Assessment of scoliosis related indications on the spine

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To identify and monitor scoliosis, it is crucial to identify relevant parameters on the spine and conduct several measurements, such as the Cobb angle and the coronal balance. Manual analysis of these parameters is tedious, time-consuming and holds a high risk for inter- and intra-reader inconsistencies due to variations in clinical experience.

Intra- and inter-observer inconsistency

High radiation exposure



An integration of an automated AI based software could significantly maximize the reliability and accuracy. In addition, this should allow for a large amount of data to be handled in an automated way. AI can ultimately improve the effectiveness of pre- and postoperative evaluation and maintain a more patient-centered healthcare.

Workflow efficiency

saves time and leads to higher inter-reader agreement

Potentially lower radiation exposure

Patients with scoliosis are exposed to high levels of radiation due to the frequency of examinations. Improvements in standardization and consistency in measurements can potentially decrease the frequency of radiographic examinations and the associated radiation exposure.

Risk factors detection

Assists in detecting risk factors for treatment outcome


Pediatric scoliosis patients receive up to 42 x-ray examinations over the course of treatment



The mean Cobb angle is 5° higher in the afternoon compared to measurements taken in the morning



 AI can reduce reading time of scoliosis x-rays by up to ~90%!

Product description

IB Lab SQUIRREL is a fully automated, radiological image processing software that aims to support physicians in the assessment of spinal morphology and scoliosis evaluation using frontal radiographs of the spine, particularly for the purpose of scoliosis assessment and disease progression. The algorithm is triggered automatically by a scoliosis study and returns relevant scoliosis parameters like the patient’s Cobb angle and the Coronal Balance. All findings are summarized in a visual output report, attached to the original x-ray image and saved automatically in the PACS system. 

IB Lab SQUIRREL facilitates objective scoliosis assessment as well as monitoring disease progression. 

Findings - SQUIRREL V1.00, Research 05/2022:

  • AP/PA full spine
  • Vertebral detection/ labeling
  • Spinal Alignment
  • Cobb angle
  • Coronal balance
  • Calibration ball support
  • Metalwork/Bracing support


Time Savings

in tedious measurements


in determining and measuring the correct cobb angles


in (longitudinal) scoliosis assessment

Intended use

IB Lab SQUIRREL is a radiological fully-automated image processing software device intended to aid medical professionals in the assessment and quantification of scoliosis by automating the measurement of Cobb’s angle and coronal balance on standing full-length spine AP/PA radiographs.

IB Lab SQUIRREL is intended to be used on patients of 10+ years with suspicion or diagnosis of Adolescent Idiopathic Scoliosis.


  • X-Ray (& EOS)
  • Full Spine AP/PA

Patient Population:

  • From 10+ years of age 
  • (Adolescent) Idiopathic Scoliosis
  • Bracing support

Off-Label Use:

  • Patients <10 years
  • Congenital/Neurogenic/Early-Onset Scoliosis
  • Metalwork

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