5 Advantages of Cloud-Native Medical Imaging
Medical imaging is a vital tool for diagnosing and treating various diseases and conditions. However, traditional medical imaging systems face many challenges, such as data security, data storage, data interoperability, and data analysis.
Cloud-native medical imaging is a new approach that leverages the power and flexibility of cloud computing to overcome these challenges and improve patient care.
In this blog post, we will explore five advantages of a cloud-native medical online image storage system.
1. Data Security
Cloud-native medical imaging uses the international DICOMweb standard for imaging data exchange, which ensures data encryption and authentication.
Cloud-native medical imaging also provides automated data de-identification, which removes sensitive information from the images to protect patient privacy.
It leverages the advanced security features of Google Cloud, such as identity and access management, audit logging, and compliance certifications.
2. Data Storage
Cloud-native medical imaging enables scalable and cost-effective data storage on Google Cloud.
Cloud-native medical imaging can seamlessly integrate with on-premises storage systems, such as NetApp or Change Healthcare cloud-native PACS, to provide a hybrid cloud solution that meets the diverse needs of healthcare organizations.
Cloud-native medical imaging also allows easy access to data from any device and location, which facilitates remote reading and collaboration.
3. Data Interoperability
Cloud-native medical imaging supports the convergence of diverse storage formats to the DICOM standard, which enables data compatibility and consistency across different systems and devices.
Cloud-native medical imaging also allows easy integration with other Google Cloud services, such as Big Query and Looker, to perform advanced analytics and create training datasets for AI models.
Cloud-native medical imaging also offers native integration with any DICOMweb viewer, which enhances the user experience and workflow.
4. Data Analysis
Cloud-native medical imaging accelerates the development and deployment of AI models for medical imaging by using Vertex AI, a Google Cloud service that simplifies the entire ML lifecycle.
Vertex AI helps automate the highly manual and repetitive task of labeling medical images with AI-assisted annotation tools from NVIDIA and MONAI.
Vertex AI also helps reduce the time and resources required to build custom models with 80% fewer lines of code. It also provides scalable and reliable model training, testing, deployment, and monitoring.
5. Data Deployment
Cloud-native medical imaging offers flexible options for data deployment to meet the diverse sovereignty, data security, and privacy requirements of healthcare organizations.
Cloud-native medical imaging can deploy data on Google Cloud, on-premises, or at the edge using Google Distributed Cloud, enabled by Anthos.
Google Distributed Cloud provides centralized management and policy enforcement for all data deployments while ensuring consistent performance and functionality.
Summary
Cloud-native medical online image storage system is a game-changer for healthcare delivery. It helps improve data security, data storage, data interoperability, data analysis, and data deployment for medical imaging.
It also helps improve patient outcomes by enabling faster diagnoses, increasing productivity, reducing costs, and expanding access to care.