Jove
Visualize
Contact Us
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 Concept Videos

Glassware Calibration01:11

Glassware Calibration

1.5K
Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
1.5K
Instrument Calibration01:12

Instrument Calibration

799
Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
799
Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

5.0K
In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
5.0K
Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

482
Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...
482
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

4.5K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
4.5K
Frustration and Conflict: Approach-Approach, Approach-Avoidance01:20

Frustration and Conflict: Approach-Approach, Approach-Avoidance

551
Frustration occurs when people are obstructed or prevented from achieving a desired goal or fulfilling a perceived need. For example, when someone's input is ignored in a discussion, it can lead to feelings of frustration. Conflict, however, arises from opposing interests, goals, or actions. Conflicts can take various forms based on the nature of these opposing desires or goals.
One common type of conflict is the Approach–Approach Conflict. In this case, a person faces two desirable...
551

You might also read

Related Articles

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

Sort by
Same author

Reply to Pastore, E.P. Comment on "Rastogi et al. Brain Tumor Detection and Prediction in MRI Images Utilizing a Fine-Tuned Transfer Learning Model Integrated Within Deep Learning Frameworks. <i>Life</i> 2025, <i>15</i>, 327".

Life (Basel, Switzerland)·2026
Same author

Crack Detection in Metallic Structures Using Planar Monopole Antenna.

Sensors (Basel, Switzerland)·2025
Same author

Brain Tumor Detection and Prediction in MRI Images Utilizing a Fine-Tuned Transfer Learning Model Integrated Within Deep Learning Frameworks.

Life (Basel, Switzerland)·2025
Same author

L-Shaped Coplanar Strip Dipole Antenna Sensor for Adulteration Detection.

Sensors (Basel, Switzerland)·2025
Same author

Applications of Chipless RFID Humidity Sensors to Smart Packaging Solutions.

Sensors (Basel, Switzerland)·2024
Same author

Tailoring the Performance of a Nafion 117 Humidity Chipless RFID Sensor: The Choice of the Substrate.

Sensors (Basel, Switzerland)·2023

Related Experiment Video

Updated: Feb 14, 2026

Microwave-driven Synthesis of Iron Oxide Nanoparticles for Fast Detection of Atherosclerosis
08:13

Microwave-driven Synthesis of Iron Oxide Nanoparticles for Fast Detection of Atherosclerosis

Published on: March 22, 2016

11.0K

Tumor Detection and Characterization Using Microwave Imaging Technique-An Experimental Calibration Approach.

Anudev Jenardanan Nair1,2, Suraksha Rajagopalan3, Naveen Krishnan Radhakrishna Pillai3

  • 1Department of Electrical and Electronics Engineering, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India.

Sensors (Basel, Switzerland)
|February 13, 2026
PubMed
Summary

This study presents a microwave imaging system for detecting breast tumors. The system achieved over 96% accuracy in detecting simulated tumors, offering a promising tool for early cancer diagnosis.

Keywords:
SDG3beamforming algorithmdouble ridged horn antennaimage reconstructionmicrowave imagingrelative area of tumor

More Related Videos

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging
04:43

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

Published on: February 27, 2020

7.4K
Experimental Assessment of Mouse Sociability Using an Automated Image Processing Approach
08:24

Experimental Assessment of Mouse Sociability Using an Automated Image Processing Approach

Published on: May 15, 2016

9.0K

Related Experiment Videos

Last Updated: Feb 14, 2026

Microwave-driven Synthesis of Iron Oxide Nanoparticles for Fast Detection of Atherosclerosis
08:13

Microwave-driven Synthesis of Iron Oxide Nanoparticles for Fast Detection of Atherosclerosis

Published on: March 22, 2016

11.0K
Detection of Lung Tumor Progression in Mice by Ultrasound Imaging
04:43

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

Published on: February 27, 2020

7.4K
Experimental Assessment of Mouse Sociability Using an Automated Image Processing Approach
08:24

Experimental Assessment of Mouse Sociability Using an Automated Image Processing Approach

Published on: May 15, 2016

9.0K

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Electromagnetics

Background:

  • Microwave imaging (MWI) offers a non-invasive method for detecting biological tissue anomalies.
  • Comparing electrical properties of healthy and malignant tissues is key to MWI.
  • Early tumor detection is crucial for effective breast cancer treatment.

Purpose of the Study:

  • To introduce and experimentally evaluate a microwave imaging system for breast tumor detection.
  • To assess the system's performance across various tumor sizes and locations.
  • To validate the system's potential for clinical application.

Main Methods:

  • A microwave imaging system using a horn antenna in a monostatic configuration was developed.
  • Simulated tumors with high dielectric contrast were used in a homogeneous background medium.
  • Reflection coefficients were utilized for image reconstruction with a modified beamforming algorithm.

Main Results:

  • The system achieved a minimum accuracy of 96% across all test cases.
  • Evaluation time for image reconstruction was less than 48 seconds.
  • Key metrics including DICE score, IoU, precision, accuracy, sensitivity, and specificity were computed.

Conclusions:

  • The proposed microwave imaging methodology shows promising results for breast tumor detection in controlled environments.
  • The system's high contrast in conductivity aids in antenna and phantom calibration for improved imaging.
  • Further biological studies are needed for potential clinical implementation, contributing to SDG 3.