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 22, 2026

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Template-cut: a pattern-based segmentation paradigm.

Jan Egger1, Bernd Freisleben, Christopher Nimsky

  • 1Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA. egger@bwh.harvard.edu

Scientific Reports
|May 29, 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

Deep PACBED: Multitask analysis of PACBED images using deep neural networks.

Ultramicroscopy·2026
Same author

Can Crowdsourced Annotations Improve AI-based Congestion Scoring For Bedside Lung Ultrasound?

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same author

Subthalamic segmentations in relation to deep brain stimulation volumes in Parkinson's disease.

Acta neurochirurgica·2026
Same author

No link between piriform cortex subregion resection and seizure freedom in two cohorts with temporal lobe epilepsy.

Journal of neurology·2026
Same author

Optimized precision oncology through implementation of a comprehensive molecular analysis pipeline - relevance for additional therapeutic options.

Cancer genetics·2026
Same author

Aromatic amino acid metabolism shapes autophagy-mediated adaptation to iron deprivation in glioblastoma cells.

Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine·2026
Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026
Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026
Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026
Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026
Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026
Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026
See all related articles

This study introduces a novel template-based segmentation method using graph cuts for improved object separation. The new approach enhances accuracy, especially in complex images with similar object and background textures.

Area of Science:

  • Computer Vision
  • Medical Image Analysis
  • Computational Imaging

Background:

  • Traditional graph-based segmentation methods often use uniform node distribution, limiting their ability to segment complex structures.
  • Objects with textures and backgrounds that are similar, or have indistinguishable gray levels, pose significant segmentation challenges.

Purpose of the Study:

  • To develop a scale-invariant, template-based segmentation paradigm for accurate object isolation from backgrounds.
  • To overcome limitations of uniform node distribution in graph cuts for complex segmentation tasks.

Main Methods:

  • Implemented a graph cut segmentation approach utilizing a "template shape" for non-uniform and non-equidistant node sampling.
  • Evaluated the method on 2D images with challenging texture and gray-level similarities between objects and backgrounds.

More Related Videos

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples
09:38

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples

Published on: November 23, 2016

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Related Experiment Videos

Last Updated: May 22, 2026

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples
09:38

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples

Published on: November 23, 2016

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Main Results:

  • The template-based graph cut method demonstrated improved segmentation performance in scenarios with low object-background contrast.
  • Successful application in 3D on brain tumor datasets for neurosurgical planning.

Conclusions:

  • The proposed template-based segmentation paradigm offers a robust solution for scale-invariant object isolation.
  • This technique enhances the precision of segmentation, particularly in medical imaging applications like neurosurgery planning.