AI solution for standard radiography fracture detection

BoneView is a trauma decision support tool. BoneView analyzes x-rays, gives an assessment of the presence of fractures at the examination scale and locates the fractures on each image by presenting them to the practitioner directly on his screen, without any other logistical constraint for the doctor.

Detection and localization of fractures on x-ray images

Every X-ray image of an examination is enriched with enclosing boxes around the region where a fracture is present or suspected to be present.

Classification and sorting of exams into three categories

The examination is classified into three categories: presence of a fracture, suspicion of fracture’s presence, or absence of fracture. This automatic triage of cases into three categories, and therefore rapid identification of normal cases can be presented directly at the patient list level.

  • musculoskeletal
  • lumbar rachis
  • anatomical extremities
  • rib cage
  • fracture
  • x-ray
  • detection

Reduce waiting times

Speed up patient care and patient discharge and reduce waiting times.

Reassure your diagnosis

Decrease the number of missed fractures in the emergency room and reassure your diagnosis on normal cases thanks to the algorithm’s high NPV (99.7%).

Improve patient experience

Improve and standardize patient care in the emergency department

Save time, reassure your diagnosis and streamline your workflow with Incepto


Assisting radiologists requires the highest standards. To achieve this, we conducted an ambitious clinical study involving 6 radiologists and 6 emergency physicians who were asked to interpret 600 trauma x-ray examinations, half with BoneView, half without. The combined view of the RN and the practitioner resulted in a 30% reduction in the rate of undetected fractures, while significantly reducing the reading time

Christian Allouche,

CEO Gleamer


  1. Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study. Loïc Duron & al. Radiology. 2021. DOI : 10.1148/radiol.2021203886

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