Research & Publications
I have twenty five plus years of experience in medical image analysis, machine learning, and software development. I have been involved in a variety of imaging projects ranging from cardiac image analysis, image-guided epilepsy neurosurgery, image-guided prostate biopsy, development of methods for real-time fMRI, vascular image analysis and general neuroimaging analysis. We have used both model-based approaches (biomechanical and physiological models) and more data-driven statistical/machine learning approaches. These projects spanned most of the imaging modalities (MRI, CT, Ultrasound, PET, SPECT, Optical), body parts (brain, head, heart, vasculature, prostate, abdomen, hindlimbs) and a variety of species.
In addition to algorithm research, I have been heavily involved in the development of medical image analysis software. My software work (which is directly linked to the image analysis research) has focused on the creation of tools for image analysis both at Yale and as a consultant for industry. My early work (1990s) used C++/Motif/OpenInventor on Silicon Graphics workstations. Later I used C++/Tcl/VTK as part of the creation of the original Yale BioImage Suite software package. More recently, I have focused on the creation of web-based tools using a combination of JS and C++ (via WebAssembly) to create server-less tools that can be run in a browser. Some of the C++ algorithms are also made available for use in Python and MATLAB scripts.
In addition to actual software development, I teach a class on Medical Software at Yale which formed the basis for our recently released textbook “Introduction to Medical Software: Foundations for Digital Health, Devices and Diagnostics” that was just published by Cambridge University Press (Summer 2022) and a Coursera online class titled “Introduction to Medical Software” that was released in October of 2021 and which currently has more than 14000 enrolled students from all over the world. I am also a member of a number of technical standards committees at the Association for the Advancement of Medical Instrumentation (AAMI) on software and artificial intelligence. These committees work on standards that become one of the core inputs in the development of FDA regulations for medical devices and software.
Education & Training
- Postdoctoral FellowYale University, New Haven, CT (2002)
- PhDYale University (2000)
- BACambridge University, Electrical and Information Sciences (1994)
- (1) Tutorial Introduction and (2) Looking backwards: Lessons from Medical Device Regulations for Academic Medical Imaging and AI ResearchVancouver, BC, Canada 2023Medical Image Computing/Computer Aided Intervention 2023 Medical Device Workshop
Honors & Recognition
|IEEE Senior Member||IEEE||2012|
|Awarded Yale Medical School Brown-Coxe Yale Postdoctoral Fellowship||Department Of Diagnostic Radiology, Yale University, New Haven, CT||2001|
|“Harding Bliss Prize for Excellence in Engineering and Applied Science” given to the graduating Ph. D. student who has contributed the most to furthering the intellectual life of the department||Yale University, Graduate School of Arts and Sciences||2000|
|Association for the Advancement of Medical Instrumentation (AAMI)||I am a non-voting member of the following AAMI Standards Committees: AI, SM, SM-WG01 and SM-WG10. (For a full list and description see https://www.aami.org/standards/view-full-committee-list.)||2022 - Present|