Journal of Biomedical Physics and Engineering

Liver Segmentation using Wavelet Coefficients and Level Set Algorithm

Articles in Press

Document Type : Technical Note

Authors

Zahra Firouzian 1
Seyed Enayatallah Alavi 1
Gholamreza Akbarizadeh 2

1 Department of Computer Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

10.31661/jbpe.v0i0.2410-1843
Abstract
In Computed Tomography (CT) scan, liver segmentation is crucial for diagnosing liver diseases. However, it faces challenges, such as partial volume effects, similarities in gray levels with adjacent organs, and variability in liver shapes. This technical note introduces a method combining wavelet coefficients and level set algorithms for precise liver segmentation. The proposed method integrates wavelet-based texture features with level set evolution, reducing reliance on pre-trained models and manual parameter tuning, and also demonstrates improved accuracy compared to existing approaches.

Keywords

Liver
Image Segmentation
Tomography, X-Ray Computed
Wavelet
Journal of Biomedical Physics and Engineering

Articles in Press, Corrected Proof
Available Online from 18 May 2026

Home

Guide for Authors

Submit Manuscript

Guide for Reviewers

Contact Us