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Xenophon Papademetris, PhD

Professor of Biomedical Informatics & Data Science, and Radiology & Biomedical Imaging
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Additional Titles

Director: Image Processing and Analysis, Bioimaging Sciences, Radiology and Biomedical Imaging

Contact Info

Biomedical Informatics & Data Science

PO Box 208009

New Haven, CT 06520-8009

United States

About

Titles

Professor of Biomedical Informatics & Data Science, and Radiology & Biomedical Imaging

Director: Image Processing and Analysis, Bioimaging Sciences, Radiology and Biomedical Imaging

Biography

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.

Appointments

Education & Training

Postdoctoral Fellow
Yale University, New Haven, CT (2002)
PhD
Yale University (2000)
BA
Cambridge University, Electrical and Information Sciences (1994)

Research

Overview

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.

Medical Subject Headings (MeSH)

Biomedical Engineering; Brain; Imaging, Three-Dimensional; Radiology; Software

Research at a Glance

Yale Co-Authors

Frequent collaborators of Xenophon Papademetris's published research.

Publications

2024

2023

2022

Academic Achievements & Community Involvement

  • activity

    Association for the Advancement of Medical Instrumentation (AAMI)

  • activity

    (1) Tutorial Introduction and (2) Looking backwards: Lessons from Medical Device Regulations for Academic Medical Imaging and AI Research

  • honor

    IEEE Senior Member

  • honor

    Awarded Yale Medical School Brown-Coxe Yale Postdoctoral Fellowship

  • honor

    “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

Get In Touch

Contacts

Mailing Address

Biomedical Informatics & Data Science

PO Box 208009

New Haven, CT 06520-8009

United States

Locations

  • 100 College Street

    Academic Office

    Fl 9th, Rm B931

    New Haven, CT 06510