Knee Osteoarthritis Labeling Assistant

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Assessing the loss of cartilage, the hallmark feature of knee osteoarthritis (OA), is difficult to do consistently in practice. Moreover, physicians read an average of 10 knee radiographs per day, amounting to approximately 40 minutes of the daily workload.



Cost driver


Consistent and accurate assessing of radiographic signs of OA does not only increase efficiency but also supports disease management. KOALA™ is here to help!

Reliable measurements

Reliable measurements and accurate indicators: 87% sensitivity and 83% specificity discerning mild from moderate and severe knee OA based on KL score (>=2) 1

Standardized reading

23% increase in physician’s agreement rate to gold standard

Increased throughput



Knee-OA has a lifetime risk of 45%



Over 200M patients worldwide and ~100M knee X-rays in the EU in 2020


K €

The annual cost per patient ranges up to €10k

Product description

KOALA™ uses deep learning technology for detecting radiographic signs of knee osteoarthritis and augments the reporting workflow. The software application scores the stage of osteoarthritis according to the Kellgren & Lawrence grading system. It  also provides precise and automated measurements of the minimum joint space width, as well as assessment of the severity of joint space narrowing, osteophytosis and sclerosis based on OARSI criteria.

KOALA™ highlights relevant clinical findings by applying the latest international medical standards to enable timely and accurate decision making. The findings are summarized in a visual output report, attached to the original x-ray image and saved automatically in the PACS system. The AI-results are fed as text into the predefined RIS-template for accelerated reporting. IB Lab KOALA™ facilitates monitoring of disease progression by facilitating comparison of radiographic disease parameters over time.


  • Kellgren & Lawrence grade
  • Minimum joint space width
  • Joint space narrowing
  • Sclerosis
  • Osteophytosis


Saves time

Enables instant, verifiable decision making in difficult cases

Easy to monitor

Facilitates monitoring of knee osteoarthritis progression


Enhances diagnosing and reporting knee osteoarthritis according to the latest clinical guidelines

Intended use

IB Lab KOALA uses deep learning technology for detecting radiographic signs of knee osteoarthritis and augments the reporting workflow. The system is to be used by trained medical professionals including, but not limited to, orthopedists and radiologists. It should not be used in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis.

What our customers say:

Jack Farr - Orthopedist

ImageBiopsy AI software is highly accurate and efficient within our PACS system, which provides valuable information on the status of the knee along the continuum of chondrosis to arthrosis.

Jack Farr, MD

The integration of the AI ​​solutions by ImageBiopsy Lab into our RIS and PACS is easy and well done. It is fun to work with and the clarity of the visualized report is an ideal support for our patient consultation.

Jochen Mueller-Stromberg, MD

AI-based solutions reduce the amount of work and the findings become more accurate. An objective value is given which can be used both for monitoring and forecasting the progress. We offer something that others don’t have.

Michael Gruber, MD

Exact diagnosis and reproducible follow-up exams are indispensable for a successful osteoarthritis therapy. Software-based methods can assist the physician in the therapy management and adjustment process.

Prof. Jochen Hofstätter, MD