MATLAB Program for Lung Field Segmentation Using Single Threshold with Three Different Methods

This MATLAB program implements lung field segmentation using three different single-threshold methods. The program incorporates threshold-based segmentation techniques specifically designed for medical lung imaging analysis. First, we implement the basic single-threshold method, which involves using MATLAB's graythresh() function for automatic threshold calculation based on Otsu's method, followed by imbinarize() for segmentation. Second, we implement a histogram-based threshold selection approach that analyzes the intensity distribution of lung CT images to determine optimal separation points between tissue types. Third, we include an adaptive threshold method that adjusts based on local image characteristics, particularly useful for handling intensity variations across different lung regions. The program integrates these three methods into a unified framework using MATLAB's Image Processing Toolbox functions, allowing users to compare segmentation results through visual output and quantitative metrics. Key functions implemented include image preprocessing using imadjust() for contrast enhancement, regionprops() for analyzing segmented lung morphology, and bwlabel() for connected component analysis. This implementation provides researchers with a practical tool for lung image analysis and serves as a foundation for more advanced segmentation algorithms in medical imaging research.