Knee Osteoarthritis Labeling Assistant

Get DemoComing soon


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.

DE Cost driver

DE Inconsistent

DE Subjective


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

DE Increased throughput

DE Reliable measurements

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

DE Standardized reading

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


K €

DE The annual cost per patient ranges up to €10k



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



DE Knee-OA has a lifetime risk of 45%


IB Lab 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.

IB Lab 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



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

Easy to monitor

Facilitates monitoring of knee osteoarthritis progression

Saves time

Enables instant, verifiable decision making in difficult cases

Vorgesehene Verwendung

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.

Das sagen unsere Kunden:

Jack Farr - Orthopedist

Die KI-Software von ImageBiopsy ist innerhalb unseres PACS-Systems hochpräzise und effizient, dadurch erhalten wir wertvolle Informationen über den Status des Knies entlang des Kontinuums von Chondrose zu Arthrose.

Jack Farr, MD

Die Integration der KI-Lösungen von ImageBiopsy Lab in unser RIS und unser PACS ist simpel. Es macht Spaß, damit zu arbeiten und der visuelle Bericht ist eine ideale Unterstützung bei der Beratung unserer Patienten.

Dr. med. Mueller-Stromberg

KI-basierte Lösungen sind weniger arbeitsintensiv und die Befunde sindgenauer. Man erhält einen objektiven Wert, der zur Überwachung und Prognose des Verlaufs genutzt werden kann. Wir bieten etwas, das andere nicht haben.

Priv.-Doz. Dr. Gruber

Eine genaue Diagnose und reproduzierbare Nachuntersuchungen sind für eine erfolgreiche Arthrosetherapie unverzichtbar. Software-basierte Verfahren können dem medizinischen Fachpersonal bei der Steuerung und Anpassung der Behandlung unterstützen.

Prof. Jochen Hofstätter, MD