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Christopher F. Beaulieu MD, PhD, is Professor of Radiology, Associate Chair of Education, and former Chief of Musculoskeletal Imaging at Stanford University in Palo Alto, California, USA. He received his MD degree and a PhD degree in Biological Structure from the University of Washington in Seattle, WA. He was a resident and chief resident in radiology at Duke University in Durham, NC, followed by a fellowship in Body Imaging at Stanford. He was a visiting fellow in musculoskeletal imaging (MSK) at the University of California, San Diego. His research has focused on computer graphics, computer-aided diagnosis, artificial intelligence, as well as numerous technical and clinical musculoskeletal imaging and interventional projects. He has a popular YouTube channel that highlights a variety of clinical topics in MSK. His most recent academic work involves development of an open-source teaching and learning software platform “STELLA” – the STanford Electronic Learning Library and Applications system, which went live at Stanford in 2023.
My group works on technological developments in diagnostic imaging. Specifically, we have developed computer graphics methods for evaluation of imaging data such as CT colonography which is now widely used to screen for colonic polyps. As part of that work, we developed a number of supervised learning methods that automatically detect polyps (computer aided detection). More recently, my attention has focused on medical informatics and machine learning. The overall aim is to make medical imaging data much more computationally accessible so that prior instances of imaging diagnoses can help inform and improve diagnosis in new clinical cases. An example of this is the use of Bayesian modeling of bone tumors and automatic generation of differential diagnosis for focal bone lesions. We have also worked on liver lesions and more recently on deep learning methods for diagnosis in knee MRI.