on Google Cloud. The transformation brought together modern imaging services, intelligent storage management, DICOMweb-based interoperability, and secure access to create a more flexible and scalable pathology environment.

The results included smaller image sizes, lower long-term storage costs, and significantly faster access to high-resolution images—while laying the groundwork for future AI-driven diagnostic capabilities.

Download the Success Story:

Take a closer look at how a healthcare imaging organization approached some of the practical challenges that come with scaling digital pathology, including:

Managing rapidly growing volumes of high-resolution pathology images without letting storage costs escalate
Improving the speed at which pathologists and other users can access digital images
Bringing greater flexibility to pathology workflows through standards-based interoperability
Managing image metadata and storage lifecycles more effectively
Creating a secure, cloud-native foundation that can evolve as digital pathology and AI capabilities advance

Who should read this:

CIOs, CTOs, Chief Digital Officers, enterprise architects, and technology teams exploring how cloud can help modernize imaging environments and support the next generation of pathology workflows

What insights you’ll gain:

The success story offers a practical view of what it takes to modernize a digital pathology environment for scale. It looks beyond simply moving workloads to the cloud and explores how architecture, storage, interoperability, security, and image access can come together to address real operational challenges.
Readers will also see how Google Cloud technologies can be applied to a digital pathology environment and how a modern cloud foundation can help organizations prepare for emerging AI-driven diagnostic use cases.

Frequently Asked Questions

What is digital pathology?

Digital pathology is the process of capturing, storing, managing, viewing, and analyzing pathology slides as high-resolution digital images rather than relying solely on physical glass slides. It enables pathologists and healthcare organizations to access pathology images digitally, support collaboration, integrate pathology data with clinical systems, and create a foundation for advanced analytics and AI-driven diagnostics. Discover our comprehensive digital pathology services.

Why are healthcare organizations moving digital pathology to the cloud?

Healthcare organizations are moving digital pathology to the cloud to manage growing volumes of high-resolution images, improve accessibility, optimize storage costs, and support scalable digital workflows. A cloud-native architecture can also simplify infrastructure management and provide a foundation for interoperability, automation, analytics, and future AI-enabled pathology applications.

What are the key benefits of a cloud-native digital pathology platform?

A cloud-native digital pathology platform can improve scalability, image accessibility, storage efficiency, interoperability, and operational agility. It can also automate image and storage lifecycle management while enabling secure access across pathology viewers and healthcare systems. These capabilities help organizations modernize legacy pathology environments and prepare their infrastructure for advanced analytics and AI-driven diagnostics.

How can Google Cloud support digital pathology?

Google Cloud can support digital pathology through cloud-based healthcare imaging, storage, security, and interoperability capabilities. Services such as Cloud Healthcare API and DICOM Store can help organizations manage medical images and enable standards-based access through DICOMweb. Google Cloud can also support scalable architectures for image processing, storage optimization, secure access, and future AI-enabled healthcare applications. Explore and unlock value across the healthcare spectrum with CitiusTech by simplifying complex healthcare workflows using Google Cloud Platform (GCP). For more information, consult with our experts to discover how AI and Google Cloud can elevate your digital pathology initiatives and drive innovative healthcare solutions.

What is DICOMweb and why is it important for digital pathology?

DICOMweb is a web-based set of standards for accessing and exchanging medical imaging information using DICOM. It is important for digital pathology because it can enable standardized image access across different viewers, applications, and healthcare systems. DICOMweb can help reduce dependence on proprietary interfaces and support more flexible, interoperable cloud-based imaging environments.

How can healthcare organizations reduce digital pathology storage costs?

Healthcare organizations can reduce digital pathology storage costs by combining image compression, intelligent storage tiering, metadata-driven lifecycle management, and automated movement of rarely accessed images to appropriate storage classes. A cloud-native approach can help organizations optimize storage based on image usage and retention requirements instead of maintaining all pathology images in high-performance storage indefinitely. Consult with our experts to explore how this strategy can benefit your organization.

How can cloud technology improve digital pathology image retrieval?

Cloud technology can improve digital pathology image retrieval by using scalable imaging services, optimized storage architectures, caching, and efficient access mechanisms such as DICOMweb. A well-designed architecture can reduce the time required to retrieve high-resolution pathology images while providing secure access through pathology viewers and clinical applications.

How does interoperability improve digital pathology workflows?

Interoperability enables digital pathology images and associated metadata to be accessed and exchanged across different applications, viewers, and healthcare systems. Standards such as DICOM and DICOMweb can help create a more connected imaging environment, reducing technology silos and making it easier for healthcare organizations to integrate pathology data into broader clinical, operational, analytics, and AI workflows. Consult with our experts to explore how this integration can enhance your digital pathology capabilities.

How can digital pathology infrastructure support AI-driven diagnostics?

Modern digital pathology infrastructure can provide the scalable image storage, standardized data access, processing capabilities, and interoperability needed to support AI-driven diagnostics. By modernizing the underlying imaging architecture first, healthcare organizations can create a stronger foundation for deploying computer vision, image analytics, machine learning, and other AI applications as their clinical use cases mature. Consult with our experts to understand and plan for an AI-ready digital pathology environment.

What should healthcare organizations consider when modernizing digital pathology infrastructure?

Healthcare organizations should consider scalability, storage economics, image retrieval performance, interoperability, security, metadata management, workflow integration, and future AI requirements when modernizing digital pathology infrastructure. A cloud-native architecture should address both current operational challenges and future technology needs, allowing organizations to evolve their pathology ecosystem without repeatedly redesigning the underlying infrastructure. Consult with our experts to explore how to build a flexible, scalable, and future-proof digital pathology environment.