International Journal Of Imaging

Abstract

VLSI Implementation of chest X-Ray image segmentation using hybrid clustering

Author: P. Sasi Hemanth, S. Anuradha , B. Manisha , Mrs. C. Sridevi

Abstract:

Chest X-ray imaging plays a critical role in diagnosing pulmonary diseases, with approximately 30 million chest X-ray procedures performed annually worldwide. Despite its prevalence, traditional image segmentation techniques, particularly threshold segmentation, often struggle with variability in lighting and contrast, leading to suboptimal performance in accurately delineating anatomical structures. These limitations necessitate a more robust approach to segmentation that can effectively handle diverse imaging conditions while maintaining high accuracy. This work presents a novel hybrid k- means clustering method for the segmentation of chest X-ray images, leveraging the strengths of both k-means clustering techniques. By integrating these approaches, the proposed method enhances segmentation accuracy and robustness, particularly in regions with overlapping features. hybrid algorithm effectively reduces sensitivity to noise and variability in image quality, significantly improvi