Facilitating the scalability of a cutting-edge radiology imaging platforms and boosting the accuracy and efficiency of the ML model predicting the probability of the development of cancer using the information extracted from CT scans and MRIs.

90% faster image processing due to ML model optimization
Environment setup time reduced from several hours to a few minutes
Seamless integration with the client’s ML model for DICOM analysis
Customizable viewer interface for clinical-grade use
90% faster image processing due to ML model optimization
Environment setup time reduced from several hours to a few minutes
Seamless integration with the client’s ML model for DICOM analysis
Customizable viewer interface for clinical-grade use
Developed a custom automated system for provisioning isolated environments for clinics, internal use, and demo purposes.
Customized and extended an open-source DICOM viewer to support clinical workflows.
Сreated a fail-safe management and routing studies system based on multiple instances of Orthanc.
Established a robust user management and invitation system to safeguard scalability, industry compliance, and data security.
Enabled automated analysis pipeline with the client’s ML model and report generation.
Implemented multi-role validation, findings approval, and visual verification workflows.
Achieved a 90% performance gain in ML inference by optimizing logic and GPU usage.
Introduced cybersecurity best practices like user role management and data encryption to ensure the maximum level of data protection.
Created a smooth and uninterrupted user experience to safeguard quick onboarding and a frictionless workflow for healthcare professionals utilizing the solution.
Developed a custom automated system for provisioning isolated environments for clinics, internal use, and demo purposes.
Customized and extended an open-source DICOM viewer to support clinical workflows.
Сreated a fail-safe management and routing studies system based on multiple instances of Orthanc.
Established a robust user management and invitation system to safeguard scalability, industry compliance, and data security.
Enabled automated analysis pipeline with the client’s ML model and report generation.
Implemented multi-role validation, findings approval, and visual verification workflows.
Achieved a 90% performance gain in ML inference by optimizing logic and GPU usage.
Introduced cybersecurity best practices like user role management and data encryption to ensure the maximum level of data protection.
Created a smooth and uninterrupted user experience to safeguard quick onboarding and a frictionless workflow for healthcare professionals utilizing the solution.
Location
Spain
Industry
Healthcare
Partnership Period
10 months
Type
Enterprise Medical Imaging Solution
Platform
Web
Team Size
10 experts
Services
IT Consulting, Custom Software Development, Data Science, and AI/ML services
Expertise
Web Development, DevOps, Quality Assurance and Testing, UI/UX Design
Tech Stack
Node.js, React, Python, Orthanc, OHIF Viewer, PostgreSQL, PyTorch, NumPy, CUDA, Matplotlib, Argo CD, Helm Chart, Kubernetes, IaC, Terraform
Organize the project in layers such as presentation, domain, and data to follow a clean architecture.
Place business logic in reusable custom hooks or services.
Introduce lazy loading to load components only when needed.
Design small, reusable, and decoupled components. Use props and slots to compose complex components.
Set up a new, solid database with only the necessary tables and clear, well-defined relationships.
Incorporate integrity control, constraints (Primary Keys, Foreign Keys, Unique, Check, NotNull)
Implement a set of data security measures promoting safe authentication and authorization, encryption of sensitive data, and prevention of common attacks
Organize the project in layers such as presentation, domain, and data to follow a clean architecture.
Place business logic in reusable custom hooks or services.
Introduce lazy loading to load components only when needed.
Design small, reusable, and decoupled components. Use props and slots to compose complex components.
Set up a new, solid database with only the necessary tables and clear, well-defined relationships.
Incorporate integrity control, constraints (Primary Keys, Foreign Keys, Unique, Check, NotNull)
Implement a set of data security measures promoting safe authentication and authorization, encryption of sensitive data, and prevention of common attacks
Location
Spain
Industry
Healthcare
Partnership Period
10 months
Type
Enterprise Medical Imaging Solution
Platform
Web
Team Size
10 experts
Services
IT Consulting, Custom Software Development, Data Science, and AI/ML services
Expertise
Web Development, DevOps, Quality Assurance and Testing, UI/UX Design
Tech Stack
Node.js, React, Python, Orthanc, OHIF Viewer, PostgreSQL, PyTorch, NumPy, CUDA, Matplotlib, Argo CD, Helm Chart, Kubernetes, IaC, Terraform