Dr Bridge is trained as an engineer, with MEng (Distinction) and DPhil degrees from the University of Cambridge and University of Oxford, respectively. He has worked in the area of medical image analysis for nearly a decade. His work on his doctoral thesis involved the development of a system for analyzing fetal cardiac ultrasound videos using machine learning. From 2017 until 2022, he worked as a machine learning scientist at the MGB Data Science Office developing machine learning models across a range of imaging modalities and medical specialties in collaboration with industry partners. As Director of Machine Learning since 2021 he led a team focused on the deployment of AI models into the medical workflow. He has been affiliated with the Martinos Center since 2020 and joined as full time research staff in October 2022 supported by an award from the Rappaport Foundation. His interests include machine learning methodology development for medical image analysis, translation of AI into clinical practice, and open software and standards for AI model deployment.
DPhil, Engineering Science, University of Oxford
“Highdicom: A Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology”. C.P. Bridge, C. Gorman, S. Pieper, S.W. Doyle, J.K. Lennerz, J. Kalpathy-Cramer, D.A. Clunie, A.Y. Fedorov, and M.D. Herrmann. Journal of Digital Imaging, August 2022
“Development and Clinical Application of a Deep Learning Model to Identify Acute Infarct on Magnetic Resonance Imaging”. C.P. Bridge, B.C. Bizzo, J.M. Hillis, J.K. Chin, D.S. Comeau, R. Gauriau, F. Macruz, J. Pawar, F.T.C. Noro, E. Sharaf, M.S. Takahashi, B. Wright, J.F. Kalafut, K.P. Andriole, S.R. Pomerantz, S. Pedemonte, and R.G. González. Scientific Reports 12, 2154 (2022)
“A Fully Automated Deep Learning Pipeline for Multi-Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest Computed Tomography”. C.P. Bridge, T.D. Best, M. Wrobel, J. Marquardt, K. Magudia, C. Javidan, J.H. Chung, J. Kalpathy-Cramer, K.P. Andriole, and F.J. Fintelmann. Radiology: Artificial Intelligence, 2022 4:1
2022: Rappaport Foundation MGH Research Fellow