ABSTRACT
The growing usage of digital image processing practices devoted to health is explicit, aiding in the solution, improving diagnosis, and creating new diagnostic schemes. Histopathological assessments are the first, most common inspections to catch the general patient clinical picture. Still, their cost can be unreachable to populaces of less favored nations. Image processing can analyze numerical and semantic knowledge from several image regions besides extracting quantitative information from them, performing measurements unmanageable to obtain manually, and permitting multiple data types. Metaheuristic techniques are great tools for the segmentation of tissues. This text will handle the separation and calculation of blood cells as a case study where each imagery possesses platelets, red blood cells, and leukocytes. Metaheuristics can enhance the computational blood breakdowns, but this analysis still faces shortcomings as cyber-physical systems advance and more effective big data methodologies make their way into healthcare.
