Matthew McCormick

Matthew McCormick

Principal Engineer

Matthew McCormick, Ph.D., is a Principal Engineer at Kitware’s office in Carrboro, North Carolina. As a subject matter expert, he manages and makes technical contributions to scientific image analysis projects. Dr. McCormick’s experience spans multiple medical, biological, and geospatial imaging applications.

Dr. McCormick leads the development of the Insight Toolkit (ITK), a high performance, N-dimensional image processing library written in C++ with interfaces in Python and JavaScript. In development for over two decades, ITK is a collaborative effort of the world’s best research software engineers. The open source project provides hundreds of advance algorithm modules, covering topics in image processing, registration, segmentation, quantification, and reconstruction. Dr. McCormick has led the community through two major revisions, ITK 4 and ITK 5, and he has coordinated over 30 releases of the toolkit, each of which comprises developments from 30 to 60 individual contributors. Recently, he architected a port of the toolkit to WebAssembly, called itk.js, to couple ITK with interactive browser visualizations built on vtk.js.

Dr. McCormick’s specialty is diagnostic ultrasound imaging, with an emphasis on radio-frequency-based signal characterization. He has designed and developed innovative solutions for tissue characterization, elastography, and low-cost, portable systems.

Dr. McCormick received a B.S. in Biomedical Engineering with a focus on biomechanics from Marquette University in 2005. While at Marquette, he interned at Boston Scientific Corporation, where he worked on peripheral vascular nitinol stents. He continued his studies in biomedical engineering in the doctorate program at the University of Wisconsin-Madison, where his research covered not only vascular mechanics, but also signal processing, medical imaging physics, and computing. His thesis focused on the characterization of carotid plaque (a primary cause of stroke) with diagnostic ultrasound. The principal aim of Dr. McCormick’s research was to develop algorithms to quantify local deformation in the plaque from raw ultrasound image data. The code developed for this purpose makes extensive use of ITK and the Visualization Toolkit (VTK).

Dr. McCormick has continued to work on cutting-edge research at Kitware since he received his doctorate in 2011. He has been a principal investigator and a co-investigator of several research grants, and he has led various commercial projects. Dr. McCormick serves as a reviewer for journals such as IEEE Transactions on Medical Imaging and the Journal of Open Source Software. He is also an active contributor to conferences for the Medical Imaging Computing and Computer Assisted Intervention (MICCAI) and Scientific Computing in Python (SciPy) communities.

  1. P. Hernandez-Cerdan, B. Paniagua, J. Prothero, J. Marron, E. Livingston, T. Bateman, and M. McCormick, "Methods for quantitative characterization of bone injury from computed-tomography images," in submitted to Society of Photographic Instrumentation Engineers (SPIE) in Medical Imaging Conference 2019, 2019.
  2. J. Prothero, M. McCormick, B. Paniagua, J. Vimort, A. Ruellas, J. Marron, L. Cevidanes, and E. Benavides, "Detection of bone loss via subchondral bone analysis," in Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018. [URL]
  3. H. Greer, S. Gerber, M. Niethammer, R. Kwitt, M. McCormick, D. Chittajallu, N. Siekierski, M. Oetgen, K. Cleary, and S. Aylward, "Scoliosis screening and monitoring using self contained ultrasound and neural networks," in Proceedings of the IEEE International Symposium on Biomedical Imaging, 2018. [URL]
  4. D. Chittajallu, M. McCormick, S. Gerber, T. Czernuszewicz, R. Gessner, M. Willis, M. Niethammer, R. Kwitt, and S. Aylward, "Image-based methods for phase estimation, gating and temporal super-resolution of cardiac ultrasound," IEEE Transactions on Biomedical Engineering, pp. 1-1, 2018. [URL]
  5. S. Gerber, M. Jallais, H. Greer, M. McCormick, S. Montgomery, B. Freeman, D. Kane, D. Chittajallu, N. Siekierski, and S. Aylward, "Automatic Estimation of the Optic Nerve Sheath Diameter from Ultrasound Images," in Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound. Springer International Publishing, 2017, pp. 113-120. [URL]
  6. J. Vimort, M. McCormick, and B. Paniagua, "Computing Bone Morphometric Feature Maps from 3-Dimensional Images," Insight Journal, no. January-December 2017, 2017. [URL]
  7. J. Vimort, M. McCormick, F. Budin, and B. Paniagua, "Computing Textural Feature Maps for N-Dimensional images," Insight Journal, 2017. [URL]
  8. S. Aylward, M. McCormick, H. Kang, S. Razzaque, R. Kwitt, and M. Niethammer, "Ultrasound spectroscopy," in Proceedings of the IEEE International Symposium on Biomedical Imaging, 2016. [URL]
  9. D. Zukić, M. McCormick, G. Gerig, and P. Yushkevich, "RLEImage: run-length encoded memory compression scheme for an itk::Image," The Insight Journal, 2016. [URL]
  10. D. Zukić, J. Vicory, M. McCormick, L. Wisse, G. Gerig, P. Yushkevich, and S. Aylward, "nD morphological contour interpolation," The Insight Journal, 2016. [URL]
  11. X. Liu, M. Niethammer, R. Kwitt, N. Singh, M. McCormick, and S. Aylward, "Low-Rank Atlas Image Analyses in the Presence of Pathologies," IEEE Transactions on Medical Imaging, vol. 34, no. 12, pp. 2583-2591, Dec. 2015. [URL]
  12. M. McCormick, X. Liu, J. Jomier, C. Marion, and L. Ibanez, "ITK: enabling reproducible research and open science," Frontiers in Neuroinformatics, vol. 8, 2014. [URL]
  13. X. Liu, M. Niethammer, R. Kwitt, M. McCormick, and S. Aylward, "Low-Rank to the Rescue – Atlas-Based Analyses in the Presence of Pathologies," in Proceedings of the Internation Conference on Medical Image Computing and Computer Assisted Intervention, 2014. [URL]
  14. L. Ibanez, X. Liu, and M. McCormick, "ITK Bar Camp: Growing the ITK Community," Kitware Source, no. 24, Jan. 2013.
  15. M. McCormick, "New infrastructure for easy multi-threading in itkv4," Kitware Source, no. 24, Jan. 2013.
  16. M. McCormick and T. Varghese, "An Approach to Unbiased Subsample Interpolation for Motion Tracking," Ultrasonic Imaging, vol. 35, no. 2, pp. 76-89, Apr. 2013. [URL]
  17. M. McCormick, T. Varghese, X. Wang, C. Mitchell, M. Kliewer, and R. Dempsey, "Methods for robust in vivo strain estimation in the carotid artery," Physics in Medicine and Biology, vol. 57, no. 22, pp. 7329-7353, Nov. 2012. [URL]
  18. X. Liu, B. Helba, K. Krishnan, P. Reynolds, M. McCormick, W. Turner, L. Ibanez, D. Yankelevitz, and R. Avila, "Fostering open science in lung cancer lesion sizing with ITK module LSTK," The Insight Journal, 2012. [URL]
  19. M. McCormick, N. Rubert, and T. Varghese, "Bayesian Regularization Applied to Ultrasound Strain Imaging," IEEE Transactions on Biomedical Engineering, vol. 58, no. 6, pp. 1612-1620, Jun. 2011. [URL]
  20. M. McCormick, "A lightweight image comparison library," Kitware Source, no. 16, Jan. 2011.
  21. E. Madsen, G. Frank, M. McCormick, M. Deaner, and T. Stiles, "Anechoic sphere phantoms for estimating 3-D resolution of very-high-frequency ultrasound scanners," IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 57, no. 10, pp. 2284-2292, Oct. 2010. [URL]