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 Experiment Video

Updated: May 25, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Biomedical image segmentation via constrained graph cuts and pre-segmentation.

Zeyun Yu1, Ming Xu, Zhanheng Gao

  • 1Department of Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA. yuz@uwm.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary
This summary is machine-generated.

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

Unhealthy dietary behavior in refractory functional dyspepsia: a multicenter prospective investigation in China.

Journal of digestive diseases·2014
Same author

How fragility makes phase-change data storage robust: insights from ab initio simulations.

Scientific reports·2014
Same author

GDC-0980-induced apoptosis is enhanced by autophagy inhibition in human pancreatic cancer cells.

Biochemical and biophysical research communications·2014
Same author

Redox and pH-responsive poly (amidoamine) dendrimer-poly (ethylene glycol) conjugates with disulfide linkages for efficient intracellular drug release.

Colloids and surfaces. B, Biointerfaces·2014
Same author

Indirect growth of mesoporous Bi@C core-shell nanowires for enhanced lithium-ion storage.

Nanoscale·2014
Same author

Prevention of anastomotic fistula formation after low-position Dixon Operation.

Pakistan journal of medical sciences·2014
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

This study introduces a novel method for high-fidelity 2D and 3D image boundary segmentation, combining graph-cuts with pre-segmentation techniques. The approach enhances accuracy through user guidance and a graphical user interface (GUI), proving effective on biomedical imaging data.

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Image Processing

Background:

  • Accurate image segmentation is crucial for analyzing 2D and 3D biomedical data.
  • Existing methods may face challenges with complex boundaries and computational efficiency.

Purpose of the Study:

  • To present a high-fidelity method for 2D and 3D image boundary segmentation.
  • To improve segmentation accuracy and efficiency using a novel combination of algorithms.
  • To develop a user-friendly interface for interactive segmentation.

Main Methods:

  • A novel algorithm combining graph-cuts and initial image segmentation.
  • Pre-segmentation using anisotropic vector diffusion and the fast marching method to reduce graph size.
  • Incorporation of user guidance via a graphical user interface (GUI) for minimal graph cut determination.

More Related Videos

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Related Experiment Videos

Last Updated: May 25, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Main Results:

  • Significant reduction in the size of the graph considered for segmentation.
  • Demonstrated high efficiency and effectiveness on various 2D and 3D biomedical imaging datasets.
  • Successful validation of the developed approaches and tools.

Conclusions:

  • The proposed method offers a robust and efficient solution for high-fidelity image boundary segmentation.
  • The integration of user guidance and a GUI enhances accuracy and usability.
  • The technique is well-suited for applications in biomedical imaging analysis.