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

Effects of Intensive Periodized Training with Multi-Strain Probiotic Supplements on Training Adaptation and Exercise Performance in Amateur Runners.

Journal of the American Nutrition Association·2026
Same author

The optical origin of the human skin color 'banana' in CIELAB space.

bioRxiv : the preprint server for biology·2026
Same author

Discovery and evaluation of a 4-(benzothiazol-2-yl)-N-substituted aniline scaffold as MERS-CoV inhibitors.

European journal of medicinal chemistry·2026
Same author

Lessons from α-RuCl 3 for pursuing quantum spin liquid physics in atomically thin materials.

Journal of physics. Condensed matter : an Institute of Physics journal·2026
Same author

Topology-Regulated Polyurea: From Structural Design to Emerging Applications.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

HAIC Combined with Lenvatinib and Pembrolizumab for Unresectable Hepatocellular Carcinoma: A Retrospective Study.

Journal of hepatocellular carcinoma·2026
Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
See all related articles

Related Experiment Video

Updated: Apr 28, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

6.3K

Replica inference approach to unsupervised multiscale image segmentation.

Dandan Hu1, Peter Ronhovde, Zohar Nussinov

  • 1Department of Physics, Washington University, Campus Box 1105, 1 Brookings Drive, St. Louis, Missouri 63130, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|March 10, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel replica-inference Potts model for unsupervised image segmentation. The method effectively identifies structures across multiple scales, excelling at detecting camouflaged images with high accuracy and speed.

More Related Videos

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

3.6K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

995

Related Experiment Videos

Last Updated: Apr 28, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

6.3K
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

3.6K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

995

Area of Science:

  • Computational physics
  • Image analysis
  • Statistical mechanics

Background:

  • Unsupervised image segmentation is crucial for image analysis.
  • Existing methods face challenges with multi-scale analysis and complex structures.
  • Statistical mechanics offers frameworks for complex system analysis, like community detection.

Purpose of the Study:

  • To develop a replica-inference-based Potts model for multi-scale unsupervised image segmentation.
  • To leverage statistical mechanics principles for robust image structure identification.
  • To enhance the detection of camouflaged images and improve segmentation accuracy.

Main Methods:

  • Applied a replica-inference Potts model inspired by community detection in statistical mechanics.
  • Computed information-theory-based correlations among multiple solutions (replicas) across resolutions.
  • Utilized information theory measures, thermodynamic quantities (entropy, energy), and convergence time as metrics.

Main Results:

  • Identified significant multiresolution structures through replica correlations and information theory overlaps.
  • Analyzed the Potts model phase diagram at zero and finite temperatures.
  • Found optimal parameters within the 'easy phase' for effective unsupervised segmentation, outperforming existing algorithms.

Conclusions:

  • The replica-inference Potts model provides a fast and accurate method for unsupervised, multi-scale image segmentation.
  • The approach is particularly effective for segmenting challenging, camouflaged images.
  • This method offers a robust framework by analyzing phase transitions and solution landscapes.