Medical device R&D · Computer vision & AI since 2004

Image understanding, engineered into medical devices.

iGrok builds software and hardware/software solutions for image-guided medical devices, from classical computer vision to modern machine learning. Exploratory research is fast and broad-based, while production-oriented development is driven within your quality system or the iGrok QMS, built for life-critical products.

What we do

Your product, accelerated by our expertise.

Our products rarely carry the iGrok name. We measure success by how proud our partners are to put their own name on our work, from university spin-offs to multinational device makers.

Fast innovation, proven foundations

Projects start near the finish line. Our continuously refreshed libraries in imaging analysis, registration, treatment planning and workflow give new development a real head start, and we still benchmark against the state of the art.

Fast-start expert teams

Engineering, research, project management, quality assurance and technical communication, staffed by people with deep experience in critical healthcare systems and the domain knowledge to get traction from day one.

Quality built in

A quality management system designed to work our way, your way, or a hybrid. That covers everything from start-ups new to device regulation to multinationals with highly regimented processes.

Capabilities

From pixels and voxels to clinical meaning.

"iGrok" comes from image understanding. Our work combines image processing, computer vision, machine learning, rapid search and optimization to turn torrents of multi-modal data, from CT, MR and ultrasound to endoscopic video, into information clinicians can act on in seconds.

We deliver across desktop, embedded, web and mobile platforms, whichever vehicle best fits the device and the clinical workflow.

  • Image analysis & segmentation
  • Deformable registration
  • Machine & deep learning
  • Optical flow & SLAM
  • 3D modeling & visualization
  • Treatment planning, modeling & control
  • Clinical monitoring
  • Image communication
  • Workflow management
  • Quality assurance

Clinical domains

  • Urology & endoscopyEndoscopic video understanding and device control
  • Radiation oncologyIMRT, IGRT and medical physics: where we started
  • Image-guided neurosurgeryStereotactic, neuro-navigation, electrocorticography
  • Radiology & image-guided ablationAnalysis, guidance and review tools
  • Regulatory & reimbursementFDA 510(k) submissions, CE marking, medical reimbursement
AI in medical devices

We were doing this when it was still called computer vision.

Image understanding has always been machine intelligence: segmentation, registration, classification, and learned models of anatomy and motion. The methods have moved from hand-built features to deep networks and foundation models, and they will keep moving. Medical device R&D still needs the same four things from them: an efficient path to an optimal solution, evidence that it works, a clear account of how it may fail, and a design that keeps patients safe.

AI in the devices we build

  • Training data with known provenance, permitted use, and coverage of the patients, sites and equipment the device will actually meet.
  • Ground truth defined and adjudicated by clinicians, with an annotation process we can defend in a submission.
  • Test data sequestered from development, with performance reported by subgroup and acquisition device, not just in aggregate.
  • Failure treated as a design input: uncertainty estimates, detection of unfamiliar inputs, and a safe fallback when the model shouldn't be trusted.
  • Human-factors work on how clinicians rely on the output, including the risk of over-reliance.
  • Post-release change planned from the start, so a model can improve without restarting the regulatory work.

AI in how we build them

  • AI data management frameworks curate and fully leverage the data that's often the most expensive and valuable asset.
  • AI assistants speed up our coding, testing and documentation. Each use in design-controlled development is defined and validated as a tool under our quality system, for its intended purpose.
  • Your code, data and IP reach an AI service under contractual and technical controls, made consistent with your policies. Some projects use none, by design.

Fast-moving frameworks

AI tools in the R&D process and AI techniques in the end product both move fast: in capability, in expectations, and in regulatory requirements. We continually tune our toolsets and workflows and track guidance as it changes, so we reach safe, effective product quickly, with submission strategies that hold up.

  • IEC 62304
  • ISO 14971 & AAMI TIR34971
  • ISO 13485 / FDA QMSR
  • FDA guidance on AI-enabled device software
  • Predetermined change control plans
  • Good Machine Learning Practice
  • EU MDR & AI Act
  • IEC 81001-5-1

Questions to consider for AI-integrated projects

  1. Does this need to be learned, or would a deterministic method be safer, simpler and easier to validate?
  2. What will the model see in the clinic that it never saw in training?
  3. How will a clinician know when not to trust it?
  4. What will change after release, and how will we show it's still safe?
Quality

Life-critical software deserves exceptional rigor.

High-quality medical software and hardware demand an enthusiastic focus on user experience and exceptional attention to detail, verification and validation. We're committed to a quality process that our clients can see in our work product, and rely on in theirs.

iGrok engages flexibly: entirely within our own Quality Management System, within the framework of yours, or in a hybrid.

Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction and skillful execution; it represents the wise choice of many alternatives.William A. Foster
About iGrok

Twenty years of imaging insight.

iGrok grew from new treatment-time imaging in radiation therapy. That imaging promised to transform how physicians track clinically significant change over a course of treatment, but it buried them in gigabytes of data. Our first tools automatically analyzed and summarized those images so physicians could review weeks of data in seconds.

The technology was first demonstrated in 2004, and the company was founded in 2006 in Sewickley, Pennsylvania, just outside Pittsburgh. Since then our work has spread from cancer care into neurosurgery, urology and a growing range of endoscopic applications, and we draw on sharp minds wherever we find them.

"Grok," to understand completely, comes from Heinlein's Stranger in a Strange Land.

2006Founded in Sewickley, PA
5+Clinical specialties served
510(k) & CERegulatory experience

Work on technology that reaches patients quickly.

Flexible hours, mostly remote, on medical R&D that reaches patients. We're always interested in researchers, developers and interns in computer vision and machine learning.

Careers & internships
Contact

Let's talk about your device.

Whether you're scoping a new product, need imaging expertise on an existing program, or want a quality-minded development partner, we'd be glad to hear from you.

Email us
Email
info@igroksolutions.com
Phone
412-254-4765
Office
iGrok, Inc.
234 Graham St., Suite 200
Sewickley, PA 15143-1872