Image Segmentation of Cranial Vault for Clinical Analysis - Prahlad Rao, K (International Journal of Computer Sciences and Engineering, 2025)
For several applications, segmented images gives better insight with increased accuracy and repeatability. Several segmentation algorithms were proposed for clinical purposes to diagnose, treatment and for tracking the progress of disease. Segmenting structures from medical images and reconstruction of specific anatomical shapes is difficult due to large size of datasets, complexity and variability of a given image. It is therefore, better to view the segmented images than the whole scan obtained from CT or MRI. Particularly, in surgical planning over diseased organ, segmented part is enough for visualization than the whole image. For example, if there is fracture in skull bone, it would be sufficient to view the fractured bone from a diagnostic image. Watershed segmentation is widely used in medical image processing applications because it is relatively fast in terms of computational time. An algorithm to segment the cranial vault bone based on Watershed method is presented. It is also implemented for few specific cranial vault abnormalities to demonstrate the results.