Abstract: Sophisticated filtering and morphological procedures form the backbone of a comprehensive image processing methodology aimed at kidney stone diagnosis. The process initiates with the conversion of color images to grayscale, followed by the application of Adaptive Histogram Equalization (AHE) to enhance image contrast. To eliminate noise while preserving edges and ensuring the sharpness of critical features, a bilateral filter is employed. Otsu's adaptive thresholding technique then facilitates the differentiation of distinct stone sections. Further refinement of segmentation is achieved by filling gaps in the binary image and removing small objects. The real image is masked using the generated binary mask, and contrast is subsequently improved. The image is then reconverted to grayscale, high-intensity areas are highlighted, and the region of interest is selected. These systematic processing steps significantly enhance the precision and reliability of kidney stone detection. This methodology offers a novel combination of techniques, including bilateral filtering, advanced morphological procedures, and AHE, providing significant insights and improving precision in the field of medical imaging related to kidney stone diagnosis..
Keywords: Kidney stone detection · Ultra sound image · Otsu’s Thresholding · Bilateral Filtering.
|
DOI:
10.17148/IJARCCE.2025.14160
