Frequently asked questions
What services and solutions does EthosMED provide?
EthosMED delivers complete Picture Archiving and Communication Systems (PACS), teleradiology platforms, and integrated AI diagnostic microservices. Our solutions are designed to streamline medical imaging storage, enable rapid remote reporting, and provide advanced diagnostic decision support to clinical teams.
Can EthosMED integrate with our existing PACS, RIS, and hospital network?
Yes. Our architecture natively supports standard DICOM protocols, HL7 messaging, and web REST APIs. Whether you are connecting to an established enterprise PACS or an open-source framework like Orthanc, EthosMED integrates directly into your existing workflow without requiring a overhaul of your infrastructure.
What structures are covered by the AI Auto Segmentation module?
The 3D Auto Segmentation module automatically identifies, contours, and renders over 104 distinct anatomical structures across CT and MRI series, including skeletal elements, vascular systems, thoracic organs, and abdominal viscera for rapid surgical planning and volume analysis.
Can EthosMED run fully offline or in an air-gapped environment?
Yes. All processing engines, database systems, and pre-trained AI models can be deployed fully on-premise. This ensures zero reliance on cloud connectivity and allows your facility to operate independently during internet outages.
How is patient data privacy and HIPAA/GDPR compliance managed?
Data security is built into every tier of our architecture. For local and hybrid deployments, DICOM pixel data and patient metadata remain strictly within your hospital or clinic network with encrypted storage, role-based access controls, and full audit logging.
How does the system handle high-volume teleradiology and remote reporting?
Our infrastructure utilizes optimized DICOM streaming and lossless progressive compression. This allows radiologists to open and interact with large volumetric studies (such as 3D CT or MRI series) remotely in seconds, even over bandwidth-constrained connections.
What deployment options are available (On-Premise, Cloud, Hybrid)?
We offer full flexibility based on your facility's operational needs:
On-Premise: Full data sovereignty with local processing and local server archives.
Hybrid: Local high-speed diagnostic caches paired with cloud backup for long-term storage and remote access.
SaaS / Cloud: Fully hosted infrastructure with global accessibility and managed maintenance.
What are the minimum hardware requirements for on-premise deployment?
For basic diagnostic viewing and archiving, standard server hardware with multicore CPUs and enterprise storage is sufficient. If you plan to deploy high-throughput 3D segmentation or heavy vision-language AI models, an NVIDIA GPU with at least 12GB to 24GB VRAM is recommended for optimal inference speed.
Is technical support and training included with deployment?
Yes. Every deployment includes comprehensive onboarding for radiographers, radiologists, and IT administrators, alongside ongoing maintenance, automated system health monitoring, and regular software updates.
