EnvoyAI Partner:

Year Founded: 2016
Area of Focus/Speciality: Bone disease, Osteoarthritis

Hospital Associations:

  • Royal National Orthopaedic - London
  • Orthopedic hospital - Vienna
  • Trauma Center AUVA– Vienna
  • University Hospital - Krems
  • Hanusch Hospital – Vienna
Company Headquarters: Vienna, Austria
Number of Machines: 1
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ImageBiopsy Lab – Beyond Diagnostic

About ImageBiopsy Lab

ImageBiopsy Lab (IB Lab) is a Health-AI startup based in Vienna. We are dedicated to offer solutions for the prediction and assessment of bone diseases of which osteoarthritis (OA) is the most common one worldwide. Standardization and automation in the image grading relieves the physicians of manual work. Changes in cartilage (Joint Space Narrowing as well as Joint Space Area) and bone micro-architecture are automatically assessed, freeing up time resources by automatically generating a patient centric report of the diagnosis.

IB Lab’s mission is to enhance patients diagnostic experience and go beyond the current standard of care. Currently, 100 million people suffer from OA in US and Europe alone. By 2040, this number is predicted to exceed 140 million. Diagnoses are often too late, subjective and might lag details due to time pressure. This demands a solution – now. IB Lab uses state-of-the-art computer-vision and deep learning to efficiently solve these problems.


Reference Sites:

  • Corpus Clinic Vienna, Austria
  • Radiologic Institute Dr. Fruehwald & Partners, Austria
  • Orthopedic Office Dr. Stippler & Partners, Austria
  • Orthopedic Clinic Dr. Papp, Austria
  • University of Bristol, UK
  • St. Georges University, UK
ImageBiopsy Lab Leadership
Dr. Richard Ljuhar

Dr. Richard Ljuhar


MSc Christoph Goetz CTO ImageBiopsy Lab

MSc Christoph Goetz


Msc Philip Meier Head of Business Development

Msc Philip Meier

Head of Business Development

ImageBiopsy Lab Machines | Analyzer JSx and Analyzer BMAx

ImageBiopsy Lab is directly responsible for product and clinical representations

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  • IBLAnalyzer.png
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Automatic assessment of joint space width (JSW), joint space/cartilage area (JSA), osteophytes and sclerosis based on the classification score by Kellgren & Lawrence. Assessment of bone structure characteristics based on a combination of texture analysis algorithms.

  • Applicable Study Types: Conventional knee X-rays
  • Training data source: MOST Study, OAI Study, EpiReuma Study, Local partners
  • Number of studies trained on: > 10,000
  • Statistical performance ROC AUC for OA incidence: 0.8, ROC AUC for OA classification: 0.86
  • Type of model used: Linear-kernel support vector classifiers and Deep learning
  • Regulatory Status: Research use only