Medical Imaging / PACS
Zyemed Lumina
A medical imaging platform for storing, managing, retrieving and viewing diagnostic imaging studies.
- DICOM networking
- DICOMweb
- PACS architecture
- Orthanc integration
- OHIF-based diagnostic viewing
- study management
Ronnie Kakunguwo
Biomedical Software Engineer
Medical Imaging · Clinical AI · Digital Health Infrastructure · Intelligent Systems
I am a biomedical engineer and software developer building intelligent systems for healthcare, medical imaging, artificial intelligence and data-driven infrastructure. My work sits at the intersection of medicine, engineering and computing — from PACS and radiology information systems to AI-assisted clinical tools, healthcare data infrastructure, IoT and intelligent software platforms.
Based in Zimbabwe. Building for Africa. Thinking globally.
Engineering Focus
Engineering Beyond Software
I do not see software as an isolated discipline. My background in Biomedical Engineering shapes how I approach technology: understanding the physical system, the clinical environment, the data, the user, the infrastructure and the engineering constraints before writing the software.
Medical Imaging & HealthTech
PACS, RIS, DICOM, DICOMweb, imaging workflows, interoperability and clinical infrastructure.
Artificial Intelligence
Computer vision, language models, medical AI, speech recognition, multimodal systems and edge AI.
Software & Systems Engineering
Backend systems, distributed services, databases, cloud infrastructure, APIs, DevOps and scalable application architecture.
Biomedical & Intelligent Systems
Medical devices, sensors, IoT, embedded systems, robotics and engineering experimentation.
Currently Building
Building Healthcare Infrastructure for Africa
One of my major areas of work is developing technologies under Zyemed, a healthcare technology initiative focused on medical imaging infrastructure, clinical workflows and healthcare AI.
ZYEMED
Modality
↓
DICOM
↓
Lumina ──── Orbis ──── Sonus
│ │
└────── Zyemed Labs ───┘Production
Radiology Information System
Zyemed Orbis
A RIS platform focused on coordinating the operational workflow around diagnostic imaging.
- patient registration
- appointments
- radiology orders
- accession numbers
- modality worklists
- DICOM MWL
Clinical Voice & Reporting Intelligence
Zyemed Sonus
An exploration of speech recognition and intelligent reporting tools for clinical environments.
- medical speech recognition
- radiology dictation
- voice workflows
- language models
- structured reporting
- medical terminology
Research & Development
Zyemed Labs
A research initiative focused on the data, experimentation and validation needed to build future African healthcare AI systems.
- medical imaging datasets
- de-identification
- annotation
- clinical data governance
- computer-aided detection research
- AI evaluation
Selected Engineering
Selected Work
A selection of systems, experiments and platforms I have contributed to or built.
01
ViewZyemed Medical Imaging Ecosystem
ProductionHealthcare · Medical Imaging · Backend · Infrastructure
An interconnected medical imaging ecosystem covering image management, radiology workflows, reporting and future AI development — now operating with clients.
02
ViewAgricultural AI Systems
ResearchAI · Computer Vision · Remote Sensing
Research and experimentation involving AI for agriculture, including satellite imagery, vegetation indices and crop monitoring.
Engineering Philosophy
How I Approach Engineering
Understand the system first.
Good engineering starts before code. I try to understand the domain, physical constraints, workflow, users, data and failure modes before selecting technologies.
Architecture matters.
The difference between a demo and an operational system often comes down to architecture, observability, security, scalability and maintainability.
Build for real environments.
Systems should account for imperfect internet connectivity, limited computing resources, infrastructure constraints and real user behaviour.
Evidence before assumptions.
Particularly important in healthcare and AI. A model performing well on one dataset does not automatically mean it will work safely in another population or clinical environment.
Engineering is multidisciplinary.
The most interesting problems sit between disciplines: medicine and software, hardware and AI, data and clinical workflows, research and product engineering.
Research & Writing
Research, Experiments & Technical Notes
I document what I learn while exploring biomedical engineering, artificial intelligence, software architecture and medical imaging.
Biomedical Engineering
Biomedical Engineering Is Becoming a Software Discipline
How artificial intelligence, robotics, cloud systems and medical devices are changing the role of biomedical engineers.
AI Infrastructure
Running Language Models With Limited GPU Resources
Lessons from experimenting with quantisation, QLoRA and smaller language models on consumer hardware.
Artificial Intelligence
Building Healthcare AI in Africa Requires More Than Models
Why datasets, infrastructure, clinical validation and local context are just as important as model architecture.
Medical Imaging
PACS vs RIS: Understanding the Radiology Information Flow
A practical explanation of how patient registration, orders, modalities, images, reporting and archives fit together.
Medical Imaging
Understanding DICOM: More Than a Medical Image File
DICOM is often introduced as a file format. In reality, it defines an ecosystem for storing, exchanging, identifying and managing medical imaging information.
Experience
Experience
My professional work spans software engineering, backend systems, artificial intelligence, healthcare technology and product development.
Zyenova Technologies
Founder / Engineer
Building and researching technology products across healthcare, artificial intelligence and intelligent digital infrastructure.
AADS
Software Developer
Working across enterprise software, backend engineering, AI systems and technology platforms.
Mework
Software Developer / Integration Lead
Software development and integration work involving web platforms, backend services and connected systems.
Recognition
Recognition & Community
POTRAZ AI for Impact Challenge
2026Zyemed Labs reached the Top 16 and finished as 4th runner-up in the Data Track, contributing to conversations around healthcare data and artificial intelligence in Zimbabwe.
Africa CDC
Youth digital health engagement and participation in Africa's growing digital health ecosystem.
University of Zimbabwe
Biomedical Engineering graduate with First Class Honours. Academic and technical experience spanning engineering, entrepreneurship and technology development.
Engineering & Innovation
Participation in innovation challenges, research activities, entrepreneurship programmes and technical communities has shaped how I approach technology development.
Let's connect
Building at the intersection of healthcare and intelligent systems.
I am always interested in meaningful conversations around medical imaging, healthcare AI, biomedical engineering, artificial intelligence, software architecture, research collaboration and technology for Africa.
Start a Conversation