Medical Image Processing: MATLAB Implementation Codes and Technical Report

In this technical report, we provide a detailed examination of MATLAB implementation codes and methodologies for medical image processing. Beyond introducing several commonly used MATLAB segmentation techniques, we explore the significance of medical image processing and its applications in healthcare domains. Each method's underlying principles and implementation steps are thoroughly analyzed, accompanied by detailed code examples with practical execution results. The implementation approaches include threshold-based segmentation using graythresh() and imbinarize() functions, region-growing algorithms with seed point selection, and edge detection methods employing Sobel and Canny operators. Furthermore, we discuss the comparative advantages and limitations of various segmentation techniques, while proposing enhancement strategies and optimization suggestions. Through studying this report, readers will gain deeper insights into medical image processing and develop practical skills to effectively apply these methods in solving real-world medical imaging challenges.