Jove
Visualize
Contact Us

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Generation of Prior Information in a Dual-Mode Microwave-Ultrasound Breast Imaging System.

Sensors (Basel, Switzerland)ยท2022
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Oct 22, 2025

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

22.7K

Novel Stopping Criteria for Optimization-Based Microwave Breast Imaging Algorithms.

Cameron Kaye1, Ian Jeffrey1, Joe LoVetri1

  • 1Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Journal of Imaging
|August 30, 2021
PubMed
Summary

Automated stopping criteria were developed for microwave breast imaging using the discontinuous Galerkin formulation of the Contrast Source Inversion algorithm (DGM-CSI). These criteria improve reconstruction efficiency by intelligently determining when to change imaging frequencies or end the process.

Keywords:
Kolmogorov-Smirnov (K-S) testbreast imagingcontrast source inversion (CSI)discontinuous Galerkin method (DGM)microwave imagingstopping criteria

More Related Videos

Troubleshooting FoCUS Image Acquisition: Patient Positioning, Transducer Manipulation, and Image Optimization
06:50

Troubleshooting FoCUS Image Acquisition: Patient Positioning, Transducer Manipulation, and Image Optimization

Published on: March 3, 2023

1.8K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.1K

Related Experiment Videos

Last Updated: Oct 22, 2025

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

22.7K
Troubleshooting FoCUS Image Acquisition: Patient Positioning, Transducer Manipulation, and Image Optimization
06:50

Troubleshooting FoCUS Image Acquisition: Patient Positioning, Transducer Manipulation, and Image Optimization

Published on: March 3, 2023

1.8K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.1K

Area of Science:

  • Medical Imaging
  • Computational Electromagnetics
  • Applied Mathematics

Background:

  • Microwave breast imaging utilizes the Contrast Source Inversion (CSI) algorithm, often implemented with a discontinuous Galerkin formulation (DGM-CSI).
  • Frequency-cycling reconstruction techniques enhance image quality but require appropriate stopping points for frequency shifts and algorithm termination.
  • Previous DGM-CSI methods used fixed iteration counts, leading to arbitrary and potentially suboptimal reconstruction.
  • Tissue-dependent geometrical mapping has improved initial guesses in frequency hopping, but lacked automated control over the inversion process.

Purpose of the Study:

  • To introduce automated stopping criteria for the DGM-CSI algorithm in microwave breast imaging.
  • To enhance the efficiency and objectivity of frequency-cycling reconstruction.
  • To improve the determination of optimal times for frequency shifts and global algorithm termination.

Main Methods:

  • Modification of the discontinuous Galerkin formulation of the Contrast Source Inversion algorithm (DGM-CSI).
  • Implementation of automated stopping criteria based on statistical analysis of data error.
  • Utilizing the two-sample Kolmogorov-Smirnov (K-S) test to analyze data error distribution patterns across past iterations.
  • Applying these criteria to determine optimal frequency shifts and algorithm termination points.

Main Results:

  • The developed stopping criteria intelligently identify suitable moments to shift imaging frequencies during reconstruction.
  • The criteria provide an objective method for globally terminating the DGM-CSI algorithm.
  • The automated stopping criteria improve the efficiency of DGM-CSI reconstructions.
  • Image quality achieved with the new criteria is comparable to reconstructions using a fixed, often overestimated, number of iterations.

Conclusions:

  • Automated stopping criteria based on the Kolmogorov-Smirnov test offer an intelligent and efficient approach to DGM-CSI in microwave breast imaging.
  • This method enhances the practical application of frequency-cycling reconstruction by removing arbitrary iteration limits.
  • The findings suggest improved objectivity and performance in dielectric property imaging of breast tissue models.