Abstract:
Advances in imaging computation and analytics is revolutionizing how radiographic data is being analyzed. Nowhere is it being felt more than in the field of thoracic radiology. With high resolution and soft tissue-air contrast, clinically available computed tomography scans are being exploited for algorithmic development, which includes AI techniques, leading to improved diagnostics, prognostication and response assessment. Here, I will present my groups’ research in phenotyping of obstructive lung diseases, deep learning feature detection for air trapping quantification and machine learning for improved donor lung screening for transplantation.


Biosketch:
Dr. Craig Galban is an Associate Professor of Radiology who received his doctorate in Chemical Engineering from Florida State University. He has received consistent funding from the National Institutes of Health and has nearly 100 publications in peer-reviewed journals.