Enhancing the Segmentation Accuracy of the Otsu Method for Calculating Blood Vessel Rupture Volumes in CT-Scan Images

Abstract

The precise quantification of cerebral hemorrhage volume assumes paramount significance, given its consequential impact on subsequent medical interventions. While antecedent scholarly endeavors have undertaken cerebral hemorrhage volume computations, the attendant accuracy remains amenable to refinement. The main contribution to this research is the development of a rectangle algorithm using the Otsu method, which can be used to calculate the total volume of brain hemorrhage in CT-Scan images of the human brain. The present investigation seeks to augment the segmentation paradigm inherent to the Otsu method, thereby advancing the precision of cerebral hemorrhage volume assessments. The Otsu method is conceived with the purpose of automating the segmentation of the hemorrhagic domain through the determination of threshold values. The refinement of the Otsu method’s accuracy is effectuated by the formulation of an algorithm aimed at maximizing the mean discrepancy between object and background intensities within the object image, predicated upon the ascertained threshold values. These determined thresholds subsequently govern the transformation of grayscale images into binary format, achieved through the quotient of the threshold value and the mean variance, thereby amplifying segmentation precision. The incorporation of variance and mean values in the binarization of grayscale images affords adaptability in threshold modulation commensurate with the intensity spectrum of the image. The research corpus leverages CT-Scan images sourced from RSUP M. Djamil Padang, West Sumatra, encompassing a compendium of 100 image slices culled from a quintet of patients. Empirical findings attest to the fortification of the Otsu method in the segmentation milieu, substantiating the augmentation of threshold value accuracy. This enhancement is conspicuously manifest in the outcomes of segmentation tests, underscoring the superior efficacy of the Otsu method in discerning between objects and backgrounds. The corollary effect is a discernibly more accurate computation of volumes employing the Otsu-T methodology. The import of this research rests in its successful establishment of automated threshold values and the concomitant elevation of segmentation precision.