Michael Jermyn

Overview

Michael Jermyn, PhD, is an expert in computational solutions for biomedical applications. He has experience in machine learning, cancer imaging, software development, computer vision, optical imaging, and biomedical engineering.

Research Interests

Cancer imaging; machine learning; software development; optical imaging; 3D visualization/analysis

Education

• BS, Computer Science and Mathematics, Tufts University 2007
• MS, Mathematics, Tufts University 2009
• PhD, Biomedical Engineering, Dartmouth 2013

Awards

• Quebec Science #2 Discovery of the Year (2018)
• La Recherche Technology Prize (2017)
• Lewis Reford Fellows Award (2016)
• Tubber Award at William Feindel Conference: 1st place (2015)

Research Projects

• Scintillation dosimetry for quality assurance in radiotherapy

  Scintillation dosimetry for quality assurance in radiotherapy

  Radiation therapy is used to treat cancer tumors by killing the tissue with high ionizing radiation doses. Modern external beam radiotherapy systems deliver high dose levels to precisely marked tumor volume in less time. As a mis-administration can have potentially severe impact to the surrounding healthy tissue, more stringent and complex quality assurance measurements are required in clinics. By developing a comprehensive optical dose imaging camera system, we aim to fundamentally simplify the quality assurance process and, in turn, to further promote the culture of safety in radiotherapy. By converting the dose to visible light using scintillation phantom, we can image and reconstruct 3D dose maps in real time, enabling complete and accurate verification in a fast enough timeframe for it to be useful in every procedure.

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• Machine learning in cancer imaging

  Machine learning in cancer imaging

  Cancer tissue is often impossible to distinguish from healthy tissue during surgery. We have developed optical spectroscopy imaging and detection techniques that make use of sophisticated machine learning techniques to distinguish cancer tissue in real-time.

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• Cerenkov imaging in radiation therapy

  Cerenkov imaging in radiation therapy

  Radiation therapy is used to treat cancer tumors by killing the tissue with high ionizing radiation doses. Until recently it has not been possible to image the radiation dose delivered to tissue, but through Cherenkov light imaging, this delivered dose can be mapped with high resolution cameras. The research group focuses on quantification of the imaging, and developing tools which allow radiation therapy to be delivered in a safer and more validated manner.

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Selected Publications

• S. Decker, A. Matous, R. Zhang, D. Gladstone, E. Grove, B. Williams, M. Jermyn, S. McVorran, L. Jarvas, Cherenkov imaging combined with scintillation dosimetry provides real-time positional and dose monitoring for radiotherapy patients with cardiac implanted electronic devices. Phys. and Imaging in Radiation Oncology. (2024), doi:10.1016/j.phro.2024.100642.
• J. Hallett, P. Bruza, M. Jermyn, K. Li, B. Pogue, Noise & mottle suppression methods for cumulative Cherenkov images of radiation therapy delivery. Phys. Med. Biol. (2024), doi:10.1088/1361-6560/ad8c93.
• D. Alexander, S. Decker, M. Jermyn, P. Bruza, R. Zhang, E. Chen, et al., One year of clinic-wide Cherenkov imaging for discovery of quality improvement opportunities in radiation therapy. Pract Radiat Oncol. (2023), doi:10.1016/j.prro.2022.06.009.
• D. Alexander, S. Majji, M. Jermyn, B. Byrd, P. Bruza, T. Li, T. Zhu, Characterization of Cherenkov imaging parameters and positional constraints on an O-ring linear accelerator. Phys. Med. Biol. (2023), doi:10.1088/1361-6560/acfdf2.
• R. Hachadorian, P. Bruza, M. Jermyn, D. Gladstone, R. Zhang, L. Jarvis, B. Pogue, Remote dose imaging from Cherenkov light using spatially resolved CT calibration in breast radiotherapy. Med. Phys. (2022), doi:10.1002/mp.15614.
• T. Miao, R. Zhang, M. Jermyn, P. Bruza, T. Zhu, B. Pogue, D. Gladstone, B. Williams, Computational dose visualization & comparison in total skin electron treatment suggests superior coverage by the rotational versus the Stanford technique. J Med Imaging Radiat Sci. (2022), doi:10.1016/j.jmir.2022.08.006.
• L. Jarvis, R. Hachadorian, M. Jermyn, P. Bruza, D. Alexander, I. Tendler, B. Williams, D. Gladstone, P. Schaner, B. Zaki, B. Pogue, Initial clinical experience of Cherenkov imaging in EBRT identifies opportunities to improve treatment delivery. International Journal of Radiation Oncology*Biology*Physics (2021), doi:10.1016/j.ijrobp.2020.11.013.
• R. Hachadorian, J. Farwell, P. Bruza, M. Jermyn, D. Gladstone, B. Pogue, L. Jarvis, Verification of field match lines in whole breast radiation therapy using Cherenkov imaging. Radiother. Oncol. 160, 90-96 (2021), doi:10.1016/j.radonc.2021.04.013.
• R. Hachadorian, P. Bruza, M. Jermyn, D. Gladstone, B. Pogue, L. Jarvis, Imaging radiation dose in breast radiotherapy by X-ray CT calibration of Cherenkov light. Nature Communications 11(1), 2298 (2020), doi:10.1038/s41467-020-16031-z.
• I. Tendler, A. Hartford, M. Jermyn, E. LaRochelle, X. Cao, V. Borza, D. Alexander, P. Bruza, J. Hoopes, K. Moodie, B. Marr, B. Williams, B. Pogue, D. Gladstone, L. Jarvis, Experimentally observed Cherenkov light generation in the eye during radiation therapy. International Journal of Radiation Oncology*Biology*Physics 106(2), 422-429 (2020), doi:10.1016/j.ijrobp.2019.10.031.
• I. Tendler, P. Bruza, M. Jermyn, J. Soter, G. Sharp, B. Williams, L. Jarvis, B. Pogue, D. Gladstone, Technical note: a novel dosimeter improves total skin electron therapy surface dosimetry workflow. Journal of Applied Clinical Medical Physics (2020), doi:10.1002/acm2.12880.
• T. Miao, H. Petroccia, Y. Xie, M. Jermyn, M. Perroni-Scharf, N. Kapoor, J. Mahoney, T. Zhu, P. Bruza, Computer animation body surface analysis of total skin electron radiation therapy dose homogeneity via Cherenkov imaging. J. Med. Imaging 7(3), 034002 (2020), doi:10.1117/1.JMI.7.3.034002.

Courses

• ENGG 113: Image Visualization and Analysis

News

An infallible hand-held probe to aid cancer surgery
Jun 30, 2017

In the News