Join us at RSNA 2018!

  • We welcome you to visit Quantib in booth #7367H at RSNA 2018, where you can supercharge your practice with machine learning!
  • Get a demo of Quantib™ ND. Our software supports radiologists with dementia diagnosis and MS monitoring by providing automated atrophy quantification of lobes and hippocampus, and white matter hyperintensity segmentation. Reference centile curves, derived from the population-based Rotterdam Scan Study, provide an intuitive tool to compare the patient’s brain volume to a healthy population.
  • Our experts will brief you through advantages of Artificial Intelligence algorithms in medical imaging workflow.
  • Save the date for Quantib’s session: Machine Learning Theatre: Deep Imaging: What Will be the Impact of AI-empowered Image Reconstruction, Diagnosis and Prognosis? | Presented by Wiro Niessen | Sunday 11:00-11:20 AM | ML11 | Room: Machine Learning Showcase North Hall
  • Our satellite locations: Intrasense #8146, GE #7334
  • We look forward to seeing you at RSNA exhibition!
      REQUEST A DEMO   MEET US!

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Accelerated and more accurate dementia diagnosis

With this machine learning radiology application, automatic brain tissue segmentation provides fast insight in the possible presence of atrophy related to Alzheimer’s disease or other types of dementia, supporting more accurate diagnosis. The available reference centile curves derived from the population-based Rotterdam Scan Study enable accurate detection and staging of atrophy.

 

Brain atrophy tracking over time 

 

Quantib ND's follow-up feature allows for tracking of neuro degeneration over time. Based on T1w scans, the radiology software will be able to process scans from subsequent time points and compare quantified volumes of total brain, CSF, lobes, hippocampus and white matter hyperintensities. 

Radiology software to detect and track MS lesions

Automatic assessment of white matter hyperintensity development supports easy and fast monitoring of MS patients. Quantib™ ND medical software distinguishes between new and previously identified WMHs, providing an intuitive visualization with color-coded lesions super positioned on an anatomical map.