With all the challenges facing radiologists, saving time is crucial. To accomplish that, you need fewer clicks. contextflow develops the components necessary for deep integrations, so comprehensive chest CT insights are available to users directly in their native viewer. No clickouts necessary.
Smart(er) Worklist
We can populate your worklist with the following quantifications:
- Number of nodules detected
- Average diameter of largest nodule (mm)
- Lung coverage values (%) for anomalies
Secondary Capture
Visualize detected findings and nodules in color from within your native viewer.
Structured reporting
Quantifications are pre-populated into the reporting tool
Testimonials
We are very interested in using tools based on artificial intelligence like contextflow SEARCH to support the decision in the diagnostic process based on the image.
Lluís Donoso Bach
President of the International Society of Radiology
At Dubrava University Hospital, we take pride in providing the best care possible to our patients. There are many AI radiology solutions, but we agreed to the proof of concept with contextflow because their solution provides real value, particularly for new residents.
Boris Brkljacic
President of the European Society of Radiology
We’re very interested in using AI to improve the hospital experience for both doctors and patients; contextflow’s use of deep learning, particularly for lung diseases, is exactly the type of technology we want to evaluate. I very much look forward to the results.
Christian Herold
Head of Radiology at Vienna General Hospital
I really like the transparency of contextflow SEARCH as opposed to other black box AI solutions. It’s designed to support my workflow while leaving the final decision up to me.
Elmar Kotter
Vice Chair and Head of Imaging Informatics at the Department of Radiology at Freiburg University Medical Center
After using and advising several radiology AI software companies, I can say that what contextflow offers is actually the next generation of AI products to support the radiologist, not replace them. Their general approach means they recognize all relevant findings, not just one.
Anand Patel
MD, Chief of Interventional Radiology, Providence Little Company of Mary Medical Centers
contextflow SEARCH Lung CT is one of the applications that certainly fits radiology’s current needs and can simplify the analysis of complex lung pathology. With the right insights and technology, we can succeed in introducing AI in a very attractive way to radiology departments on a global scale.
Erik Ranschaert
Former President of the European Society of Medical Imaging Informatics (EuSoMII), Radiologist at St. Nikolaus Hospital in Eupen
I have been following contextflow’s progress practically since the company’s founding, and their traction in the area of lung CT is impressive. Being able to shape clinical decision support tools that myself and colleagues can benefit from in clinical practice is a big motivator. We’re literally shaping the future.
Jacob Visser
Chief Medical Information Officer & Head of Imaging IT and Value-Based Imaging at Erasmus MC