World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
36
Citations
4010
World Ranking
5422
National Ranking
240

Overview

Joe LoVetri is affiliated with the University of Manitoba in Canada and has made contributions primarily in the field of Engineering. Their research spans several subfields including Biomedical Engineering, Ocean Engineering, Mechanics of Materials, Electrical and Electronic Engineering, and Radiology, Nuclear Medicine and Imaging.

The central themes of LoVetri's work focus on Microwave Imaging and Scattering Analysis, Geophysical Methods and Applications, Ultrasonics and Acoustic Wave Propagation, Ultrasound Imaging and Elastography, Microwave and Dielectric Measurement Techniques, Geophysical and Geoelectrical Methods, and Electromagnetic Compatibility and Measurements.

LoVetri has a significant record of publications in a range of scientific venues. Frequent publication outlets include:

  • IEEE Open Journal of Antennas and Propagation
  • Journal of Imaging
  • IEEE Access
  • IEEE Antennas and Propagation Magazine
  • 2022 16th European Conference on Antennas and Propagation (EuCAP)

Their recent scholarly papers demonstrate an emphasis on imaging technologies and applications. Notable works include:

  • "Full 3D Microwave Breast Imaging Using a Deep-Learning Technique," 2020, Journal of Imaging
  • "Tissue-Type Classification With Uncertainty Quantification of Microwave and Ultrasound Breast Imaging: A Deep Learning Approach," 2020, IEEE Access
  • "Innovations in Electromagnetic Imaging Technology: The Stored-Grain-Monitoring Case," 2020, IEEE Antennas and Propagation Magazine
  • "Improved Tumor Detection via Quantitative Microwave Breast Imaging Using Eigenfunction-Based Prior," 2020, IEEE Transactions on Computational Imaging
  • "CNN for Compressibility to Permittivity Mapping for Combined Ultrasound-Microwave Breast Imaging," 2021, IEEE Journal on Multiscale and Multiphysics Computational Techniques

Throughout their career, LoVetri has collaborated frequently with several co-authors, notably including:

  • Ian Jeffrey
  • Mohammad Asefi
  • Colin Gilmore
  • Vahab Khoshdel
  • Max Hughson

These collaborations and publication venues collectively reflect a research focus integrating advanced electromagnetic and acoustic imaging with deep learning methodologies, particularly in biomedical imaging contexts such as breast cancer detection.

Best Publications

  • A Wideband Microwave Tomography System With a Novel Frequency Selection Procedure

    C. Gilmore;P. Mojabi;A. Zakaria;M. Ostadrahimi

  • Finite-element contrast source inversion method for microwave imaging

    Amer Zakaria;Colin Gilmore;Joe LoVetri

  • Overview and Classification of Some Regularization Techniques for the Gauss-Newton Inversion Method Applied to Inverse Scattering Problems

    P. Mojabi;J. LoVetri

  • Microwave Biomedical Imaging Using the Multiplicative Regularized Gauss--Newton Inversion

    P. Mojabi;J. LoVetri

  • Comparison of an Enhanced Distorted Born Iterative Method and the Multiplicative-Regularized Contrast Source Inversion method

    C. Gilmore;P. Mojabi;J. LoVetri

  • Analysis of Incident Field Modeling and Incident/Scattered Field Calibration Techniques in Microwave Tomography

    M. Ostadrahimi;P. Mojabi;C. Gilmore;A. Zakaria

  • A comparison of numerical techniques for modeling electromagnetic dispersive media

    R. Siushansian;J. LoVetri

  • Derivation and comparison of SAR and frequency-wavenumber migration within a common inverse scalar wave problem formulation

    C. Gilmore;I. Jeffrey;J. LoVetri

  • Microwave imaging of human forearms: pilot study and image enhancement

    Colin Gilmore;Amer Zakaria;Stephen Pistorius;Joe LoVetri

  • Enhancement of Gauss–Newton Inversion Method for Biological Tissue Imaging

    Majid Ostadrahimi;Puyan Mojabi;Amer Zakaria;Joe LoVetri

  • On Super-Resolution With an Experimental Microwave Tomography System

    Colin Gilmore;Puyan Mojabi;Amer Zakaria;Stephen Pistorius

  • A Near-Field Dual Polarized (TE–TM) Microwave Imaging System

    M. Ostadrahimi;A. Zakaria;J. LoVetri;L. Shafai

  • FULL-VECTORIAL PARALLEL FINITE-ELEMENT CONTRAST SOURCE INVERSION METHOD

    Amer Zakaria;Ian Jeffrey;Joe LoVetri

  • Breast Imaging Using Microwave Tomography with Radar-Based Tissue-Regions Estimation

    Anastasia Baran;Douglas J. Kurrant;Amer Zakaria;Elise C. Fear

  • A Novel Microwave Tomography System Based on the Scattering Probe Technique

    M. Ostadrahimi;P. Mojabi;S. Noghanian;L. Shafai

  • Finite-difference analysis of dispersive transmission lines within a circuit simulator

    B. Kordi;J. LoVetri;G.E. Bridges

  • Enhancement of microwave tomography through the use of electrically conducting enclosures

    Colin Gilmore;Joe LoVetri

  • Full 3D Microwave Breast Imaging Using a Deep-Learning Technique.

    Vahab Khoshdel;Mohammad Asefi;Ahmed Ashraf;Joe LoVetri

  • Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique.

    Vahab Khoshdel;Ahmed Ashraf;Joe LoVetri

  • An Experimental Phantom Study for Air-Based Quasi-Resonant Microwave Breast Imaging

    Mohammad Asefi;Anastasia Baran;Joe LoVetri

  • Incorporation of Ultrasonic Prior Information for Improving Quantitative Microwave Imaging of Breast

    Nasim Abdollahi;Douglas Kurrant;Pedram Mojabi;Muhammad Omer

  • Integrating prior information into microwave tomography Part 1: Impact of detail on image quality

    Douglas Kurrant;Anastasia Baran;Joe LoVetri;Elise Fear

Frequent Co-Authors

Elise C. Fear
Elise C. Fear University of Calgary
Lotfollah Shafai
Lotfollah Shafai University of Manitoba
Peter Russer
Peter Russer Technical University of Munich
Christophe Fumeaux
Christophe Fumeaux University of Queensland

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