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

You might also read

Related Articles

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

Sort by
Same author

Nano Silicon Anode without Electrolyte Adding for Sulfide-Based All-Solid-State Lithium-Ion Batteries.

Small (Weinheim an der Bergstrasse, Germany)·2023
Same author

Maternal obesity: A potential disruptor of female fertility and current interventions to reduce associated risks.

Obesity reviews : an official journal of the International Association for the Study of Obesity·2023
Same author

Tanshinone I specifically suppresses NLRP3 inflammasome activation by disrupting the association of NLRP3 and ASC.

Molecular medicine (Cambridge, Mass.)·2023
Same author

Deficiency of the <i>Tmem232</i> Gene Causes Male Infertility with Morphological Abnormalities of the Sperm Flagellum in Mice.

Cells·2023
Same author

RNase H1 facilitates recombinase recruitment by degrading DNA-RNA hybrids during meiosis.

Nucleic acids research·2023
Same author

HIV-1 subtype B Tat enhances NOTCH3 signaling in astrocytes to mediate oxidative stress, inflammatory response, and neuronal apoptosis.

Journal of neurovirology·2023
Same journal

Anti-aliasing-enhanced WaveUNet for clinically reliable 12-lead ECG reconstruction from limited 3-lead input.

Medical & biological engineering & computing·2026
Same journal

Deep multi-modal features based spatio-temporal video regression for non-invasive hemoglobin estimation.

Medical & biological engineering & computing·2026
Same journal

Reduced mechanical strength correlates with decreased elastin content in aortic intima-media tissue: association with dissection in human ascending aortas.

Medical & biological engineering & computing·2026
Same journal

How plaque morphology and stenosis severity govern stent-artery interaction and deployment outcomes: a computational study.

Medical & biological engineering & computing·2026
Same journal

Investigating a relation between amyloid beta plaque burden and accumulated neurotoxicity caused by amyloid beta oligomers.

Medical & biological engineering & computing·2026
Same journal

A robot-assisted eye positioning method with high precision and repeatability for ocular particle therapy: mechanical and geometric assessment.

Medical & biological engineering & computing·2026
See all related articles

Related Experiment Video

Updated: May 7, 2026

Comprehensive Characterization of Tissue Mineralization in an Ex Vivo Model
07:29

Comprehensive Characterization of Tissue Mineralization in an Ex Vivo Model

Published on: September 27, 2024

Inverse finite-element modeling for tissue parameter identification using a rolling indentation probe.

Hongbin Liu1, Kiattisak Sangpradit, Min Li

  • 1Department of Informatics, Centre for Robotics Research, King's College London, London, UK, hongbin.liu@kcl.ac.uk.

Medical & Biological Engineering & Computing
|September 17, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces inverse finite-element modeling (IFEM) methods for identifying tissue properties and locating tumors using indentation. These robust IFEM techniques accurately determine tissue stiffness and tumor depth with minimal error.

More Related Videos

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing
07:07

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing

Published on: December 13, 2016

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

Related Experiment Videos

Last Updated: May 7, 2026

Comprehensive Characterization of Tissue Mineralization in an Ex Vivo Model
07:29

Comprehensive Characterization of Tissue Mineralization in an Ex Vivo Model

Published on: September 27, 2024

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing
07:07

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing

Published on: December 13, 2016

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

Area of Science:

  • Biomechanics
  • Medical Engineering
  • Computational Modeling

Background:

  • Accurate identification of soft tissue mechanical properties is crucial for surgical palpation and diagnosis.
  • Existing methods for tissue parameter identification can be limited in accuracy and speed.
  • Inverse finite-element modeling (IFEM) offers a promising approach for complex material characterization.

Purpose of the Study:

  • To develop and validate IFEM-based algorithms for tissue parameter identification using both uniaxial and rolling indentation probes.
  • To investigate the capability of IFEM for locating and characterizing embedded tumors within soft tissues.
  • To assess the accuracy and robustness of the proposed methods in experimental settings.

Main Methods:

  • Development of IFEM algorithms for uniaxial indentation to identify tissue stiffness (μ).
  • Creation of IFEM algorithms for rolling indentation to locate and identify properties of embedded tumors.
  • Experimental validation using silicone phantoms and porcine kidney tissue.
  • Comparison of estimated properties with standard material testing results.

Main Results:

  • IFEM methods demonstrated good robustness and rapid convergence for both uniaxial and rolling indentation.
  • Estimated tissue properties showed good agreement with standard material tests.
  • Uniaxial indentation achieved <3% error for stiffness estimation in silicone and kidney.
  • Rolling indentation achieved 7-9% error for tumor stiffness (μ) and 1-2 mm error for tumor depth (D) estimation.

Conclusions:

  • IFEM-based methods are effective for rapid and accurate tissue parameter identification and tumor characterization.
  • The developed techniques show significant potential for enhancing surgical palpation and diagnostic capabilities.
  • Experimental results confirm the reliability and precision of the proposed IFEM approaches.