How does deep learning work? How do you implement AI into your daily practice? What are challenges for AI in radiology? Do you want to learn more?
Training deep learning algorithms for radiology solutions requires large amounts of medical imaging data. How do we obtain good quality, correctly labeled datasets?
We push advanced technology forward to make sure radiologists can spend their time in the best way possible. Our engineers go to great lengths to create user-friendly radiology software solutions for challenging image analyses issues.
I welcome the Quantib™ Brain software in our department because it provides robust quantitative imaging biomarkers. It facilitates a more objective way of evaluating and enables detection of subtle abnormalities.
Quantib™ ND clearly enables constructive multidisciplinary meetings by enabling efficient decision making. It provides a comprehensive overview of imaging results and compares outcomes to a normative database, therefore it enhances the quality of care we can deliver to our patients.
Quantib™ ND allows me to compare my patient’s brain volumetry to a database of thousands of subjects. Now I can quickly detect and quantify deviations from the norm, which is more objective and sensitive than visual assessment alone.