Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Confocal Fluorescence Microscopy

Confocal Fluorescence Microscopy

Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...

You might also read

Related Articles

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

Sort by

Same author

[Study of electroreflectance spectrum and Franz-Keldysh effect at metal-GaAs interfaces].

Guang pu xue yu guang pu fen xi = Guang pu·2008

Same author

[Study on electro-degradation of new conjugated polymer PFO-BT15 light emitting diodes].

Guang pu xue yu guang pu fen xi = Guang pu·2008

Same author

Comparison of the curative effects of video assisted thoracoscopic anterior correction and small incision, thoracotomic anterior correction for idiopathic thoracic scoliosis.

Chinese medical journal·2008

Same author

Distribution and sources of mercury in soils from former industrialized urban areas of Beijing, China.

Environmental monitoring and assessment·2008

Same author

[Main flavonoids from Sophora flavescenes].

Yao xue xue bao = Acta pharmaceutica Sinica·2008

Same author

External validation and prediction employing the predictive squared correlation coefficient test set activity mean vs training set activity mean.

Journal of chemical information and modeling·2008

Search research articles

Related Experiment Video

Updated: May 17, 2026

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

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

Published on: August 13, 2014

A fast and robust level set method for image segmentation using fuzzy clustering and lattice Boltzmann method.

Souleymane Balla-Arabé¹, Xinbo Gao, Bin Wang

¹State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China. balla_arabe_souleymane@yahoo.fr

IEEE Transactions on Cybernetics

|October 19, 2012

Summary

This study introduces a fast, robust image segmentation method using the lattice Boltzmann method (LBM) and fuzzy c-means. The approach effectively handles intensity variations and noise for accurate object detection in medical and real-world images.

More Related Videos

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

Related Experiment Videos

Last Updated: May 17, 2026

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

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

Published on: August 13, 2014

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

Area of Science:

Computational imaging
Image processing
Numerical analysis

Background:

The lattice Boltzmann method (LBM) is a powerful computational fluid dynamics technique increasingly used for solving partial differential equations.
Image segmentation is crucial for analyzing medical and real-world images, but faces challenges like noise and intensity inhomogeneity.
Existing methods often struggle with accuracy and speed, especially in complex imaging scenarios.

Purpose of the Study:

To develop a novel, efficient, and robust image segmentation technique.
To integrate the lattice Boltzmann method with fuzzy c-means for enhanced segmentation performance.
To address challenges of bias fields and intensity inhomogeneity in image segmentation.

Main Methods:

Designed an energy functional incorporating fuzzy c-means and a bias field correction.
Utilized the gradient descent method to derive a level set equation.
Developed a fuzzy external force for the LBM solver based on Zhao's model.
Implemented a highly parallelizable algorithm for fast computation.

Main Results:

The proposed method demonstrates speed and efficiency in experiments.
Achieved robustness against noise and independence from initial contour placement.
Effectively segmented objects even with significant intensity inhomogeneity.
Successfully detected objects with and without distinct edges in diverse datasets.

Conclusions:

The developed LBM-based fuzzy segmentation method offers a fast and robust solution for image analysis.
The technique shows significant potential for applications in medical imaging and beyond.
The parallelizable nature of the method allows for efficient processing of large datasets.