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
- heart attacks
- cranial fractures
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- 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
- 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.
- Artificial intelligence pinpoints nine different abnormalities in head scans. Emily Mullin. Nature Medicine (2018). 10.1038/d41591-018-00003-4.