Citrusbug builds AI-powered medical imaging platforms for radiology groups, hospital systems, and medtech enterprises. From PACS modernization to FDA-aligned SaMD builds with DICOM, FHIR R4, and IEC 62304 compliance baked in, we deliver imaging infrastructure your clinical and engineering teams can actually rely on.
HIPAA Compliant
HL7 / FHIR Compatible
SOC 2 Type II
Trusted by
Certifications and Accreditations
Most radiology and imaging teams are not dealing with theoretical problems. They are managing PACS environments built on proprietary vendor lock-in, DICOM viewers that cannot handle modern study volumes, and AI tools purchased without a clear integration plan.
When an imaging system cannot connect to Epic Hyperdrive via a standards-based FHIR R4 interface, radiologists work around it. When a legacy VNA lacks DICOMweb API support (WADO-RS, STOW-RS), cloud migration stalls entirely. When an AI model flags a finding that cannot be surfaced inside the existing RIS workflow, clinicians stop trusting it.
These are not configuration issues. They are architectural decisions made at build time, and they are expensive to undo without the right development partner.
What Breaks First
Custom Picture Archiving and Communication Systems and Vendor-Neutral Archives built on DICOMweb APIs (WADO-RS, STOW-RS, QIDO-RS). Microservices architecture for multi-facility deployment and high-volume study throughput without proprietary lock-in.
Convolutional neural networks and transformer-based models trained on DICOM datasets using the MONAI framework. Covers lesion detection, image segmentation, anomaly flagging, and structured report generation for CT, MRI, X-ray, and PET modalities.
Web-based DICOM viewers built on OHIF Viewer architecture, customized for specialty-specific workflows, such as neuroradiology, cardiology, oncology, and mammography. Worklist prioritization with AI-driven triage and critical finding alerts.
Imaging data integration with Epic Hyperdrive, Oracle Health, and standalone EHRs using HL7 FHIR R4/R4B APIs. ImagingStudy, DiagnosticReport, and Observation FHIR resource mapping for bi-directional clinical data exchange.
Full Software as a Medical Device development following FDA’s PCCP guidance (finalized December 2024) and IEC 62304 lifecycle processes. Includes 510(k) documentation, risk analysis under ISO 14971:2019, and software SBOM preparation per FDA’s June 2025 cybersecurity requirements.
Structured reporting platforms replacing free-text dictation, automated study routing, and AI-powered worklist management that connects to clinical workflow automation software across the enterprise imaging network.
Legacy imaging systems slow diagnostic throughput and widen integration debt. Talk to our team about what a rebuild or modernization actually looks like.
Book a Technical Consultation
High-volume DICOM ingestion pipelines, MPR reconstruction, automated windowing, and AI-assisted lesion measurement. Neuroradiology, thoracic, and abdominal CT applications with RECIST-compliant measurement tools.
Brain MRI analysis platforms with volumetric segmentation, CNN-based tumor detection, and comparison study management. FMRI and DTI tractography visualization for research and clinical applications.
Echocardiography analysis software with automated ejection fraction calculation, wall motion scoring, and cardiac CT angiography measurement. Integration with cardiovascular information systems (CVIS) via HL7 feeds.
2D and 3D mammography viewers with AI-powered density classification, lesion detection, and prior comparison tools. FDA 510(k)-cleared CADe algorithm integration or custom model development with PCCP documentation for future updates without re-submission.
Whole-slide image management platforms with tile-based rendering, AI-assisted annotation, and DICOM WSI standard (Supplement 145) compliance for cross-system interoperability.
Real-time ultrasound processing software with automated measurements, AI guidance for image quality assessment, and edge-compute capability for portable and point-of-care deployments.
We map clinical workflows, define intended use, assign FDA SaMD classification, and identify the applicable regulatory pathway (510(k), De Novo, or general controls) before any design work begins. IEC 62304 software safety classification is assigned in this phase.
We produce a full system architecture with DICOM conformance statements, FHIR resource mapping, and integration specifications for target EHR systems. Risk analysis under ISO 14971:2019 starts here, running in parallel with design.
Training pipelines built on MONAI framework using curated, de-identified DICOM datasets. Model validation covers sensitivity, specificity, and performance across demographic subgroups, addressing the FDA's expectations for medical device software that informs clinical decisions.
DICOM conformance testing, HL7 interface validation, FHIR API integration testing, and HIPAA security assessment. We maintain a full traceability matrix linking requirements to test cases per IEC 62304. Healthcare software testing services cover functional, performance, and regulatory compliance validation.
Production deployment with documented software SBOM (mandatory for FDA networked device submissions since June 2025). L1/L2/L3 SLA support options. PCCP documentation included for AI components, enabling future model updates without triggering a new 510(k) submission.
Citrusbug's imaging platform architecture is designed for regulatory submission from the first sprint, not retrofitted after build. Compliance and interoperability frameworks built into every system we deliver.
Hospitals have purchased AI imaging tools that radiologists do not use. The pattern is consistent: the model runs on a separate server, outputs appear in a separate interface, and there is no structured way to surface findings inside the existing RIS or EHR workflow. Radiologists cannot act on what they cannot see in context.
This is a software integration failure, not an AI quality problem. The FDA cleared 295 AI/ML SaMD devices in 2025 – 76% in radiology, but clinical adoption has not kept pace with clearance volume. The bottleneck is integration depth, not AI capability.
Citrusbug builds medical image analysis software where AI outputs surface inside the radiologist’s existing workflow – DICOM viewer annotations, structured report pre-population, and RIS worklist flags rather than requiring a separate application to be opened, checked, and cross-referenced.
Medical imaging platform development ranges from $40,000 for focused module builds to $350,000+ for full SaMD development with FDA regulatory documentation. The primary drivers are modality scope, AI model complexity, regulatory pathway, and EHR integration depth. Share your requirements and we will return a detailed scope estimate within 48 hours.
$40,000 – $100,000+
For teams migrating a legacy PACS to cloud-native DICOMweb architecture, adding AI integration to an existing viewer, or building a specific imaging module (structured reporting, worklist, DICOM router).
• Legacy PACS to cloud migration
• DICOMweb API layer development
• AI model integration into existing viewer
• 12–20 week timeline
$100,000 – $250,000+
For radiology groups or medtech companies building a complete imaging platform including PACS, DICOM viewer, AI diagnostic layer, and EHR integration from scratch.
• PACS + VNA + DICOM viewer
• AI model development and validation
• FHIR R4 EHR integration
• FDA regulatory documentation support
• 24–40 week timeline
$150,000 – $350,000+
For imaging AI companies building a clinical decision support or diagnostic tool requiring FDA SaMD classification, 510(k) submission, and PCCP documentation for future algorithm updates.
• Full IEC 62304 lifecycle documentation
• ISO 14971 risk management file
• Software SBOM preparation
• 510(k) technical file support
• PCCP for algorithm update pathway
Every imaging project begins with FDA SaMD classification and IEC 62304 safety class assignment before architecture design. Compliance is not a final checklist; it is a built-in constraint from day one.
Our teams understand DICOM conformance at the protocol level, conformance statements, SOP class support, transfer syntax negotiation, and DICOMweb API implementation, not just DICOM as a file format. This prevents the integration failures that stall deployment.
We produce DICOM conformance statements, FHIR resource maps, system architecture diagrams, and risk analysis starting points before writing a single line of application code. What you see before signing is what gets built.
Full source code, model weights, training pipelines, and compliance documentation are delivered to your team at project completion. No licensing dependency on Citrusbug infrastructure for your production system.
Most medical imaging software development companies build technically capable software. The problem is what happens at the intersection of engineering and regulatory submission.
FDA’s 510(k) process for AI imaging SaMD requires a Software SBOM for networked devices, PCCP documentation if you want to update your AI model post-clearance without re-submission, and a full traceability matrix under IEC 62304 connecting requirements to implementation and test evidence. Teams that treat these as post-build documentation tasks spend six to twelve additional months in remediation before they can submit.
Citrusbug embeds this documentation discipline into the Secure ADLC delivery methodology from sprint one.
→ IEC 62304 traceability matrix maintained throughout development
→ ISO 14971 risk management file updated as architecture evolves
→ DICOM conformance statement produced alongside the viewer/PACS build
→ Software SBOM prepared in parallel with the codebase, not assembled at submission
Replacing or migrating a PACS is one of the highest-risk infrastructure projects a radiology group or health system can undertake. Study continuity, DICOM data migration, and zero-downtime switchover during active clinical operations are non-negotiable requirements.
We approach PACS modernization using a phased migration strategy: the legacy PACS remains live while the new cloud-native system ingests forward-flow studies, followed by retroactive migration of historical studies in priority order (most recent first). DICOM conformance is validated end-to-end before any routing changes affect clinical workflow.
Legacy PACS Assessment: Review of current DICOM conformance, SOP class support, storage architecture, and integration points with RIS and EHR systems.
Cloud-Native Architecture Design: New system architecture using DICOMweb APIs, a Vendor-Neutral Archive layer, and Azure Health Data Services or AWS HealthImaging for compliant cloud storage. Integration with diagnostic imaging systems downstream.
Phased Migration Execution: Forward-flow cutover followed by retroactive migration with DICOM tag validation, lossless transfer verification, and reconciliation reporting. Zero-downtime transition with rollback capability maintained throughout.
EHR and RIS Integration: FHIR ImagingStudy and DiagnosticReport resources connected to Epic Hyperdrive or Oracle Health. HL7 ORM/ORU messages are maintained for legacy RIS compatibility during transition.
Unlike agencies that deliver a running application and a login, Citrusbug delivers the full package required for a production medical imaging system.
Source code, model weights, training pipelines, infrastructure-as-code, and DICOM conformance statements – all versioned and handed to your team with no Citrusbug dependency for production operation.
IEC 62304 software development plan, design history file, traceability matrix, ISO 14971 risk management file, and software SBOM prepared to FDA cybersecurity guidance standards. Usable directly in regulatory submissions.
FHIR API documentation, HL7 interface specifications, DICOM conformance statement, and system integration test reports. Your EHR and PACS integration teams receive what they need to maintain and extend the system.
For SaMD products: a documented plan for real-world performance monitoring, feedback collection, and PCCP-aligned model update procedures. Meets FDA’s December 2025 Real-World Evidence guidance expectations for AI imaging devices.
Their agile way of working, competence, and friendliness are impressive.December 7, 2024
Citrusbug Technolabs handles a data extraction project for an education company. They're also responsible for managing an AI generation project for the client.
Citrusbug Technolabs has laid out and followed a clear project outline and consistently met deadlines. The team communicates well and demonstrates a strong understanding of the client's vision and goals. Their agile approach, high level of competence, and personable approach stand out.
Read More
Their communication and ability to capture exactly what I was asking for were impressive.November 14, 2024
Citrusbug Technolabs built an automated system for a veteran medical company. The system needed to collect and store user data, generate customized letters based on surveys, and use AI to summarize reviews.
Citrusbug Technolabs delivered a functional automated system that successfully organized the client's records and auto-generated statements. The team was quick to respond, addressed all roadblocks, and communicated effectively. Overall, their ability to understand the client's needs stood out.
Read More
They were very calm and talented, and they did bring some of their own ideas.January 28, 2025
Citrusbug Technolabs has developed an MVP for a freight and capacity marketplace. The team has created three different interfaces for three market segments.
Citrusbug Technolabs has successfully developed an effective MVP. The team has delivered the project on time and almost within budget. Moreover, their responses have been timely. Overall, the team has been calm, talented, and innovative. This has led to the client's satisfaction.
Read More
What stood out most about them was their personalized approach and sense of ownership in every aspect of the project."February 27, 2024
Citrusbug Technolabs built a Flutter cross-platform mobile app for an education company. They also developed two web apps and an admin panel and provided DevOps support for the client's infrastructure.
Citrusbug Technolabs' support successfully boosted the client's user engagement by 8x, resulting in an 85% retention rate. The reliable team demonstrated a dedication to delivering on time and promptly responding to concerns and adjustments. Their personalized, client-centric approach stood out.
Read More
They didn't like the phrase "impossible to do", which made them very solution-oriented.February 19, 2024
A healthcare company hired Citrusbug Technolabs to design and develop a user-friendly application. The team provided tailored assistance to meet the client's requirements.
Citrusbug Technolabs successfully delivered an application that was ready for market. The team was highly professional and well-organized; they stayed focused throughout the engagement and were receptive to changes. Overall, they stood out for their trustworthiness and commitment to excellence.
Read More
They're 100% on time and transparent throughout each stage of the project.February 24, 2024
A financial technology company has hired Citrusbug Technolabs to build a custom web application. The team handles the development and design of the app.
The project is ongoing, but the client has been satisfied with Citrusbug Technolabs' services. The team is very professional — they always respect timelines and provide regular updates to ensure everyone's on the same page. Also, their transparent approach makes them a trustworthy partner.
Read More
"I do believe they are exceptional at where they stand."
Citrusbug Technolabs took on a mobile app development project for a Singapore-based development house. They were provided with UX designs to execute. Currently, they're finalizing and fine-tuning the product.
Citrusbug Technolabs contributed to the successful launch of the product, which has garnered over 10,000 users in just three months. The product has also received support from investors. They consistently followed-up with their progress and delivered at a speedy rate. The team is truly stellar.
Read More
CarePoint is a comprehensive pharmacy and clinical management solution developed by Citrusbug, centralizing inventory, patient prescriptions, dispensing workflows, and compliance reporting for multi-location healthcare operations.
A state-of-the-art wellness and patient engagement platform built for Mediyoga, integrating guided care programs, health tracking, and provider-patient communication into a unified digital experience.
Designed for healthcare providers and researchers, the platform enhances early detection of neurological conditions
Custom Software Development
Medical imaging software plays an integral part in the modern world of healthcare. It is the engine behind the instruments that allow clinicians to see inside the human body, identify…
Read Article →
Custom Software Development
Healthcare providers today use a wide range of medical devices, from bedside monitors and ventilators to imaging systems and wearables. Such devices are continuously generating useful patient information, but in…
Read Article →
Artificial Intelligence
The healthcare sector is riding the wave of more advanced, data-driven modalities, and diagnostics is a part of the paradigm change. The integration of advanced technologies and AI-powered diagnostics means…
Read Article →Modernization migrates existing infrastructure storage, DICOM routing, viewer to a cloud-native or API-based architecture while preserving existing study data and workflows. A new build starts from defined clinical requirements with no legacy constraints. The right choice depends on your current vendor agreements, DICOM data volumes, and integration debt with downstream systems.
From scoping to 510(k) submission, most AI-enabled imaging SaMD projects run 18 to 30 months. Clinical validation, IEC 62304 documentation, risk management, and software SBOM preparation add 4 to 8 months beyond pure development. Teams that embed compliance from sprint one reduce this by 20 to 30 percent.
At minimum: DICOM PS3 storage SOP classes relevant to your modalities, DICOMweb APIs (WADO-RS, STOW-RS, QIDO-RS) for cloud-native access, and DICOM TLS for encrypted transport. Specialty requirements vary, mammography platforms need DICOM for Mammography (PS3.3 C.8.31), whole-slide imaging requires Supplement 145 support.
Yes. We use FHIR R4 ImagingStudy and DiagnosticReport resources for bidirectional integration with Epic Hyperdrive and Oracle Health. Legacy HL7 v2.x ORM/ORU message support is maintained for RIS systems that have not yet moved to FHIR APIs.
Since June 2025, the FDA requires an SBOM for any networked medical device software submitted for clearance. The SBOM lists all third-party libraries, open-source components, and their versions, enabling ongoing cybersecurity monitoring post-clearance. We build SBOMs in parallel with development so they reflect the production codebase, not a retroactive inventory.
A Predetermined Change Control Plan documents how your AI model can be updated post-clearance without triggering a new 510(k) submission. FDA finalized PCCP guidance in December 2024. Without a PCCP, every algorithm update requires a new clearance typically adding 3 to 9 months per update cycle. Including PCCP in the initial submission enables your team to retrain and redeploy on new data within a defined validation framework.
You do. Full source code, trained model weights, training pipelines, compliance documentation, and DICOM conformance statements are transferred to your team at delivery. Citrusbug retains no licensing rights or infrastructure dependency in your production system.
