Review of improved A.I. based Image Segmentation for medical diagnosis applications - Ranjan, Pranshu; Rauf Khan, Pervez (International Journal of Computer Sciences and Engineering, 2025)
Image segmentation is very important application in a biomedical diagnosis use image data analysis. In medical analysis the accuracy of image segmentation has a critical clinical requirement for the localization of body organs or pathologies in order to raise the quality of prediction of disease or infections. This paper covers review that includes several articles in which latest A.I biomedical image segmentation techniques are applied to different imaging color space models. This review article describes how various computer assisted diagnosis system works for achieving the goal of finding abnormal segments of body organs in biomedical images of the MRI, ultrasound etc. It has been observed that those segmentation approach are broadly giving accurate results in which the segmentation of the images is performed by defining an active shape model and then localization of potential area of interest using thresholding.