Analysis of Blood Cell Detection Using Radial Symmetry and Ellipse Fitting Approaches

This paper addresses essential hematology that is automatically segmenting blood cells. We consider a unique hybrid ellipse fitting (EF) based blood-cell segmentation technique that combines noniterative-geometric and algebraic approaches to overcome current concerns with inaccurate seed-point identification, noise, and over-segmentation. We propose a hybrid EF approach based on least-squares (LS) for improved segmentation performance. To enhance segmentation while retaining a reasonable EF, we advise utilizing the specified value for the residue offset and computing the minor and major axes using the residue and offset residue variables. Different evaluation matrices such as precision, and F1 score are used where our approach performs better than existing EF algorithms. This approach is computationally effective and might be used in cybernetics and medicine.