Liver Segmentation using Wavelet Coefficients and Level Set Algorithm

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.