Automated Brain CT Image Segmentation for White Matter Extraction

This document presents MATLAB-based automated segmentation technology for brain CT images, specifically designed to isolate cerebral white matter. The automated segmentation of brain CT images represents an advanced image processing technique that leverages MATLAB's computational capabilities to perform precise white matter extraction. The implementation typically involves preprocessing steps like noise reduction using Gaussian filters, followed by segmentation algorithms such as region-growing methods or clustering techniques (like k-means) to differentiate tissue types. Key MATLAB functions employed may include imadjust for contrast enhancement, watershed for boundary detection, and morphological operations for post-processing refinement. This technology holds significant value in medical imaging applications, enabling physicians to improve diagnosis and treatment of various cerebral disorders. Through MATLAB-based automated segmentation, researchers and clinicians can achieve more accurate analysis and understanding of brain structures, providing a powerful tool for both medical research and clinical practice.