AI solution for emergency diagnosis in cranial CT scans

qER is a tool assisting radiologists and emergency services in the detection of brain pathologies. qER analyzes x-rays, detects several brain pathologies such as bleeding or cranial fractures, and integrates the results into the radiologist’s usual reading environment.

Automatic detection, localization and longitudinal monitoring of urgent and critical brain pathologies for the patient

qER detects intracerebral bleeding and its subtypes, heart attacks, tumor mass effects, midline deviation, atrophies and cranial fractures.

Automatic classification and sorting of abnormal exams within a worklist

The qER algorithm gives radiologists and emergency physicians a comprehensive overview of all exams with AI results during the day. Critical cases are highlighted and instantly identifiable

Automated production of a report integrating an annotated image, and detected and localized pathologies.

qER generates a pre-filled report that contains annotated images, information on the urgency or criticality of the exam, as well as any anomalies detected and their location.

  • brain pathologies
  • bleeding
  • heart attacks
  • atrophies
  • cranial fractures
  • x-ray
  • detection

Prioritize patient flow


Prioritize patient flow in emergency settings and improve patient care thanks to this AI triage assistant tool.

Save time


Save time thanks to an automated detection of certain brain pathologies.

Integrate in your infrastructure


Integrate AI support directly into your existing infrastructure and into your regular clinical workflow.

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


C’est l’un des plus grands progrès de l’AI en radiologie à ce jour, parce qu’il élargit le deep learning à l’orientation d’urgence pour de nombreux scans cérébraux.

Dr Eric Topol,

Scripps, USA


  1. National trends in use of computed tomography in the emergency department. Kocher, K. E. et al. Ann. Emerg. Med 58, 452–462 (2011).
  2. Development and Validation of Deep Learning Algorithms for Detection of Critical Findings in Head CT Scans. S. Chilamkurthy, et al. https://doi.org/10.1371/journal.pone.0204155
  3. Chilamkurthy, Sasank, Rohit Ghosh, Swetha Tanamala, Mustafa Biviji, Norbert G Campeau, Vasantha Kumar Venugopal, Vidur Mahajan, Pooja Rao, and Prashant Warier. “Deep Learning Algorithms for Detection of Critical Findings in Head CT Scans: A Retrospective Study.” The Lancet 392, no. 10162 (December 2018): 2388–96. https://doi.org/10.1016/S0140-6736(18)31645-3.
  4. Artificial intelligence pinpoints nine different abnormalities in head scans. Emily Mullin. Nature Medicine (2018). 10.1038/d41591-018-00003-4.

Save time, secure diagnosis and optimize your workflow with Incepto